for economic growth, the Latin American Structuralist school gave life to an important ...... Kumho. 9. Donglip. Panbon. Dong-Ah. Const. Kukje. Daelim. Hanhwa.
Essays on Economic Growth and Industrial Development: A comparative analysis between Brazil and South Korea
Igor Lopes Rocha
Sidney Sussex College
September 2015
This PhD dissertation is submitted for the degree of Doctor of Philosophy
DECLARATION
This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. This dissertation does not exceed the word limit for the Degree Committee of Human, Social and Political Sciences.
i
SUMMARY
This dissertation consists of four chapters/essays related to the role of the manufacturing sector in economic growth. The concern with the manufacturing sector in the performance of the economic dynamic derives from the longstanding debate surrounding the dichotomy between East Asia and Latin America, particularly South Korea and Brazil, in terms of productive structure. Therefore the thesis is structured as described below. The first chapter, as the theoretical core of this research, systematises the literature on economic growth and industrialisation in which the manufacturing sector plays an important role as the main engine of growth. The main contribution relies on the attempt to systematise the literature on sector specificity in a common channel that comprises the Structuralist, Kaldorian and Neo-Schumpeterian contribution with regards to the role of industrialisation, specifically manufacturing, in economic growth. The second chapter seeks to analyse in a comparative perspective the remarkable contrasts and parallels about the process of economic development undertaken by Brazil and South Korea over the last 60 years. Circumscribed by factors which include the sectoral composition of countries and the role of the state in guiding the developmental path, the main contribution of the chapter is an identification of factors that determined different routes of economic dynamism followed by Brazil and South Korea from the 1980s onwards.
The third chapter analyses the structural transition of Brazil and South Korea through an input-output framework. This analysis investigates these economies regarding their patterns of productive diversification, structural transition and density of industrial chains. The contributions of this chapter to the existing literature are twofold. First, the chapter adopts the methodology proposed by Imbs & Wacziargs (2003) in an inter- and intra-sectoral perspective to identify the path of economic diversification undergone by Brazil and South Korea over the decades. Second, in a complementary analysis, the input-output framework is used to identify and quantify factors that contributed to this pattern of specialisation. The fourth chapter, as in the previous one, uses principally input-output methodologies to compare the Brazilian and South Korean productive structures in terms of productive dynamisms and leading sectors. Moreover, aspects regarding the interdependence of the manufacturing and services are also investigated. The contributions of this chapter are twofold. First, this analysis provides a useful framework to understand specificities and regularities of each economy and methodological referential for further empirical studies of sectoral specificity of growth. Second, this chapter estimates the interdependence between services and manufacturing through a new input-output methodology. Therefore, this study advances some findings presented by the literature and opens an interesting window for future research. Supervisor: Dr Gabriel Palma
Examiners: Dr Ha-Joon Chang (University of Cambridge) and Dr Alfredo Saad Filho (University of London) ii
To my parents, Armando and Fatima, and my brother Felipe.
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TABLE OF CONTENTS INTRODUCTION ..................................................................................................................... 1 STRUCTURE OF THE DISSERTATION AND METHODOLOGY ..................................... 2 CHAPTER 1 – MANUFACTURING AS DRIVER OF ECONOMIC GROWTH ........... 5
Introduction ............................................................................................................................... 5 1.
The structuralist view: An alternative approach to the neoclassical analytical framework ............................................................................................................................................ 8
1.1. The Early Structuralist approach to manufacturing: First insights ......................... 10 1.1.1. Industrialisation: Balanced and unbalanced growth theories ......................... 11
1.2. Latin American Structuralism: Linking underdevelopment to the centre-periphery paradigm.................................................................................................................................. 16 2.
Kaldor’s stylised facts and the contemporaneous debate ................................................. 21
2.1. Manufacturing as engine of growth: from industrialisation to de-industrialisation 22
2.2. Statistical illusions .................................................................................................... 26
2.3. Servicification............................................................................................................ 27 3. 4. 5.
2.4. Productive Fragmentation ........................................................................................ 28
Manufacturing as the main source of productivity growth .............................................. 32 Manufacturing really does matter for the equilibrium in the balance of payments ......... 34 Technological dynamics, innovations and economic growth .......................................... 36
5.1. The catching-up hypothesis: From imitation to innovation ...................................... 37
5.2. Manufacturing shaping a hierarchy of national innovation systems: The case of Machinery industries ............................................................................................................... 40 6.
Concluding remarks ......................................................................................................... 43
Appendix 1.1 - The Kaldor-Dixon-Thirlwall cumulative causation model ............................. 46 CHAPTER 2 – FALLING BEHIND AND MOVING AHEAD: THE BRAZILIAN AND SOUTH KOREAN PROCESS OF INDUSTRIALISATION............................................ 48 Introduction ............................................................................................................................. 48 1. 2.
The Developmental State promoting a Big Push in economic growth ............................ 50
Mapping the Golden Age of the Industrialist Era ............................................................ 52
2.1. Brazil: 1930-1980 ..................................................................................................... 52 2.2. South Korea: 1945-1980 ........................................................................................... 58
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3.
4. 5. 6. 7.
The role of the State and private sector in the industrialisation process .......................... 62
3.1. Creating National Champions: The South Korean Chaebols ................................... 62
3.2. Contrasting developmental patterns ......................................................................... 65
External Debt and Exogenous Shocks ............................................................................. 68 Technological Learning and Industrial Development ...................................................... 71
The “fundamentalist” neoliberal shock ............................................................................ 75 Brazil falling behind and South Korea moving ahead ..................................................... 78
7.1. Brazil: FDI flows and the loss of industrial dynamism............................................. 78 7.2. The loss of manufacturing and productive disarticulation ....................................... 81
7.3. Labour productivity ................................................................................................... 85 7.4. Manufacturing Share and Income ‘Catching-up’ ..................................................... 87 8.
7.5. Export-trajectories: Two historical distinct patterns ................................................ 88 Concluding remarks ......................................................................................................... 92
Appendix 2.1 - Brazil’s Macroeconomic Indicators, 1950-2013 (%) ...................................... 96 Appendix 2.2 - South Korea’s Macroeconomic Indicators, 1950-2013 (%) ............................ 99 Appendix 2.3 – Classification of manufacturing industries by technology group ................. 102
CHAPTER 3 – PRODUCTIVE DIVERSIFICATION, STRUCTURAL TRANSITION AND DENSITY OF INDUSTRIAL CHAINS: ARE BRAZIL AND SOUTH KOREA VERY DIFFERENT? .......................................................................................................... 103 Introduction ........................................................................................................................... 103 1.
2. 3. 4. 5.
Structural change and economic dynamic: Specialisation vs. Diversification............... 105
1.1. The U-shaped curve for Brazil and South Korea .................................................... 106
1.2. Sectoral composition and economic dynamism ...................................................... 111 The structural decomposition analysis ........................................................................... 114
Interpreting results in light of distinct economic policies .............................................. 117 The density of industrial chains ..................................................................................... 121 Concluding remarks ....................................................................................................... 124
Appendix 3.1 – Technical Details ........................................................................................... 127 Appendix 3.2 – Map of sectoral aggregation (UNIDO) ......................................................... 131 Appendix 3.3 – Map of sectoral aggregation (ECLAC-PADI)............................................... 132 Appendix 3.4 – Classification of manufacturing subsectors by technology group ................ 133
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CHAPTER 4 – ENGINES OF GROWTH AND SECTORAL INTERDEPENDENCE IN BRAZIL AND SOUTH KOREA ....................................................................................... 134 Introduction ........................................................................................................................... 134 1. 2.
The relevance of industrial linkages: a Hirschmanian perspective ................................ 136
Output Multipliers and Hirschman-Rasmussen Linkages .............................................. 138
2.1. Output Multiplier..................................................................................................... 138 2.2. Hirschman-Rasmussen Linkages ............................................................................ 140
3.
2.3. Pure Normalised Backward and Forward Linkages............................................... 143 The interdependence between manufacturing and services ........................................... 146
3.1. Opening intersectoral linkages ............................................................................... 147 3.1.1. Forward Linkage decomposition ................................................................... 148
4.
3.1.2. Backward Linkage decomposition ................................................................. 149
Concluding Remarks ...................................................................................................... 151
Appendix 4.1 – Technical Details ........................................................................................... 154 Appendix 4.1 – Map of sectoral abbreviation and aggregation ............................................. 159 Appendix 4.2 - Hirschman-Rasmussen Backward Linkage index (Brazil) ............................. 160
Appendix 4.3 - Hirschman-Rasmussen Forward Linkage index (Brazil) ............................... 161 Appendix 4.4 - Hirschman-Rasmussen Backward Linkage index (South Korea) .................. 162
Appendix 4.5 - Hirschman-Rasmussen Forward Linkage index (South Korea) .................... 163
Appendix 4.6 - Backward and Forward Linkages Decomposition (Brazil, %) ...................... 164 Appendix 4.6 - Backward and Forward Linkages Decomposition (South Korea, %)............ 165 CONCLUSIONS .................................................................................................................. 166 REFERENCES .................................................................................................................... 173
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LIST OF FIGURES Figure 1.1 - Annual GDP growth and change in the share of manufacturing value added in the global manufacturing GDP, 1970-2010.................................................................................... 24
Figure 1.2 - The ‘inverted-U’ relationship between manufacturing and income per capita .... 25 Figure 1.3 - Value added in the Global Value Chain ............................................................... 29 Figure 2.1 - Number of state-owned enterprises created in each year (1950-1990) ................ 66 Figure 2.2 - External Debt, total (% GDP) and Total external debt/exports (ratio), 1961 - 2013 .................................................................................................................................................. 69
Figure 2.3 - Brazil: Foreign Direct Investment, 1990-2008 ..................................................... 79 Figure 2.4 - Brazil: Manufacturing Share in GDP and Value Added by Technology Intensity (%) ............................................................................................................................................ 83
Figure 2.5 - South Korea: Manufacturing Share in GDP and Value Added by Technology Intensity (%) ............................................................................................................................. 84 Figure 2.6 - Labour Productivity and ‘Catching-up’ with the US, 1960-2010 ........................ 86
Figure 2.7 - Share of manufacturing in GDP and relative income gap with the US, 1950-2010 .................................................................................................................................................. 87
Figure 2.8 - Share of Manufacturing and Exports in GDP (%) (1960-2010) ........................... 89 Figure 3.1 - The inter-sectoral U-shaped curve and sectoral share for South Korea ............. 108 Figure 3.2 - The inter-sectoral U-shaped curve and sectoral share for Brazil ........................ 110
Figure 3.3 - The intra-sectoral U-shaped curve for South Korea ........................................... 111 Figure 3.4 - Shares in global manufacturing and GDP .......................................................... 114
Figure 4.1 - Hirschman-Rasmussen BL and FL indices (Average 1995-2009) ..................... 141 Figure 4.2 - Intermediate consumption of services in manufacturing value-added (%) ........ 147
Figure 4.3 - Forward Linkage decomposition (%) ................................................................. 149 Figure 4.4 - Backward Linkage decomposition (%)............................................................... 150 LIST OF TABLES Table 2.1 - Brazilian Economic Development Plans and Economic Indicators ....................... 58 Table 2.2 - South Korean Economic Development Plans and Economic Indicators ............... 62 Table 2.3 - The 10 largest Chaebol groups in South Korea from late 1950s to 2000 .............. 64
Table 2.4 - Major indicators of innovation activities ............................................................... 73
Table 2.5 - Stocks and inflows of foreign direct investment in Brazil, by sector .................... 81
Table 3.1 - Sectoral composition of the manufacturing sector (%), 1990-2008 .................... 112 viii
Table 3.2 - Inter and Intra-sectoral decomposition of output growth (%), 1995-2002 .......... 118 Table 3.3 - Inter and Intra-sectoral decomposition of output growth (%), 2003-2008 .......... 120
Table 3.4 - Import input coefficients for Korea, 1995-2008 .................................................. 122 Table 3.5 - Import input coefficients for Brazil, 1995-2008 .................................................. 123
Table 4.1 - Output Multipliers ................................................................................................ 139 Table 4.2 - Pure normalised backward linkages ..................................................................... 144 Table 4.3 - Pure normalised forward linkages ........................................................................ 145
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“After some four decades of concerned attention of development, we might ask how much economics can explain. Economic theory can determine the necessary, though not the sufficient, conditions of growth. The so-called noneconomic factors account for the gap between the necessary and the sufficient. Any evaluation of development can only state that the necessary conditions for growth exist or are being created; it cannot predict with certainty that growth will actually take place. One can learn a lot from past performance, but the criteria of evaluation are ex ante concepts. They yield a probability judgment and have, therefore, to be continually checked" (Rosenstein-Rodan, 1984, p. 207) “Economic development has much to do with human endowments, social attitudes, political conditions – and historical accidents. Capital is a necessary but not a sufficient condition of progress.” (Nurkse 1953, p.1) “To explain why certain regions have become highly industrialised, while others have not we must introduce quite different kinds of considerations – what Myrdal (1957) called the principle of ‘circular cumulative causation’. This is nothing but the existence of increasing returns to scale – using the term in the broadest sense – in processing activities. (…) As Allyn Young (1928) pointed out in a famous paper, Adam Smith’s principle of ‘division of labour’ operates through the constant sub-division of industries, the emergence of new kinds of specialised firms, of steadily increasing differentiation – more than through the expansion in the size of the individual plant or the individual firm.” Nicholas Kaldor, “The Case for Regional Policies”, 1970 “The most important Agenda of the state relates not to those activities which private individuals are already fulfilling, but to those functions which fall outside the sphere of the individual, to those decisions which are made by no one if the state does not make them. The important thing for government is not to do things which individuals are doing already, and to do them a little better or a little worse; but to do those things which at present are not done at all.” John Maynard Keynes, “The end of Laissez-faire”, 1926
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INTRODUCTION This dissertation consists of four chapters/essays related to the role of the manufacturing sector in economic growth. The concern with the manufacturing sector in the performance of the economic dynamic derives from the longstanding debate about the dichotomy between East Asia and Latin America, particularly South Korea and Brazil, in terms of productive
structure. During the developmental era, despite superficial similarities marked by dictatorial regimes and economic development plans, both regions had employed very different models
of industrialisation. With the outbreak of the debt crisis during the 1980s, these distinct productive structures engendered a clear polarisation of the emerging world expressed in different trajectories and performances. Furthermore, it prompted a wide debate about the industrial pattern and economic policies that contrast the South Korean success with the Brazilian failure in terms of economic development.
Moreover, it raised a controversial debate between mainstream and heterodox
economists. While the conventional view neglects the sectoral-specific approach of the
economic growth, the developmental school states that the specialisation pattern matters for the pace and scope of the development process. Consequently, the literature has explored the dilemma between the capacity of the state in coordinating policies in favour of the
manufacturing sector and the so-called market-friendly policies of the neoliberal approach.
Thus, the main aim of this dissertation is to analyse and compare economic growth and industrial development in Brazil and South Korea, focusing on the importance of the manufacturing sector for economic development. Moreover, this study seeks to summarise
important aspects related to the manufacturing sector in economic growth within a theoretical, historical and empirical approach. Thus, in the light of these propositions, the main questions for which this thesis aims to provide answers are:
Is manufacturing still the main engine of growth?
Why did these countries develop different industrial structures from the 1980s onwards?
How deep is the dichotomy between the Brazilian and the South Korean development patterns?
What are the sectoral engines of growth in Brazil and South Korea? 1
Are manufacturing and services becoming more interdependent in these countries over the years?
STRUCTURE OF THE DISSERTATION AND METHODOLOGY To fulfil the questions summarised in the last section, this dissertation presents four
chapters which diverge widely in scope and methodology. Each chapter/essay is related to the
theme of economic growth and industrial development with current references to important issues neglected by the neoclassical view synthesised in the first chapter. In this way, all of them are structured through a heterodox background where three strands can be highlighted: the Anglo-Saxon and Latin American Structuralism, the Kaldorian and the NeoSchumpeterian approach.
The first chapter, entitled “Manufacturing as driver of economic growth”, is a study
which makes an effort to combine different theoretical strands on development regarding the importance of the manufacturing industry to the economic growth. Through a confluence of
the Keynesian-Kaldorian, Structuralist and Neo-Schumpeterian frameworks, the essay argues that the manufacturing industry presents some special properties which are not found in other
sectors. The discussion constitutes the theoretical core of this dissertation. The first section describes the Anglo-Saxon Structuralism focused on structural change dynamics and the Latin
American Structuralist view of underdevelopment, according to which the economic development results from technical progress induced or enabled by capital accumulation. The
second section seeks to describe the Kaldorian approach to growth, understood as “laws” where Kaldor explains the differences in international growth rates recovering important elements in the contemporaneous debate. The third section investigates the Neo-
Schumpeterian route to development, exploring relations between innovation, economic dynamics and catching-up in a sectoral specific approach.
The second chapter, entitled “Falling behind and moving ahead: the Brazilian and
South Korean Process of industrialisation”, seeks to analyse the remarkable contrasts and
parallels among the development process in these countries over the last 60 years. The first section elucidates briefly the whole of the developmental state for economic growth. The second section, based on a historical retrospection, describes the industrialisation process
from the 1950s to the debt crisis in the 1980s. The third section makes an attempt to evaluate
the role of public and private sectors in the formation of these late industrialised countries. 2
Thus, seeking to answer why the decoupling in growth rates after the 1980s was much more drastic in Latin American countries vis-à-vis Asian economies, the fourth section explains the genesis of the debt crisis. The fifth section analyses the reason behind distinct technological
dynamisms between these two economies and the trajectory of technological learning
undertaken by South Korea. The rise of the neoliberal era is described in the sixth section to give the necessary support to understand the economic policy change from the 1980s onwards. Therefore, the outcomes in terms of industrialisation and sustained economic growth
in a long-term perspective are approached in the seventh section highlighting the dichotomy between Brazil and South Korea in terms of labour productivity, catching-up and exports. The last section presents some concluding remarks.
The third and fourth chapters compose the empirical part of this dissertation with a
focus on Brazilian and South Korean industrial structures. The methodologies used in both chapters are based on the input-output analysis. Therefore, data available at the World InputOutput Database (WIOD) was used when applied to the input-output methodology in a
comparative perspective. This database covers 40 countries for the period 1995-2009, and the
data is available in both current and previous years’ prices. Additionally, the methodology encompassed secondary sources. This included among others The Brazilian Institute of Geography and Statistics (IBGE), The Institute for Applied Economic Research (Ipea), The Bank of Korea (BOK), The Brazilian Central Bank (BCB), The Conference Board and
Groningen Growth and Development Centre, The United Nations Conference on Trade and Development (UNCTAD),
The United
Nations
Industrial
Development
Organization (UNIDO) and The Organisation for Economic Co-operation and Development (OECD).
Hence, the third chapter, entitled “Productive Diversification, Structural Transition
and density of Industrial Chains: Are Brazil and South Korea very Different?”, seeks to analyse the structural transition undertaken by Brazil and South Korea over the decades. The
first section discuss the long-lasting debate on specialisation or diversification and applies the method proposed by Imbs & Wacziarg (2003) to investigate the stages of sectoral
diversification presented by Brazil and South Korea in a inter- and intra-sectoral perspective over the decades. In this part the methodology is also described, including database sources
and level of sectoral aggregation. The second section focuses on the sectoral composition of manufacturing in these economies and their economic dynamism in a global perspective. The
third section, inspired particularly by Chenery’s studies, adopts the so-called structural
3
decomposition analysis (SDA) to investigate distinct factors, i.e. demand, trade and
technological change, which contributed to the movement of specialisation observed in these economies. In the fourth section, the chapter consolidates the understanding of the structural
economic dynamics via movements related to the density of industrial chains. This section advances the input-output methodology employed by Rocha (2011) to estimate imported input coefficients for Brazil and South Korea through the World Input-Output Database (WIOD). The fifth section concludes the chapter.
The final chapter is entitled “Engines of Growth and Sectoral Interdependences in
Brazil and South Korea”. This last chapter uses input-output methodology to study certain growth dimensions of the sectoral structure in Brazil and South Korea. The first section
provides a brief discussion on the relevance of industrial linkages for economic growth, based
mainly on Hirschman’s theory. The second section measures the output multipliers and Hirschman-Rasmussen backward and forward linkages comprising all productive subsectors
of manufacturing, services and the primary sector. The output multiplier indicates how much
is produced for each monetary unit spent on final demand. The Backward Linkage (BL) index
indicates the extent to which a given sector demands from other sectors while the Forward
Linkage (FL) index, in turn, measures the extension to which a given sector is demanded by other sectors. Additionally, in the same section, the Pure Normalised linkages (PNL) – also
known as Guilhoto, Hewing & Sonis (GHS) model – are calculated to evaluate the productive
structure of Brazil and South Korea, considering the size of sectors in the economy each
country. In the face of important findings related to the services sector, the third section analyses the interdependence between manufacturing and services. Finally concluding remarks are provided in the fourth section.
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CHAPTER 1 – MANUFACTURING AS DRIVER OF ECONOMIC GROWTH Introduction Theoretical, historical and empirical evidences have shown the importance of manufacturing
to sustained economic growth. However, over the years, neoclassical economics has neglected such evidences, and advocated the idea that economic growth is sector-indifferent and in some models also activity-indifferent1. A remarkable example of models in which state that
growth is activity- and sector-indifferent are the early neoclassical growth models, i.e. SolowSwan type models and the early endogenous growth models, namely “AK” models (Palma,
2005)2. Solow-Swan type models are a result of classical contributions of Solow (1956, 1957) and Swan (1956) and became the dominant approach for the analysis of economic growth
from mid-1950s until 1970s. However, over the years this model started to be considered by many economists an unrealistic description of the process leading to economic growth. In this approach, since investments have diminishing returns to capital, only continuous
technological changes explain long-term economic growth. In spite of being a central explanatory factor, technological progress is not sector- or activity-specific3.
The dissatisfaction with the assumptions of the Solow-Swan model and its capacity to
explain the non-convergence of living standards in the world economy stimulated further developments in the neoclassical growth theories. Frankel (1962), in an early version of the so-called “AK” growth models, endogenised the main factors, such as technological progress,
There is an important distinction between “activity” and “sector’. Examples of the former are research and development (R&D) and education; examples of the latter are manufacturing, agriculture and services (Palma, 2005). 2 See also Tregenna (2009). 3 Although economists have long recognized the crucial importance of technological change as a major source of dynamism in capitalist economies (especially Karl Marx and Joseph Schumpeter), it was Solow’s work that brought technological progress to prominence in the mainstream economics as a central explanatory factor in the analysis of long-term rate of economic growth. However, somewhat paradoxically, in Solow’s theory technological progress is exogenous, i.e, it is not explained by the model (Snowdon & Vane, 2005). While the Solow model is widely used as a baseline model of economic growth, it is still considered by many to be unsatisfactory as a description of the process leading to economic growth. This is because the model views improvements in total factor productivity (technological progress) to be the ultimate source of growth in output per worker, but does not provide an explanation as to where these improvements come from. In the language of economists, long-term growth is determined by something that is exogenous in the model. 1
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that drive economic growth in the long run4. As pointed out by Palma (2005), recent
endogenous growth theories are also included in this class of models, in which changes in the rate of growth are the result of the cumulative effect of market imperfections arising in the
process of technological progress that operates in an obscure cumulative effect, creating increasing returns5. Despite relevant developments in the neoclassical framework, sectoral and activity specificity were still absent in these theoretical approaches.
In the years that followed, important references regarding activity specificity arose in
the neoclassical theory. The most recent wave of endogenous models, the so-called New Growth Theory, initiated by the research of Paul Romer (1986, 1990)
6
and Robert Lucas
(1988), emerged in response to perceived theoretical and empirical deficiencies associated with the neoclassical growth model. In this approach, economic growth is explicitly attributed to the type of activity presented in the economy, particularly Research and Development
(R&D) and education. Thus, the most important mechanisms concern the creation of new
technical knowledge in R&D departments of firms (Romer, 1990) and the formation of human capital in education processes (Lucas, 1988).
In this type of growth model, neoclassical economics (and also early neo-
Schumpeterian models – such as in Aghion & Howitt (1998) and Grossman & Helpman,
(1991), which focus on technological spillovers) approached the activity specificity as the main source of endogenous growth. Although this approach incorporates the endogenous
characteristics of economic development (in contrast with Solow-Swan models, in which economic development is a result of exogenous shocks), the mechanisms employed continued to assume a self-regulating nature of the growth process, where technological change occurs
automatically and is affected only by macroeconomic aggregates, that is, physical or human capital stocks.
Therefore, although recognising endogenous elements of economic growth, the
importance of sector specificity remained overlooked in the neoclassical approach. Moreover,
Aghion & Howitt (1998) note that Frankel (1962) presented an early AK model that went largely unnoticed by the profession. In this model, the ‘endogenous’ technological progress offsets the growth-cushioning effects of diminishing returns to capital accumulation that characterise the Solow model. However, it is important to highlight that in the heterodox strand, Robinson (1956) was the first to endogenise productivity growth. 5 See Snowdon & Vane (2005), Barro & Sala-i-Martin (2004), and Blankenburg (2000, 2004) for overviews of new growth theories. 6 Romer (1986) explains technological progress as an unintentional by-product of capital accumulation by individual firms. However, a few years later, Romer (1990), dissatisfied with his initial approach, proceeded to develop a second strand of new growth theory which embraces a neo-Schumpeterian framework of endogenous technological change (Snowdon & Vane, 2005). 4
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neoclassical economics presumes that different types of economic sectors are structurally similar enough to be aggregated in a single representative sector. In such a way, both the mechanisms which trigger the process of economic growth and the structural economic
dynamics are ignored. Additionally, inserted in a framework of general equilibrium and selfadjustment of economic variables, this strand of economic thought does not consider
industrial policy as an effective way to promote economic development. In contrast to the structuralist approach, including the Latin American one and the Keynesian-Kaldorian one, traditional neoclassical models, as well as some of the later endogenous growth models,
increasing returns, though generated by research-intensive activities, are explicitly not associated with the size, depth or strength of the manufacturing sector as such or with the
process of capital accumulation within the manufacturing sector. Nor do they allow for specific effects from the manufacturing sector on the R&D activities (Palma, 2005).
In contrast to the traditional neoclassical view, the heterodox literature has emphasised
sectoral specificity as a central feature of the economic growth process. This implies that, as opposed to the neoclassical view, a value-added unit is not necessarily equivalent across
sectors, especially in terms of inducing and enhancing economic growth (Tregenna 2009).
Commonly, the fundamental role of manufacturing in economic growth is only approached by the Structuralist and the Keynesian-Kaldorian views. However, a careful analysis of the heterodox literature reveals that manufacturing is also the main engine of technological
dynamism and specifically a locus of innovation in the Schumpeterian sense. The
convergence of all these theories through a common channel, i.e. the special properties of the manufacturing sector, include a complex linking between theoretical approaches at different
levels of economic theory, i.e. micro (firm), meso (sector and sub-sectors) and macro
(economy). Therefore, as a corollary to this analysis, the heterodox triad composed by the
Structuralist, Keynesian-Kaldorian and Neo-Schumpeterian views constitutes the mainspring of this study.
In this context, the aim of this chapter is to systematise the literature on economic
growth and industrialisation in which the manufacturing sector plays an important role as the main engine of growth. Thus, the main contribution relies on the attempt to systematise the
literature on sector specificity in a common channel that comprises the Structuralist,
Kaldorian and Neo-Schumpeterian contribution to the role of industrialisation, specifically manufacturing, in economic growth. In this way, the first section reviews the main aspects
related to the Anglo-Saxon and the Latin American approaches which, in turn, shed light on
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the industrialisation process as a mechanism to overcome underdevelopment. The second section explores how manufacturing is the main engine of growth in the Kaldorian
framework, understood as “laws” where Kaldor explains the differences in international growth rates and the approach developed for these “laws”, and the importance of manufacturing for the balance of payments. In the third section, another heterodox strand is
considered, i.e. the Neo-Schumpeterian approach, exploring relationships between innovation and economic growth. Particularly, it analyses the idea that manufacturing is also the main
engine of technological dynamism and specifically a locus of innovation. The catching-up
hypothesis is emphasised, highlighting the connection between national systems of innovation
and productive structure. Moreover, the sectoral specificity of the concept of systems of innovation is emphasised. The last section presents some concluding remarks.
1. The structuralist view: An alternative approach to the neoclassical analytical framework Although structuralism is a popular term in the economic field, it is important to
recognise that many concepts are derived from neighbouring sciences such as Levi-Strauss, Godelier (anthropology), Lacan, Piaget (psychology), Althusser, Derrida, Foucault (philosophy) (Palma, 1987; Gibson, 2003; Blankenburg, Palma & Tregenna, 2008).
Therefore, it is possible to conceive structuralist economics, as it emerged in the 1940s, as an
outgrowth or extension of earlier work in these and other fields. Within this multidisciplinary background, structuralist economics is fundamentally a theoretical approach that confronts the neoclassical methods of empiricism and positivism (Palma, 1987). Structuralism uses a
method of inference analogous to that of abduction or retroduction. It begins with an observation of determinate phenomenon, “what is out there”, and then works backward to a theory. Its focus is not on prediction but description and explanation (Baghirathan, Rada & Taylor, 2004). Consequently, structuralism can be understood as an alternative way to
theorise in economics, since the mainstream theory represented mainly by the neoclassical
approach is deductive and expressed in terms of ‘uniformities’ interpreted as (actual or hypothetical) correlations or event regularities.
Furthermore, as pointed out by Blankenburg, Palma & Tregenna (2008),
structuralism takes place in conception of “an integrated system of distinguishable yet mutually constitutive elements”. In other words, the relationships that constitute structures are
more important than individual elements. This assertion is a central feature of the structuralist
8
view and distinguishes this theory from the neoclassical approach7. According to the latter, the analysis of human action can be performed in a micro approach from the perspective of individual agents (methodological individualism). However, in the former, structural analysis
emphasises that interdependent elements of the economic system form a complex whole in a
macro perspective and incorporates systemic properties that cannot be reduced to the analyses of individual elements. Thereby, the hallmark of the structuralist approach is its reliance on
internal relations among parts making up a whole, which is closely related to the methodological holism8 (Jackson, 2003).
In economics, structuralism is principally associated with the so-called Anglo-Saxon
or Early Structuralism and the Latin American strand9. Both strands base their analyses on the
concept of complementarities and poverty traps, linkages, and dualism (Ancochea, 2007). The structuralist view usually stresses that economic development is strongly linked to a radical
transformation in the structure of production to suppress obstacles, bottlenecks and other rigidities of underdevelopment. Based on the hypothesis that the industrial structure affects
both the rhythm and the direction of economic development, structuralist literature highlights
the importance of the industrialisation as a process of structural change where the manufacturing sector plays a central role.
The structuralist strand states that without a dynamic industrialisation, it is not feasible
to increase employment, productivity and income per capita and, consequently, to reduce poverty. The main argument stresses that the development process involves a production reallocation from low productivity to high productivity sectors where increasing returns to
scale prevail. Inserted in this theoretical background, economic structuralism has provided Moreover, as stressed by Street & James (1982), structuralism assumes two basic conceptions against the conventional neoclassical view. The first conception regards the economic system as an evolving process rather than an equilibrating mechanism of stable economic relations centring on market activities. The second conceives of human behaviour as characterised by habitual patterns resulting from cultural conditioning but capable of intelligent response to changing realities. It is thus distinguished from the neoclassical economic view that human behaviour is primarily devoted to utilitarian motivation and pecuniary calculation in a static system of markets. In a convergent analysis, Chenery, writing in the American Economic Review in 1975, exposes the origin of economic structuralism as a general view against the neoclassical approach based on the free market, emphasising the importance of economic planning principally in late-development countries. In other words, economic interventionism is seen as a central variable to overcome various inhibiting factors in economic growth. Consequently, the structuralist approach is an attempt to “identify specific rigidities, lags, and other characteristics of the structure of developing economies that affect economic adjustments and the choice of development policy” (Chenery, 1975, p. 310). 8 For a detailed explanation about the methodological individualism versus the methodological holism, see Kincaid (2008). 9 It is important to emphasise that the French structuralism, represented particularly by François Perroux, was very influential on the Latin American strand which in turn is detailed in the subsection 1.2. 7
9
many reflections on how economic growth should be understood in a historical perspective of
mutual causation in the economic system. While various historical, political and ideological
factors contributed to the structuralist view, Keynesian criticism of the neoclassical economics and its argument regarding state interventionism was principally important.
Paul Rosenstein-Rodan, Ragnar Nurkse, Arthur Lewis, Albert Hirschman, Gunnar
Myrdal and Hollis Chenery belong to the handful of economic thinkers associated with early
structuralism or pioneers of development10. Their seminal contributions challenged the neoclassical view of market efficiency to structural change and recognised particularities through which the manufacturing industry has a central role to support and propel economic
development. A further theoretical contribution comes from Latin American structuralism, which is mainly related to the Economic Commission for Latin America and the Caribbean
(ECLAC), whose works merged into a coherent school of thought in late 1950s. In the light of
historical experiences, the main thoughts presented in this Latin American version are encapsulated in the works of Raul Prebisch and Celso Furtado, focused on the specific challenges faced by developing countries given an world economy divided by two poles, the
“centre” and the “periphery”, and the distinctive structure of production present in these ones (Prebisch, 1949; Furtado, 1964). Problems relating to dualism in international trade, technology disparities, balance of payments constraint and state interventionism were all emphasised.
1.1.The Early Structuralist approach to manufacturing: First insights In economic theory, many studies associate the emergence of the Early structuralism
with the publication of Rosenstein-Rodan’s “Problems of Industrialization of Eastern and
South-Eastern Europe”11. In this study, Paul Rosenstein-Rodan assigned particular emphasis to the transformative power of industrialisation in the economic system (Rosenstein-Rodan, 1943). In a similar line of thinking, Nurkse (1953), Lewis (1954), Hirschman (1958), Myrdal
(1957) and Chenery (1960, 1979) pointed out that the study of long-term economic growth is
a “sector- specific” process and consequently involves an increase of the industry share, which, in turn, provides the highest potential of productivity, spillover effects, forward and backward linkages, as well as technological and pecuniary externalities. Hence, their focuses 10 11
See for instance, Blankenburg, Palma & Tregenna (2008) and Ancochea (2007). Rosenstein-Rodan (1943).
10
were essentially on the internal special properties of manufacturing and on the way in which
these properties spread to the economy as a whole, stimulating the process of economic growth.
Although not always emphasised by the literature, the essence of these classical
contributions relied especially on Allyn Young’s ideas concerning long-term determinants of economic growth which were further extended in their seminal studies. These pioneers of
economic development also focused on the identification of bottlenecks and rigidities that block the industrialisation process in underdeveloped economies. However, in spite of general agreement amongst these pioneering economists that industrialisation was the most efficient
means to support economic development, the emphasis on growth economics through industrialisation engendered a debate over whether “balanced” or “unbalanced” growth was the best strategy to extract and propel economic development through the special properties of manufacturing.
1.1.1. Industrialisation: Balanced and unbalanced growth theories The Early Structuralist approach to manufacturing is particularly associated with
Rosenstein-Rodan’s path-breaking research in economic development, which stresses the
conditions for economic growth in line with Nurkse (1953). Paul Rosenstein-Rodan and
Ragnar Nurkse supported the balanced growth theory based on “classical” arguments
concerning long-run determinants of the economic growth, particularly dynamic externalities
and increasing returns, as advanced by Allyn Young. This type of argument gave rise not only to the role of demand complementarities and increasing returns (to scale) in manufacturing industries, but also various arguments that justify industrial policy, especially of selective type, on the basis of the existence of interdependence between different activities (Chang et al., 2013).
Rosenstein-Rodan (1943) states that a remarkable feature of high-income economies,
i.e. developed countries, is a structured and dynamic industrial sector. Unlike developed economies, underdeveloped countries were characterised by the absence of a structured and
dynamic industrial sector. As a matter of fact, since industrialisation tends to be concentrated in developed countries, massive and planned investments coordinated by the state are sine qua non conditions for the creation of a new institutional environment and, consequently, the successful carrying out of industrialisation in underdeveloped countries. In this way,
11
Rosenstein-Rodan (1943) describes what later became known as the “big push theory”, i.e. a large-scale development programme geared towards jump-starting the economic growth
through the industrialisation process of an underdeveloped economy. Rosenstein-Rodan states
that free market mechanisms would only keep or even increase the distributive inequality
between countries, showing the growing gap between developed and underdeveloped nations. In his own words “the market mechanism does not realize the ‘optimum’ either in one nation or between nations because it relies on such unrealistic assumptions” and “obscures the nature of the development process” (Rosenstein-Rodan, 1984, p. 209).
Regarding planning, the author highlights two crucial points. The first is related to
labour training policies coordinated by the state to transform peasants into industrial workers. This assertion is based on the observation that the automatism of laissez-faire never worked
properly in this field. In other words, from the perspective of an individual firm, investing in
training labour is very risky since if workers move to another firm a considerable loss of
capital may occur. Although not a good investment for a private firm, it is the best investment for the state when analysed the economy as a whole (Rosenstein-Rodan, 1943). The second
and most important argument in favour of such a large investment unit refers to the complementary influence between different industries that potentiates the dynamic effects of
external economies and balances the process of economic growth. The expansion of the market through the creation of a planned complementary system of industries reduces the risk
of demand shortage and, since risk can be considered as cost, it reduces costs and provides the most important set of arguments in favour of a large-scale industrialisation12.
In such a way, a big, comprehensive and balanced investment package between
manufacturing sectors performed by the state, i.e. “the big push” – using Rosenstein-Rodan’s terminology – is the key to the economic development process through positive linkages
effects in the productive chain that enhances the dynamic effects of external economies.
From this perspective, industrialisation has a central role in economic development not only because of the terms of trade differential, as noted by Prebisch, but also due technological and
pecuniary external economies which are the main source of increasing returns to scale – a
As argued by Rosenstein-Rodan (1943) in his shoe factory example, the diversity of human wants creates a necessity for a planned effort to generate a sufficient and sustained expansion of the market. 12
12
central aspect in the development process – and in turn, are much higher in manufacturing industry than in agriculture13.
In a similar view to Rosenstein-Rodan, Nurkse stressed that economic growth is “not a
spontaneous and automatic affair14”. With this assertion in mind, Nurkse (1953) describes the forces that limit the development process in underdeveloped countries. The so-called “vicious circle of poverty” is illustrated as “a circular constellation of forces tending to act and react
upon one another in such a way as to keep a poor country in a state of poverty” (ibid, p.4).
This dynamic, translated in a low level of investment and capital accumulation, operates both
on the supply and demand side. In this way, from the supply side a low level of investment
arises from the small amount of savings available in the economy as a result of its low income level which, in turn, is a consequence of a low level of productivity. Moreover, low productivity is a direct result of small amounts of capital used in the production process and is
related to the low domestic savings presented in the country. From the demand side, similar to Rosenstein-Rodan, the greatest obstacle to development was the atrophy of the domestic
market through low demand for goods due to low income level in the economy which, in turn, discourages the formation of capital. The low level of capital used in the production process is
associated with a weak level of investments that implies a low level of productivity existing in
the country. When the productivity per worker is low, the real income is consequently low
and the poverty vicious circle is complete. Additionally, it is important to emphasise that when analysing the underlying causes of the scarcity of capital, Nurkse (1953) did not treat it just as an issue of resource availability.
The author recognises that underdevelopment was linked to the kind of product
produced by a specific country and how it was traded in the international market. In order to break this circle, a wave of capital investment in various industries should be carried out. This
would enlarge the market size, increase productivity and provide an incentive for the private
sector to invest. As pointed out by Nurkse, the only way out of the dilemma is a “more or less Although Rosenstein-Rodan (1943) clearly approaches the discussion of technological externalities, the discussion of pecuniary externalities discussion is less so. However, Rosenstein-Rodan (1961, 1984) explain it taking into consideration their horizontal and vertical dimensions on both demand and supply sides. According to Rosenstein-Rodan, any expansion of the market through the process of industrialisation leads to external economies, both pecuniary and technological. Pecuniary externalities are market-transmitted or inter-industry interdependencies. Horizontal pecuniary external economies occur between firms producing consumer goods, while vertical pecuniary external economies occur between suppliers and final goods producers. In terms of technological externalities, manufacturing is recognised as a source of effective knowledge (contemporaneously also termed as learning by doing). 14 Nurkse (1953, p.4). 13
13
synchronized application of capital to a wide range of different industries. Here is an escape
from the deadlock; here the result is an over-all enlargement of the market (...) most industries catering for mass consumption are complementary in the sense that they provide a market for, and thus support, each other” (Nurkse, 1953, p. 11).
In contrast to Nurkse and Rosenstein-Rodan, Hirschman did not support the “balanced
growth theory”, arguing that imbalances generated between sectors could provide corrective reactions, giving arguments in favour of a theory of “unbalanced growth”. According to
Hirschman (1958), economic growth is essentially an unbalanced dynamic process, in which successive disequilibria produce the conditions for development in different sectors. In his “unbalanced growth” theory, the productive structure is linked through forward and backward
linkages to downstream and upstream industries. These linkages represent physical relations of supply and demand among sectors of the economy. Thus, backward linkages are associated with the magnitude that each sector demands from other sectors of the economy, while
forward linkages are associated with the extension that each sector is demanded by other
sectors. In this dynamic, manufacturing industry is characterised by both strong backward and
forward linkages, enabling this sector to generate higher economies of scale with positive effects in terms of productivity gains and cost savings in later stages of the production chain. From this perspective, as pointed by Toner (1999), Hirschman focused particularly on the
intermediate and capital goods sectors while Rosenstein-Rodan and Nurkse focused essentially on productivity growth in the consumer goods sector.
Furthermore, while also concentrating on the role of bottlenecks, external economies
and complementarities, Albert Hirschman qualifies the economic development “essentially as
the record of how one thing leads to another” involving not even physical relations of supply and demand, but also technological linkages. It leads to the first insights on the concept of spillover effects, which stems from manufacturing to the rest of the economy and is approached by the contemporary economic developmental literature, e.g., the Kaldorian and
Neo-Schumpeterian strands. Additionally, the author’s opposition to Nurkse’s and Rosenstein-Rodan’s strategies relies on the idea that too many financial resources and
planning efforts would be necessary to stimulate the economy, concluding that “if a country
was ready to apply the doctrine of balanced growth, then it would not be underdeveloped in the first place” (Hirschman, 1958, p. 53-54).
14
In this sense, Hirschman’s strategy rested on the idea that economic policy should
focus on specific industries, i.e. key sectors with a strong interdependence or linkages – both
backward and forward – with other sectors of the economy15. The backward linkage refers to
the potential of a sector to stimulate production and investment of sectors that provide its inputs, whilst forward linkage relates to the capacity of a sector to induce productive activities of sectors which demand its output. Therefore, key sectors, i.e. sectors with strong linkages
would be capable of generating higher economies of scale with positive effects in terms of
productivity gains and cost savings in later stages of the production chain. As a matter of fact,
unbalanced growth theory asserts that certain sectors, particularly inside the manufacturing industries, are the main engines of growth16.
Like Albert Hirschman, Myrdal (1957) centralised his theory on the understanding that
economic development is intrinsically a process in disequilibria, breaking with the
neoclassical statement of “stable equilibrium”17. Thus, Myrdal’s theory of unbalanced growth is centred on the concept of “cumulative causation” to analyse the problem of development
inequality between nations. Thus, in this dynamic, trade and economic relations between
developed and underdeveloped countries are discussed considering effects that arise from this interaction and may negatively (“backwash effect”) or positively (“spread effect”) impact the development of an underdeveloped economy. Furthermore, according to him, economic development also involves not only economic relationships of supply and demand but also
institutional and political structures, denominated non-economic factors, which operating in a process of cumulative causation reveals challenges to be faced by underdeveloped countries18.
In the Myrdal’s concept of “circular cumulative causation”, the main idea relies on the
fact that free market forces would tend generally to increase regional disparities. The assertion made by Myrdal was important because, while international economic inequality grew and
became a common concern in many schools of thought, the neoclassical theory of
international trade insisted on the idea that there was a gradual equalisation tendency of factor Input-output models made possible measurements of linkages. In fact, during the 1960s and 1970s, different indicators of forward and backward linkages based on the Leontief inverse matrix were developed in order to fulfil the theoretical approach. 16 According to Ancochea (2007), the selectivity of some sectors as proposed by unbalanced growth economists received different names, such as the “propulsive industry” (Perroux, 1955), “leading sector” (Rostow, 1952, 1978), or the “development block” (Dahmen, 1987). For instance, see (Hirschman, 1987). 17 To Myrdal, neoclassical trade theories were “never developed to comprehend the reality of great and growing economic inequalities and of the dynamic processes of under-development and development” (Myrdal, 1957, p.51). 18 See also Ho (2004). 15
15
prices and income across countries. Even focused on social aspects of this cumulative
causation, Myrdal’s theory provided the fundamental framework for later complementary heterodox theories, such as the Latin American Structuralist approach – with a strong influence in Celso Furtado – and the Kaldorian theory which concentrated in the demandsupply relationships to the manufacturing sector.
As a general link between all pioneers of economic development, although wrapped in
a critical assessment of the level of state intervention in the economy, both approaches – “balanced growth theory” and “unbalanced growth theory” – directly or indirectly paid
attention to the role of the industrialisation process as a way to overcome underdevelopment.
In the context of Latin American development problems, it is important to highlight that
ECLAC participated actively in these discussions providing important contributions notably from the works of Raúl Prebisch, Celso Furtado and Aníbal Pinto. From this background, the
following section seeks to provide the main reflections on the obstacles encountered by underdeveloped countries in the face of the absence of a dynamic industrial structure.
1.2. Latin American Structuralism: Linking underdevelopment to the centreperiphery paradigm
In modern economics, Latin American structuralism should be placed in a
methodological tradition which has its origin in the Raul Prebisch’s (1949) study “El
desarrollo económico de la América Latina y algunos de sus principales problemas”. With Prebisch leading a group of outstanding economists, the Economic Commission for Latin
America and the Caribbean (ECLAC) sparked remarkable insights and explanations regarding
the causes of Latin American underdevelopment19. Latin American structuralist writers challenged the neoclassical theory through a critique of the prevailing international trade and proposed a theory of peripheral capitalism incorporating core elements presented in the
French20 and Anglo-Saxon structuralist traditions, as well as in Keynesian thinking21 (Furtado, 1967; Love, 1995, 1996; Sunkel, 1989, Palma, 1987, Blankenburg, Palma & Tregenna, 2008). 19
The French structuralism represented by innovative contributions of François Perroux (1939) defined structural economics as a science which analyses the relations characteristic of an economic system situated in time and space. According to him, economic analysis should incorporate institutions and structures over time. See Blankenburg, Palma & Tregenna (2008). 20 Perroux (1950) anticipated important elements of ECLAC’s theory, particularly with regards to the centreperiphery model, which was an extension of the concept of economic systems where “the economic world is
16
Based on this theoretical background, the basic analytical components of ECLAC and
other Latin American structuralists were grounded in historical methodology, the study of
domestic determinants of economic growth and technological progress, as well as an evaluation of arguments in favour and against state intervention (Bielschowsky, 1998). In this
sense, many prominent works followed ECLAC thinking and provided important insights, criticisms
and complementarities for the understanding of the Latin American
underdevelopment. Through a sharp critique of the neoclassical economics and its idea that specialisation based on comparative advantages, whatever its nature, was a superior solution
for economic growth, the Latin American Structuralist school gave life to an important interpretation where the productive structure matters to the pace and scope of the development
process. Comparing commodity-producers economies and industrialised countries, Prebisch (1949) noted that productivity was essentially higher in the manufacturing sector than in the primary activity. This dichotomy in levels of productivity between the productive structure of
developed (centre) and underdeveloped (periphery) countries, the so-called structural heterogeneity, was also approached by Furtado (1959, 1961) and Pinto22 (1965, 1970).
For Furtado (1961), the mainspring of the capitalist development is technological
progress through a process of incorporation and diffusion of new techniques with a consequent increase in the production and productivity23. Therefore, underdevelopment is
seen as a partial and blocked version of the development, either because of the uneven spread conceptualised in terms of hidden or explicit relationships of ‘force’, ‘power’ and ‘constraints’ between dominant and dominated entities” (Blankenburg, Palma & Tregenna, 2008, p. 2). Perroux’s theory is based on different analytical levels, i.e., markets, firms and international economy and clarifies interactions between different entities with distinctive structures of power and the consequences in terms of trade and finance. According to Perroux growth does not appear everywhere and all at once; “it appears in points or growth poles with variable intensities; it spreads along diverse channels and has varying terminal effects for the whole of the economy” (Perroux, 1955, p 308). Thus, the intensity and magnitude of growth poles are determined by the fundamental role played by propulsive industries, which are in turn highly innovative and, according to Perroux, sources of technological progress. These industries constitute the pillar of economic development and generate positive effects (spread effects) in other regions, such as the increase in income and employment and at the same time produce structural change through economic growth. Moreover, through the development pole theory, Perroux also exerted a fundamental influence on the ECLAC’s division of the world between centre and periphery and Furtado’s early work including his doctoral dissertation at Sorbonne. See Furtado (1995). 21 The Latin American structuralist school was also concerned, to a greater or lesser extent, with a coalition of the industrial bourgeoisie, the middle class and the urban working class, under the coordination of the developmental state to propel the economic development. According to the structuralist approach, it is the developmental state which is the main agent of change since it is the only institution capable of transcending sectional interests and thereby able to pursue the national interest (Kay, 1989). 22 Although the concept of structural heterogeneity was a central element in works of Raúl Prebisch or in Celso Furtado in the form of “dualism”, it was with Anibal Pinto that the concept of structural heterogeneity solidifies during the 1970s. See for instance Pinto (1970, 1971, 1976). 23 In a complementary approach, Tavares (1972, p. 50) highlights the problem to create technical progress endogenously and the consolidation of a diversified productive structure with increasing share of national content in domestic production.
17
of technical progress or the limited transmission of productivity gains to wages. According to
him, in developed countries, dynamic growth is headed by technical progress while in
underdeveloped countries it is determined primarily by external demand for imports. While the centre countries internalised the new technology by developing an industrial capital goods
sector and by spreading the improved technology to all economic sectors, the periphery remained dependent on imported technology which in turn was mainly confined to the
primary export sector. Consequently, a sizeable low-productivity pre-capitalist sector continued to survive in the periphery producing a continuous surplus of labour and
consequently keeping wages low. Without the processes of industrialisation, the asymmetry between the centre and periphery would not only perpetuate but also deepen.
In relation to this dynamic, Pinto (1965) highlighted the persistence of structural
heterogeneity. According to Pinto, developed countries had a much more homogeneous level of productivity than the periphery. The heterogeneity in underdeveloped countries – expressed in sectors where the productivity is high or “normal” with others where the productivity is
lower or several times lower in the same economic structure – would generate problems of underemployment in face of the occupational mismatch. As the occupational structure is a
mirror of the productive one, economies with high productivity tend to generate more employment while structures with very low productivity tend to generate underemployment (Rodriguez, 2006).
Pinto (1970) identifies three levels of productivity in Latin America: i) the primary
sector with low productivity and low earnings, keeping similarities with the prevailing forms of production since the colonial period; ii) the middle sector that is neither the upper end nor
the lower end and thus is near to the average of the economy as a whole; and iii) the modern sector with high productivity levels and gains, which are similar to the average of developed economies. Given these different levels of productivity, the rate of technical progress
incorporation and productivity increase would be significantly higher in central economies vis-à-vis peripheral economies, which in turn are specialised in primary products. In this way, a shift from less productive sectors to those with higher productivity – notably the
manufacturing industry – would promote an increase in the aggregate productivity, a stimulus in the technological diffusion and an increase in real wages24. 24
During the 1980s, Fernando Fajnzylber provided important contributions in relation to the underdevelopment theory emphasising the Latin American bottlenecks, especially regarding technical progress and productivity.
18
While various writers contributed to the Latin American structuralist paradigm,
Prebisch’s original ideas were pivotal in launching a critical perspective on the neoclassical
approach to the mutual profitability of free trade between developed and developing
countries, whose influence was very remarkable in Latin America. In his thinking, a key structural economic characteristic of peripheral economies refers to the deterioration in their terms of trade over time due different income-elasticity of demand – also known as “dynamic disparity of demand”. Thus, contrary to what the comparative advantage theory suggested, prices of primary products produced and exported by peripheral countries, such as in Latin
America, tended to present an antagonistic evolution when compared to prices of
manufactured products exported by industrialised countries. This means that the centre’s
imports of primary products from periphery rise at a lower rate than its national income, while the periphery’s imports of manufactured goods from the centre grow at a faster rate than its income. Since demand for manufactured goods increases more rapidly than the demand for
primary goods, the well-known Engel’s law, there is a tendency to deteriorate the terms of trade of those economies specialised in the production and export of primary goods in comparison to central industrialised economies.
In other words, prices of manufactured goods would be structurally higher in relation
to primary products. This meant that peripheral economies would have to export more to achieve the same value of industrial exports over time. In central economies adjustments along the global economic cycle are made through export quantities, due to the high level of industrialisation. On the other hand, in peripheral economies, adjustments occur through
export prices due to the primary specialisation25. In contrast to the free trade doctrine, these movements would be gradually accentuated in the absence of a dynamic industry. Thus,
Fajnzylber (1983) explained the low technological dynamism that characterised Latin American industrialisation through a convergence of structuralist thinking, the French regulation school and evolutionary economics. According to Fajnzylber, an economy which does not have an “endogenous nucleus of technological dynamism” cannot overcome underdevelopment. Moreover, since the sector of capital goods materially incorporates technological progress, policies to strengthen this sector should be carried out to establish an endogenous nucleus of technological dynamism and stimulate the diffusion of technology to other sectors as well as reverse the Latin American structural deficit in the current account. Without a strong developmental state to build this “endogenous nucleus of technological dynamism” as occurred in developed countries and in late industrialising countries (LICs) such as East Asia, including Japan, and in absence of an industrial vocation, i.e, business leadership capable of inducing transnational companies to build this “endogenous nucleus of technological dynamism”, underdevelopment would be maintained. According to Fajnzylber, in Latin America, the problem with transnational companies (TCs) was the establishment of productive structures based on technology transferred by headquarters which therefore did not contribute to the process of technological innovation. To clarify the understanding of how to overcome the inheritance of past mistakes, the author defends that Latin America should not only focus the macroeconomic stabilisation and debt reduction, but also push the technological frontier inducing TCs to adopt innovative domestic behaviour. 25 In a complementary way, see Prebisch (1950, 1959) and Singer (1950).
19
overcoming underdevelopment would not be possible through the international division of
labour, in which peripheral countries would be doomed to a specialisation in primary products. In this sense, industrialisation was seen as a way to modify this process. Thus,
through a productivity increase, the deterioration of the terms of trade could be reduced, the technological progress incorporated and a process of income distribution promoted26.
The limits of spontaneous industrialisation in developing countries clearly revealed the
need for an active state intervention in the industrialisation process. Although the state should
have the capacity to promote particular sectors through the creation of public companies, it should especially focus on planning (Ancochea, 2007). For this purpose, many other Latin
American “structuralists” sought to map different stages of the industrialisation process in a
similar manner, often distinguishing between the so-called stages of industrialisation, i.e. internalising the production of consumer goods, consumer durables, intermediary inputs and capital goods. Therefore, it is not by chance that during 1950s and 1960s this argument gave rise to the support of import substitution industrialisation (ISI) model, principally in Latin
America. ISI was a trade and economic policy programme based on the premise that a country
should attempt to reduce its foreign dependency through the local production of manufacturing goods. For this purpose, the developmental state would coordinate the process
of industrialisation from light to heavy industries through imports of intermediary and capital goods necessary to obtain a diversified and interdependent productive structure. In each stage
of the industrialisation process, a gradual replacement of imported goods for domestic production would spread technological and productivity gains over the economy.
Broadly speaking, the idea expressed by the Latin American Structuralism was that,
despite the spread of modernity, backwardness and wide differences in labour productivity between economic sectors and subsectors, and between regions and segments of the
population, tended to be maintained and sometimes expanded (Bielschowsky, 2009). According to these authors developing countries could be characterised by a dual structure
where a late agricultural sector and a modern industrial sector would coexist. The
manufacturing importance vis-à-vis a concentration in primary commodity exports was a central concern of the structuralist approach associated with the ECLAC. In this way, industrialisation is seen as the only way for developing countries to catch up. As a general 26
These dynamics were also pointed out also by Furtado (1959). In this sense, Furtado’s works are closely connected to Prebisch’s, especially regarding endogenous dimensions of underdevelopment and its determinants. In general, the economic thinking of ECLAC and Celso Furtado addressed particularly the different stages of industrialisation in a similar manner, often distinguishing between the so-called phases of industrialisation.
20
trend, these aspects would be a central issue in the Latin American structuralist strand. The
Kaldorian theory which concentrated on the demand-supply relationships in the manufacturing sector complements this view giving further elements to explore the importance of the industrialisation process, more specifically the manufacturing sector. 2. Kaldor’s stylised facts and the contemporaneous debate Kaldor showed the central role that manufacturing sector plays in economic growth in
two lectures: one in Cambridge in 1966 entitled Causes of the Slow Rate of Growth of the
United Kingdom (Kaldor, 1966); the other at Cornell University in the same year, published as Strategic Factors in Economic Development (Kaldor, 1967). Inspired by studies of Allyn
Young, Gunnar Myrdal and Adam Smith and recovering the empirical regularities pointed out
by Kuznets, Rostow, Chenery and Syrquin, Nicholas Kaldor argued that it is not possible to understand the development process and growth rate differences between countries without taking a sectoral approach. In a complementary line of research to Furtado, Hirschman,
Rosenstein-Rodan and Prebisch, Kaldor noted that the manufacturing sector was imbued with
special growth-enhancing properties that triggers a process of cumulative causation that are not shared by other sectors27.
Kaldor’s view offered support for the special role played by the manufacturing sector
given some special characteristics which forwarded itself to a special theoretical framework
for understanding the causal relationships between industrial development and economic
growth. Kaldor introduced the concept of dynamic economies of scale, such that the faster the
growth of manufacturing output, the faster the growth of manufacturing productivity. He
attributed these dynamic economies to Arrow’s (1962) notion of ‘learning by doing’ and argued that this occurred principally in manufacturing and not in services or agriculture. In
this way, challenging the neoclassical statement of constant returns to scale across sectors, Kaldor noted that poor developing countries tend to specialise in land-based sectors –
In this case, Kaldor’s explanation is highly influenced by studies of Allyn Young, Gunnar Myrdal and Adam Smith. In his own words, “to explain why certain regions have become highly industrialised, while others have not we must introduce quite different kinds of considerations – what Myrdal (1957) called the principle of ‘circular cumulative causation’. This is nothing but the existence of increasing returns to scale – using the term in the broadest sense – in processing activities. (…) As Allyn Young (1928) pointed out in a famous paper, Adam Smith’s principle of ‘division of labour’ operates through the constant sub-division of industries, the emergence of new kinds of specialised firms, of steadily increasing differentiation – more than through the expansion in the size of the individual plant or the individual firm” (Kaldor, 1970, p. 340). All these assumptions stimulated many studies which tried to provide a formalisation of Kaldor’s ideas of economic growth. In a wellknown work, Dixon & Thirlwall (1975) provided a systematic formalisation of the cumulative causation model. Appendix 1.1 addresses this issue. 27
21
agriculture and mining – subject to diminishing returns, while richer developed countries specialise in increasing returns activities (static and dynamics) such as manufacturing and sophisticated service activities associated with them including banking, finance and insurance (Thirlwall, 2013).
Unlike the neoclassical theory of growth, i.e. theories of exogenous and endogenous
growth developed since Solow (1950), where the theoretical framework relies exclusively on
the supply-side vision, Kaldor’s argument considers the demand side28, particularly the role of aggregate demand, to explain the economic dynamic. On the basis of the interaction involving demand and supply conditions in agriculture, manufacturing and services, Kaldor derived generalisations concerning the relationship between the growth of output, employment and
productivity in different sectors of the economy. These theoretical formulations became known as “Kaldor‟s growth laws” or “stylised facts” and became an important turning point in the literature of economic growth.
Many empirical tests centred on Kaldor’s laws to explain the differences in
international growth rates were made and replicated for different groups of countries and periods of time since then, following the evolution of econometric methods for static- and
dynamic-model data panels. Under this framework, many contemporaneous and prominent Kaldorian analyses emphasised a strong relationship between changes in the sectoral composition of an economy and economic growth. In a complementary way, the
contemporary developmental literature has emphasised the bundle of interactions that connects manufacturing and economic growth, particularly considering distinct stages of development and the intersectoral relationship between services and manufacturing. 2.1. Manufacturing as engine of growth: from industrialisation to deindustrialisation Over the years, the complex relationship between production structure and economic
growth has been the subject of considerable debate among economists. The ever-increasing body of policy reports, academic papers and manufacturing national strategies covering
economies with different income levels have showed the virtues of manufacturing. The so-
called stylised facts are supported by important empirical regularities that recent research on 28
Different from the neoclassical view, in the Kaldorian framework the production used in a modern capitalist economy is itself goods produced within the system given the effective demand.
22
patterns of economic growth has highlighted29. In this sense, recovering the stylised facts formulated by Kaldor, the first law states that “manufacturing is the engine of growth”. It means that the faster the growth rate in manufacturing output is, the faster the growth rate of the economy as a whole will be.
In dialogue with this hypothesis, using different econometric methods such as cross-
section, panel and time-series data analysis (for some individual countries), many empirical studies were strongly supportive of Kaldor’s first law (Thirlwall, 2013). Kaldorian analyses
showed that regression coefficients were statistically significant at the 95 per cent confidence level and above, and are strong in the case of East Asian and Latin American economies
(Hansen and Zhang, 1996; Mamgain, 1999; Libanio, 2006; Wells & Thirlwall, 2003;
Dasgupta & Singh, 2006). Unlike manufacturing, in agriculture and services the relation
between GDP growth and the growth of other sectors does not exist, at least not in the same magnitude. In fact, studies did not find a correlation between the growth of agriculture and the
growth of GDP in a causal sense. Furthermore, econometric tests have showed a strong negative correlation between GDP growth and the excess of agricultural growth over non-
agricultural growth. Additionally, the coefficient for services was lower than those of manufacturing (Thirlwall, 2013).
Other empirical studies have been supportive of the Kaldorian literature. Rodrik
(2007) found that since 1960 the economic growth of developing countries economic is
strongly associated with the development of modern industrial sectors. Szirmai & Verspagen (2011) and Szirmai (2012), taking into account a sample of 21 advanced economies and 67
developing countries in the past 50 years, found that manufacturing has functioned as an important engine of growth in developing countries. These analyses have been in dialogue with Fagerberg & Verspagen’s (1999) work which noted that developing countries are those
that benefit more from expansions of the manufacturing sector. They test the importance of the most dynamic segments of manufacturing in economic growth and confirm the importance of the flexibility to shift towards manufacturing productions.
The following Figure (1.1) illustrates a positive correlation between the rate of GDP
growth and the increase in manufacturing’s share in the global manufacturing GDP. Those
countries that achieved the fastest economic growth during the period are the countries where 29
Kaldor developed this stylised fact through a study of developed countries over the period 1952-54 to 1963-64 (Kaldor, 1966).
23
the increase shift towards manufacturing has been most intensive. The numbers bellow illustrates the dichotomy between Asia and Latin America in terms of strategy of economic
development. In Asia, the share of manufacturing in GDP grew at much higher rates resulting in significant increases in the GDP. In an opposite trend, Latin America and developed
countries showed exactly the reverse path, de-industrialising and achieving very modest rates of GDP per capita growth.
Figure 1.1 – Annual GDP growth and change in the share of manufacturing value added in the global manufacturing GDP, 1970-2010
Change in the share of manufacturing value added in the global manufacturing GDP
9% Korea
7% 5%
Nics 2
3%
India
1%
Mexico Brazil Latin America Japan Chile Argentina US Developed economies
-1% -3%
Nics 1 Singapore South-Eastern Asia China Taiwan
0%
1%
2%
3%
4%
5%
Annual GDP growth
6%
Hong Kong 7%
8%
9%
Source: Own calculations based on data from GGDC 10-Sector Database and UNCTAD. Note: GDP = Gross Domestic Product. According to UNCTAD database, developed countries include Australia, Austria, Belgium, Canada, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hong Kong, Iceland, Ireland, Israel, Italy, Japan, Luxembourg, Malta, Netherlands, New Zealand, Norway, Portugal, San Marino, Singapore, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, United States. Nics 1: Korea, Taiwan, Hong Kong, and Singapore. Nics 2: Malaysia, Thailand, Indonesia, and the Philippines. South-Eastern Asia: Brunei Darussalan, Cambodia, Indonesia, Lao, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste, Vietnam. R2 = 74%; all variables are significant at the 5% level.
Nevertheless, Szirmai & Verspagen (2011), Fagerberg & Verspagen (1999) and
Szirmai (2012) have noted that even though manufacturing plays a central role in the process
of economic development, some countries have presented a decreasing share of
manufacturing followed by an increasing share of services in their sectoral composition. With the intention of evaluating this trend, an important issue related to the stage of development should be considered. As Rowthorn & Wells (1987) noted in a seminal study, countries
24
follow a broadly similar trajectory of economic development. Thus, as development gets
under way, in low-income countries, the share of agriculture in the value added and employment fall and there is a rapid increase in the share of manufacturing. The transition
from a reasonable diversified structure of production to a mature economy is known as
‘industrialisation’ and mostly represented by the so-called middle-income countries. At a certain point, when the economy reaches a certain level of income per capita, the share of
manufacturing stabilises and then starts to fall back taking the form of an ‘inverted-U’
(Rowthorn, 1994) 30. This trend is also followed by a corresponding increase in the share of services in national employment31 and value-added, and is often described as natural process of de-industrialisation32.
Manufacturing Share (%)
Figure 1.2 – The ‘inverted-U’ relationship between manufacturing and income per capita 50 45 40 35 30 25 20 15 10 5 0
Middle Income
Low Income
0
High Income
5,000
10,000
15,000
20,000
25,000
30,000
GDP per capita (Geary-Khamis dollars - 1990)
Source: Mckinsey (2012).
30
Rowthorn & Wells (1987) defined de-industrialisation as a decline in manufacturing employment first in relative terms and then, at least in some countries, also in absolute terms. Tregenna (2009) defined the deindustrialisation as the consistent reduction of both the share of employment and the value added of manufacturing industry in total employment and GDP, respectively. In this section “de-industrialisation” will be analysed solely from the point of view of manufacturing value added. 31 In terms of employment, the statistics also indicate that in most countries the growth rate of labour productivity in the manufacturing sector has been faster than in services and in the economy as a whole. Consequently, the relative decline of manufacturing employment has been mainly the result of rapid productivity growth in this sector (Rowthorn & Coutts, 2013b). See also Rowthorn & Coutts (2013a, 2013c). 32 The “inverted U” curve also reflects the consumption pattern in each stage of the income per capita. During early stages of the economic development, i.e. low-income countries, agriculture presents the biggest share in the economy because food represents most of the household consumption. Thus, as countries go through the economic development inputs such as steel and cement are needed for infrastructure as well as machinery and transportation equipment for the productive process of industries. When the country reaches the stage of middleincome economy, a higher income per capita triggers additional forms of consumption, particularly in services. An increase in spending on services such as education, health care, travel, banking and many others begins to take up gradually a higher share of incremental income.
25
Many authors such as Robert Rowthorn have done seminal studies to understand this
natural shift in terms of sectoral composition, contrasting the so-called natural de-
industrialisation, i.e. the natural consequence of the industrial dynamism in an already developed economy, with the so-called negative de-industrialisation, which is defined as “a product of economic failure and occurs when industry is in severe difficulties and the general
performance of the economy is poor” (Rowthorn & Wells, 1987, p.9). Through this line of thinking, Rowthorn & Coutts (2004), Palma (2005), and Pieper (2003) stated that several
developing countries are de-industrialising at a much lower level of per capita income than observed historically in today’s developed countries.
In order to consider if the rise of
services is a symptom of economic failure and a harbinger of impending impoverishment or if the decline of manufacturing might be seen as something natural or even as a sign of development, some considerations must be taken into account. 2.2.Statistical illusions
Firstly, a non-negligible part of the extent of de-industrialisation – decreasing relative
importance of manufacturing – seems to be due statistical illusions, in the sense that it reflects changes in statistical classification rather than changes in real activities. Therefore, the extent of deindustrialisation has been overestimated due to the outsourcing of some services that
used to be provided in-house by manufacturing firms and thus were counted as manufacturing output, e.g. catering and cleaning, research, design, IT, accounting, telecommunications, engineering activities, logistics and legal services (Palma, 2005, Rowthorn & Coutts, 2004)33.
Although these outsourced activities are still the same, now they are counted as part of
services output, rather than manufacturing output. Consequently, services become more important without a real increase. In this manner, experts agree the outsourcing effect has
been a considerable source of de-industrialisation in middle/high-income countries principally from 1980s when the neoliberal policies took momentum. This potential overestimation of
manufacturing’s decline in industrialised countries is also discussed by McCarthy & Anagnostou (2004) and Vittucci (2008). Another handful of theorists such as Laplane & Sarti
(1997), Carneiro (2008) and Rocha (2011) have highlighted that this statistical effect also
affected Latin American countries. These studies noted that neoliberal policies, particularly regarding market deregulation and trade liberalisation, led a wide range of manufacturing 33
Rowthorn & Coutts (2004) named it as “statistical artefact”.
26
sectors to undertake defensive adjustments characterised by the process of outsourcing which
shifted value added from manufacturing to services, contributing to statistical illusions outlined above34.
2.3.Servicification Secondly, although the explanation for the premature de-industrialisation outlined
above obscure the traditional distinction between services and manufacturing, empirical studies have shown that middle income countries – characterised by a premature deindustrialisation – and high-income countries tends to present strong correlation between GDP
growth and the increasing share of services, particularly more sophisticated and high-valueadded service activities, which in turn has shown a strong dependence on manufacturing.
Although economists have also observed the difficulty of measuring interactions between services and manufacturing, due to the process of outsourcing, input-output analyses revealed
strong intersectoral interactions and interdepencies between these two sectors35 (Lodefalk, 2010; Nordås & Kim, 2013).
Pilat & Wolfl (2005) quantified the interaction between manufacturing and services in
the economy. This analysis has showed that the character of European manufacturing seems to change over the years interacting more with service industries than before, that is,
manufacturing has been using more intermediate services and employs a rising number service-related workers. This trend has been not only a result of outsourcing that
overestimates the use of services in manufacturing, but also the increasing interdependence
between some knowledge-intensive services and manufactured products. In the case of the latter, the most remarkable example is the service subsector of Information and Additionally, as pointed out by Chang (2014, p. 261), “seeing the share of manufacturing in their output falling, some manufacturing firms have applied to be reclassified as service firms”. In this sense, individual manufacturing firms have been reclassified as service firms, even though they still engage in some manufacturing production. According to the UK government’s Department for Business, Enterprise and Regulatory Reform (BERR) up to 10% of the fall in manufacturing employment between 1998 and 2006 in the UK may have been due to this reclassification effect (Chang, 2012). 35 As showed by Mckinsey (2012, p. 7), depending on the segment, 30 to 55 percent of manufacturing jobs in advanced economies are service-type functions, and service inputs make up 20 to 25 percent of manufacturing output. Moreover, for every dollar of output, US manufacturers use 19 cents of service inputs, creating $900 billion a year in demand of services, while services create $ 1.4 trillion in US manufacturing demand. In China this interdependence is around $500 billion in services demand and $600 billion in manufacturing demand. Additionally, although manufacturing exports drives more than 80 percent of German exports, services and manufacturing contribute nearly equal shares of value added to the country’s total exports. 34
27
Communications Technology (ICT). However, although services now contribute more as providers of intermediate input and service related workers to the performance of other industries, their role remains more limited than those of the manufacturing sector. Park &
Chan (1989), Rocha et al. (2014) and Magacho et al. (2014) have confirmed Hirschman’s intuition that manufacturing has larger multiplier indices than other sectors.
As suggested by Guerrieri & Meliciani (2005), the country’s capacity to develop its
services depends on the specific structural and technological composition of its manufacturing sector. Some knowledge-intensive services are spin-offs from manufacturing production,
given that the manufacturing sector itself has been the key source of new productive
knowledge to the rest of the economy. Moreover, the manufacturing sector creates demand for the growth of high-productivity services such as finance, engineering, design, accounting,
consultancy, telecommunication and transport. Therefore, services growth is closely connected to the manufacturing sector and consequently a weakening manufacturing base would eventually lead to a decline in the quality of those services (Chang, 2014). 2.4.Productive Fragmentation Last but not the least, in recent decades, the geography of industrial production has
gone through a revolution, with the breaking-down of the ‘value chain’ by multiproduct Transnational Corporations (TNCs), leading to the process of de-industrialisation in advanced economies. Since around the year 2000, the relocation of labour-intensive assembly-end part
of the value chain to developing countries has significantly fragmented the international production in coordinated networks also known as global value chains (GVC) (Unctad, 2013).
In this new productive environment countries not only specialise in terms of industries but also of activities carried out for production of a particular product. Therefore, the value of a final product sold on the market embodies more and more value added from other countries due an increasing process of international vertical specialization (Stehrer, 2013).
In the background to this process, the dominant view stresses that international
productive fragmentation is an important source of firm efficiency through improvements in competitiveness both in domestic and international markets and by cost savings. Through this productive fragmentation, companies could focus on the most dynamic levels of the global
value chain such as R&D, product design, marketing and services. Furthermore, companies 28
responsible for tangible activities would also benefit from the learning flow with global buyers that would improve their production process and product upgrading. Moreover,
countries specialised in production activities could also move to levels with higher value
added in the global value chain. Therefore, the stage of economic development would be closed related to the process of acquiring new functions which generate higher incomes (and, conversely, ceasing to perform low-income activities). At the country level, the process of
productive re-allocation to low and middle income nations would give to companies more
access to new consumer markets. In this process, low-income countries could also experience rapid economic growth processes stemming from the structural transformation of the large-
scale migration of workers from subsistence sector to manufacturing. Middle-income countries in turn could consolidate their productive structure and, in the course of economic development, move up in the global value chain.
Figure 1.3 –Value added in the Global Value Chain
Source: Elaborated by the author based on OECD/WTO (2013)
However, many studies have stressed that the process of embracing the global value
chain has generated doubtful results. Thus, the decline of manufacturing in advanced
countries like the US and EU members as well as in Latin American economies due the process of productive fragmentation nowadays concerns policy-makers and scholars particularly with regards to the risks of losing the interdependence between production
activities and technological innovation. The proponents of the manufacturing renaissance 29
have been warning that a knowledge economy which loses interaction with its productive structure may lose the capacity to innovate next-generation technologies and products.
Therefore, prominent scholars have pointed out the fact that the off-shoring of
production operations is all too often followed by a deterioration of the so-called “industrial commons”36, i.e. damage to other parts of the industrial system which includes “reduced operations by local suppliers of materials, components and production technologies; a decline
in process engineering skills, manufacturing know-how and leadership; a deterioration of
prototyping, test-bed and pilot-manufacturing infrastructure” (O’Sullivan & Mitchell, 2013, p. 43). In this way, losing “industrial commons” may cause a decline in important technological
capabilities that stems from the interconnection between product development, nextgeneration production technologies and process engineering. Consequently, due to the fact
that cutting-edge technologies often rely on elements of the “industrial commons” underpinned by dynamic manufacturing sectors, this process risks reducing the country’s capacity to compete in some of the most important new industries.
Pisano & Shih (2009) exemplified this point illustrating that US companies
overestimated the advantages of outsourcing development and manufacturing work to specialists abroad and cutting their spending on basic research. Moreover, the outsourcing and
off-shoring slogan comprised not only low-value tasks like simple assembly or circuit-board
stuffing, but also sophisticated engineering and manufacturing capabilities that support innovation in a wide range of products and process. Therefore, due to the process of losing knowledge, skilled people, and supplier infrastructure, the US reduced its capacity to manufacture a vast range of cutting-edge products.
According to Ezzel & Atkinson (2011), the current challenges faced by some
industries in the US illustrate this point well. In the case of the solar panel industry, they found that in order to lower costs, US companies re-allocated semiconductor foundries to Asian countries such as Japan, India, Taiwan, South Korea, and especially China. However, it
not only deteriorated the silicon-processing and thin-film-deposition capabilities in the US but also undermined the process of manufacturing solar panels. In the same way, US companies
are falling behind in the software industry. Initially, companies outsourced only relatively Pisano & Shih (2009) coined the term ‘industrial commons’ based on the Marshall study (1920). Moreover, based on the seminal Marshall study on industrial districts, Kaldor also pointed out that one of the most remarkable features of industrial districts is the special concentration of manufacturing activity that culminates in important advantages for industries as a whole due to the availability of specialised skills and ready communication of trade and managerial know-how (Kaldor, 1970, 1972). 36
30
mundane code-writing projects to Indian firms to lower software-development costs. However, over the years, Indian companies developed their own software-engineering
capabilities and started to attract more complex activities to India like developing architectural specifications and writing sophisticated firmware and device drivers (Pisano & Shih, 2009). The consequence of these trends is the slump of the US industrial base, “the
hollowing out of advanced production supply chains, and the loss, for many US industries, of their industrial commons” (Ezzel & Atkinson, 2011, p. 15).
Furthermore, the critics of productive fragmentation have widely documented that
production and R&D cannot be disassociated because the proximity of research, development, and manufacturing is very important to leading-edge manufacturers. As stated by Berger (2011), there is a close connection between R&D and manufacturing. In this interdependence,
for example, strategies for making processes more efficient stem from the close synergy involving R&D engineers and manufacturing. Therefore, off-shoring manufacturing is pulling high-end design and R&D capabilities out of the US and consequently diminishing the
country’s capacity to create new high-tech products. For this reason, Ezzel & Atkinson (2011)
highlight that nowadays 90 percent of all electronics R&D now takes place in Asia due to
some extent to the scale of production needed to be able to afford general R&D. They also point out that from 1998 to 2007, US corporations invested more than 2.65 times faster in
overseas R&D than domestically. Furthermore, almost “every US brand of notebook
computer, except Apple, is now designed in Asia, and the same is true for most cell phones
and many other handheld electronic devices” (Pisano & Shih, 2009). Thus, these examples show that R&D, design and manufacturing cannot be disassociated.
For this reason, especially after the outbreak of the global crisis in advanced countries,
particularly the US but also in European economies, turned attention particularly to the need
of re-strengthening the manufacturing base together with the objective to ‘bring manufacturing back home’, which was lost during the productive fragmentation era that
stimulated outsourcing and off-shoring practices. The European Commission has set an
ambitious goal aiming for a manufacturing share of 20% in 2020 (which is now around 15%)
and there is an active debate in the US today about the need of re-industrialisation to guarantee further economic growth and high-quality job creation (Stehrer, 2013)37.
37
See European Commission (2010).
31
3. Manufacturing as the main source of productivity growth Through a sharp critique of the neoclassical theory, Kaldor postulated with regards to
productivity growth in the manufacturing sector. The origin of Kaldor’s second law is an observation made by Verdoorn in 1949 that there is a positive relationship between the rate of
growth of output in manufacturing and the rate of growth of labour productivity in
manufacturing. Influenced by Young (1928), Kaldor noted that increasing returns to scale are
pervasive to manufacturing activities. In other words, according to Kaldor, the rate of
productivity growth in the manufacturing sector depends on its rate of output growth due to
the operation, within this sector, of static and, above all, dynamic returns to scale38 which are
also a source of technological progress (Kaldor, 1981). Static returns are mainly related to economies of scale internal to the firm, where the large scale of production allows a reduction on the average cost. Dynamic returns refer to the induced effect that output growth has on capital accumulation through increased productivity derived from learning–by-doing, technological change, external economies in production, and so forth (Libanio, 2006).
In this way, by highlighting the relevance of the sectoral composition to economic
growth, it is possible to verify that primary production and services do not possess the same
properties as the manufacturing sector. It means that the first one tends to present lower returns to scale while in the second one, the scale of production tends to keep constant returns.
It happens because the returns tend to be higher when the production scale is greater, as in the manufacturing sector. Therefore, there are several studies that tested the Kaldor-Verdoom law over many different time periods and across variety of countries and industries. The causal relation between the growth of manufacturing output and labour productivity growth in
manufacturing as a result of static and dynamic returns to scale has been tested for developed
countries, such as United Kingdom (Hildreth, 1989; Harris & Lau, 1998), the US (McCombie & De Ridder, 1983; Bernat, 1996), Japan (Knell, 2004), the European Community (Fingleton & McCombie, 1998; Angeriz, McCombie & Roberts, 2009) and developing economies,
particularly for Asia (Timmer & Szirmai, 2000) and Latin America (Libanio, 2006). The results indicate substantial returns to scale, especially dynamic increasing returns, in
38
In his seminal study, Verdoorn (1949) demonstrated the existence of increasing returns both across industries within one country and in total industry across countries. Verdoorn was a member of the Research and Planning Division of the Economic Commission for Europe in Geneva, directed by Kaldor between 1947 and 1949, but did not receive widespread recognition until 1966, when Nicholas Kaldor explicitly referred to it and coined the term Verdoorn’s Law in his Cambridge Inaugural Lecture (Kaldor, 1966).
32
manufacturing industry. When the same tests are fitted to other activities, there is no evidence of increasing returns in agriculture and services, especially in developing economies.
Another important stylised fact is Kaldor’s third law, which holds that the faster the
growth of manufacturing output, the greater the rate of labour transference from other sectors
of the economy (where productivity is lower) to manufacturing industries (where productivity is higher). Thus, overall productivity growth is positively related to manufacturing output
growth and negatively related to employment in non-manufacturing sectors. Moreover, the manufacturing sector increases the productivity of the system as a whole because it withdraws
labour from the agricultural sector where there is a lower marginal product. Therefore, when
the surplus of labour becomes exhausted in the agriculture sector, and levels of productivity tend to equalise across sectors, the degree of overall productivity growth induced by manufacturing output growth is likely to slow down39. In this sense, Kaldor stresses that this
process is characteristic of economies in transition from “immaturity” to “maturity”, where an “immature” economy is defined by a large amount of labour available to be transferred to
industry (Thirwall, 2013). This is why growth rates tend to be fastest in the initial stage of development, and decelerate as economies mature and become more service-oriented.
Additionally, over the years many empirical studies have tested Kaldor’s third law.
Even in face of the difficulty of measuring labour productivity growth in the nonmanufacturing sectors, particularly service type activities and public goods – such as
education and health – results obtained by Hansen & Zhang (1996) for 28 regions of China, Wells & Thirwall (2003) for Africa showed that there is a strong negative relation between
employment growth in non-manufacturing sectors and overall productivity growth. Moreover, emphasising the crucial role of the manufacturing sector in economic growth, Kaldor states
that industrialisation through manufactured goods endows special elements which trigger spillovers not only in the same sector, but also in primary production and services i.e.
intersectoral spillovers. As indicated by Szirmai (2012) and Tregenna (2007), the manufacturing sector is one of the primary sources of technological advance in the economy.
It is inside manufacturing industries that most product and process technologies are
developed. Important spillover effects in modern economies arise from manufacturing and spread to other sectors, such as the service sector. Therefore, for instance, advances in IC 39
However, as noted by Thirlwall (2013, p. 51) , “manufacturing output growth is never likely to be constrained by a generalised shortage of labour, because labour is a very elastic factor of production in terms of hours worked, participation rates of males and females, and the possibility of international migration”.
33
hardware technologies produced in the manufacturing sector (silicon chips, glass fibre cables) fuel technological change in the software producing and software using service sectors (Szirmai, 2012).
Complementary views on the role of productivity increase in the manufacturing sector
for macroeconomic growth were further presented by Cornwall (1976, 1977), recovering
Kaldor’s ideas of manufacturing as a leading sector. In this sense, John Cornwall clearly refers to manufacturing as a driving force for productivity improvement in a whole range of
sectors, through technological interdependence as well as input-output linkages between
sectors (Verspagen, 2000). Both Kaldor and Cornwall state in their perspectives that the manufacturing sector embodies such special properties of a prime sector leading to economic
growth. Moreover, this link between manufacturing and technological change, as stressed by Cornwall, rests on Neo-Schumpeterian literature which draws attention to the crucial role
played by investment in technology to the catching-up of underdeveloped countries. In this way, Cornwall (1977), Fagerberg & Verspagen (1999) and Szirmai (2012) have emphasised
the limitations of a development strategy based on the production and trade of low valueadded products.
4. Manufacturing really does matter for the equilibrium in the balance of payments In contrast to the neoclassical model of international trade, free trade does not generate
income increase and factor price equalisation among countries. As noticed by Prebisch in the 1950s, the neoclassical literature regarding balance of payments did not recognise that an
imbalance between the income elasticities of demand for imports and exports would be a
central explanation for the substantial constraint on economic growth for developing
countries. In dialogue with the work of Prebisch, Kaldor attached great importance to the export performance, thus reinforcing the link which would be developed in the literature on growth constraints imposed by the balance of payments (McCombie & Thirlwall, 1994).
Following the stylised facts proposed by Kaldor, the fourth law deduced from
Harrod’s foreign trade multiplier40 shed light on economic growth led by demand and its limitations by the balance of payments equilibrium. Known also as Thirlwall’s law, due to Thirlwall’s (1979) pioneering work, it places emphasis on balance of payments constraints on According to Harrod (1933), the production of a country is determined by the external demand for its goods and tends to be a multiple of such demand that is represented by the reciprocal proportion of domestic income spent on imports. 40
34
growth, where the country’s long-term growth rate is approximately given by the ratio
between the rate of growth of exports and the income elasticity of demand for imports. In other words, the sustainability of growth depends on the country’s ability to maintain the
competitiveness of its exports, which in turn depends on the capacity of the manufacturing sector to increase productivity.
However, in spite of the recognition that manufacturing is the leading sector in
economic growth, its relevance in the basic model of balance of payments was overshadowed since all exports and imports are aggregated together in the standard model, i.e. income elasticities of demand for exports and imports, which ‘drive’ the model, are aggregate
elasticities. For this reason, Araujo & Lima (2007) integrating Pasinetti’s structural economic
dynamics (SED) to the balance of payments-constrained growth model created a multisectoral version of Thirlwall’s Law, in which changes in the productive structure affects the
overall economic growth rate41. Moreover, this model shows that each country’s growth rate is directly proportional to the rate of exports growth in a sectoral perspective. Therefore, this
proportionality is related inversely to the sector income-elasticity of demand for imports and directly to the sector income-elasticity. As stressed by the authors, even if the sectoral
elasticities and the growth rate of world income are constant, it is still possible for a country to raise its long-term growth rate by favourably changing the sectoral composition of its trade.
Following the multi-sectoral approach, recently a number of studies have been
exploring the connection between the sectoral composition of each country’s trade and the differences in income elasticities of demand across sectors. Gouvêa & Lima (2010) dividing primary products from manufacturing products and taking into account the technological
subdivisions of manufacturing tested this multi-sectoral model for four Latin American countries (Argentina, Brazil, Colombia and Mexico) and four Asian countries (South Korea, Malaysia, Philippines and Singapore) over the 1962–2006 period. The authors used the
sectoral elasticities to estimate year-by-year the evolution of the aggregate income elasticities of exports and imports. The results showed that unlike Latin American countries (except Mexico), Asian countries have successfully changed their composition of exports and imports
to technology-intensive manufacturing sectors in a way that led their weighted income
Although Pasinetti’s (1981, 1993) structural economic dynamics (SED) recognises explicitly the role of demand- led structural change in economic growth; in his model there is no explicit balance of payments constraint on demand. 41
35
elasticity of exports to grow faster than their weighted income elasticity of imports and consequently impacted positively on the balance of payments equilibrium.
Complementarily, Gouvêa & Lima (2013), in another disaggregated study, have
estimated sectoral export and import functions in a panel of 90 countries over the period
1965-1999. Similar to the previous study, their findings showed that technology-intensive
manufacturing sectors have a higher income elasticity of demand for exports. Additionally, as
noted by Cimoli et al. (2010) in a study involving 29 developed and developing countries, the inequality between nations was reduced in countries which sought to transform their economic structure towards sectors with a higher income elasticity of demand for exports
relative to imports. These sectors would encompass both, as they call, ‘higher Schumpeterian and Keynesian efficiency’, i.e. respectively products with a superior demand properties and
technical characteristics. Based on these considerations, the next section draws attention to this dynamic, more specifically, to the role of technological progress in the economic development.
5. Technological dynamics, innovations and economic growth According to Schumpeter and his intellectual heirs (sometimes called the neo-
Schumpeterian school), the capitalist system is characterised by cyclical dynamics generated by successive waves of innovations penetrating markets. His ideas, particularly with regards
to innovation, technical progress or structural change, became a contemporary subject in
economic policy and scientific debate and influenced not only a vast amount of economic literature in mainstream economics, but also the heterodox strand. A remarkable wave of
Schumpeterian studies based on Nelson & Winter’s (1982) groundbreaking research arose to
qualify the crucial role of technology in economic growth. Building on the work of Joseph Schumpeter (1912, 1942), they argue for an evolutionary theory of production (and economic change), which delved inside the “black box” of the production function in order to
understand how innovation occurs and affects competition and economic growth (Mazzucato, 2013). In this approach there is no vague production function as in the so-called new growth theory (including the early early neo-Schumpeterian models – such as in Aghion & Howitt
(1998) and Grossman & Helpman (1991), since the process of production and competition
36
involves a complex process of differentiation among firms based on their different abilities to innovate42.
The evolutionary and Schumpeterian approach to study the complexity of innovation
has led to a policy view where the so-called national innovation systems (NIS) of a country,
as firstly defined by Freeman (1982a, 1982b), are constituted by the institutional environment where firms of different type are embedded in as system at sectoral, regional and national levels (Mazzucato, 2013). Over the years the NIS has been used as an analytical framework
for policy analysis in both developed and underdeveloped countries. As a result, research and
policy activities clearly focusing on systems of innovation can be found in most countries and a rapidly growing number of studies of specific national systems of innovation, encompassing sectoral systems of innovation, have been produced (Cassiolato & Lastres, 2008).
Many studies have provided different explanations of the concept of NIS. However,
the main definition states that NIS is shaped by collective and individual contributions of different agents to the development and spread of new technologies. It congregates a sequence
of elements and relations that relate production, assimilation, use and diffusion of knowledge
(Lundvall, 1992). The emphasis is not on the stock of R&D, but on the circulation of knowledge and its diffusion throughout the economy. In a micro and meso perspective, a
structured NIS provides an institutional environment to promote technological progress and structural change.
5.1.The catching-up hypothesis: From imitation to innovation Over the years important contributions have been made, linking the Schumpeterian
framework and policies for catching-up in an economic development perspective. Remarkable
studies such as Fagerberg (1988a, 1988b), Perez & Soete, (1988), Dosi et al. (1990), 42
This dynamic also reveals a central feature of the Schumpeterian thinking, i.e, the so-called “creative destruction”. According with this concept the economic development is a dynamic phenomenon where new combinations - understood as a synonym of innovation - incessantly revolutionise the economic structure. The innovatory process involves the development of different products and processes, as well as a permanent search for new technologies, organisational capabilities and markets providing to the innovative firm extraordinary gains. Therefore, in the process of production and competition, the introduction of basic innovations leads to a process of “creative destruction” in which sectors associated with the “old” technologies decline and new sectors emerge and grow (Schumpeter, 1912). This dynamic assumes an evolutionary character which endogenously recreates economic structures through an uninterrupted process of innovations. The capitalist dynamic involves competitive forces in constant search for capital gains, in which even leading companies with high market power may be aware that remaining in such a situation requires constant investment.
37
Abramovitz, (1986), Silverberg & Soete (1994), and Silverberg & Verspagen (1995) have
highlighted that the innovatory dynamics sets the pace of economic growth where the ultimate goal is the catching-up. Thus, according to the “catching-up hypothesis”, a country’s
technological progress diffuses through the interface between innovative firms, responsible for introducing technological innovations in the economy, and imitative ones, responsible for
the transmission of innovations throughout the economic system based on their activities of “technological imitation” (Abramovitz, 1986).
Therefore, the innovative heterogeneity also divides countries according to the
capacity to promote technological innovations. While “leading economies” are responsible for the frontier of the scientific knowledge, the “followers” – countries with less developed
scientific basis – can only improve their technological capabilities through the incorporation of technological progress developed in leading countries or based on improvements of the
technological progress achieved by leading countries, which characterises “opportunity windows” (Oliveira, Jayme Jr. & Lemos, 2003). In both cases, technological caching up involves relatively smaller costs than those costs related to innovation for leading countries.
Moreover, stressing the importance of productivity growth for the economic
development – as in the Kaldorian theory and the structuralist approach – Perez & Soete (1988) point out that an efficient rate of technology incorporation results in a growth rate of
labour productivity in follower countries, i.e. developing economies43. The way in which these countries absorb and adapt technologies from leading countries will determine their productivity growth. In this process, the cumulative causation is generated though the impact
of knowledge accumulation on productivity growth (Nelson & Winter, 2002). This dynamic elucidates the essence of the “catching-up hypothesis”, where the gap between leading and
follower countries determines the potential of technological progress for backward economies (Abramovitz, 1986, Fagerberg, 1988a). In this sense, the process of catching-up takes place
when a backward country is able to maintain over time a technological progress higher than that of leading countries, due to a significant efficiency in absorbing new technologies (Olivera, Jayme Jr. & Lemos, 2003).
Although the technological gaps offer opportunities to catch up, they are not sufficient.
The success depends on “social capabilities” which allow developing countries to obtain
“advantages from the gap”. In this way, as pointed out by Freeman (1995) and Nelson (1993), 43
This assertion elucidates the development path followed by South Korea as showed by Kim (1997).
38
such characteristics are related to the institutional framework established in a determined structure by its National Innovation System (NIS). In this case emphasis is particularly put on
the role of historical processes, reporting differences in socio-economic capabilities for distinct development paths and promoting systems of innovation with very particular local
features and dynamics. The innovative performance depends not only on the scientific and
educational infrastructure of a country, the magnitude of R&D, labour force capabilities, among others, but also on how they interact between them and other variables, as well as all other forms by which industries in a country acquire, use and diffuse knowledge.
Additionally, the Neo-Schumpeterian literature considers that NIS cannot be replaced
by foreign technology since it has a local character. That is because the development of the
NIS in a certain economy affects the degree of technological sophistication of its products and consequently its exports. Thus, despite the recent globalisation process, NIS remains fundamental to the development of technical progress and its diffusion in a country (Freeman, 2004; Nelson, 1996; Dosi, Fabiani & Freeman, 1994). Innovation capacity derives, thus, from
the confluence of social, political, institutional, and cultural specific factors and from the environment in which economic agents operate in a specific country. Therefore, the chances of a country to catch up depend on its NIS capabilities in relation to “mature countries”
(Cassiolato & Lastres, 2008; Oliveira, Jayme Jr. & Lemos, 2003)44. A movement of structural change in favour of an intensive economic growth requires investments to build an institutional structure that supports learning and innovation which is essential to technological
upgrading (Nelson & Winter, 1982; Fagerberg, 1994; Freeman, 1995, Abramovitz, 1986; Albuquerque, 1999).
44
Jayme Jr. & Resende (2009) also states that the institutional structure summarised in a developed NIS provides opportunities for productive diversification and spillovers towards the technological frontier, i.e. technological opportunities for other sectors in the economy. On the one hand, a developed NIS and a diversified industrial structure have the propensity to offer better conditions for gains in international trade through exports. An economy with this structure may generally present at least three features regarding its exports: I) the conquest of new markets will be as diversified as its exports; II) more stability of the value exported since it involves distinct products and consequently reduce the risk of market fluctuations; III) an increase in the income elasticity of demand for exports since that the demand for imports tends to grow in times of world economic growth, opening more opportunities for countries which have a diversified range of exports. On the other hand, a less developed NIS tends to present a more specified productive structure. Consequently, the range of imports will be more diversified and the proportion of domestic market attended through the international supply higher. This dynamic tends also to affect the income elasticity of imports. Indeed, the country where the NIS is relatively less developed exposes a structural external vulnerability because the income elasticity of export demand is lower than the income elasticity of import demand.
39
5.2. Manufacturing shaping a hierarchy of national innovation systems: The case of Machinery industries The analysis of historical and national trajectories, taking into account the productive,
financial, social, institutional and political contexts, as well as micro, meso and macro
spheres, shows that an efficient NIS is a necessary condition to produce the learning processes that allow the structural change towards high-tech sectors, which are centralised in the manufacturing industry (Nelson & Pack, 1999; Freeman, 2003; Lastres, Cassiolato & Maciel,
2003). Through the convergence of the neo-Schumpeterian literature and concepts presented in the structuralist economics Freeman & Soete (1997) and Lundvall et al. (2002) present a
chronological overview of this dynamic, analysing, among other features, the role of “leading sectors” in the economy. They show how creative destruction has emerged from the manufacturing sectors and promoted a movement of structural change, i.e. changes measured
ultimately by variations in the share of industrial sectors in production or employment, since the First Industrial Revolution.
Lundvall et al. (2002) showed that the convergence of the structuralist approach and
Schumpeterian thinking was already presented in Perroux and his French followers. French structuralism had developed an analysis of the importance of the structure of national systems
of production for economic dynamics, some of it rooted in the Marxian schemes of extended
and intensive reproduction. Like Hirschman, they assumed that different sectors affect growth differently and that the most dynamic elements in the system (the growth poles) were located upstream, particularly in the manufacturing sector. This led them into ordering national systems in a hierarchy. It was assumed that countries such as the US, Germany and United
Kingdom had a stronger economy than France because their economies were more industrialised and their production systems were particularly specialised in the production of machine tools. Machine tools were the catalyst for the industrial revolution, which emerged in
Britain in 18th century. Since then, machine tools are the origin of almost every manufacturing process and for this reason recognised as mother machines.
Moreover, the historical
experience of the Great Powers of the industrial era – the US, the UK and Germany – gave
rise to a perspective where well-functioning machinery sectors were the driving force of a strong manufacturing sector and a long-term innovative interaction between industrial sectors.
The relevance of the machine tools industry for economic growth were also
documented by Rosenberg (1963), taking into account a historical perspective from 1840 to 40
1910. Rosenberg showed that the US, the UK and Germany have been those nations that have controlled, within their territories, the global production, reproduction and destruction of
machinery niches. As presented by Rynn (2010), by 1913, 82.4 % of the global production of machine tools was centralised in these three countries which had the most dynamic
manufacturing development at that time45. The US produced 50% of the world’s machinery, Germany 20.6% and the UK 11.6%. In 1925 the aggregated number rose to 84.3%, where the
US corresponded to 57.6%, the UK to 13.6% and Germany to 13.1%. The US could be considered a super power in terms of machinery during this time period; the US, Germany,
and the UK were the Great Powers because they dominated the production of machinery.
During the period of World War II, the USSR overtook the UK as the third biggest producer of machine tools. Certainly the technological global race evidenced in the years that followed, particularly during the Cold War, highlighted the importance of a leading capital goods sector as locus of technical change and economic hegemony.
Rosenberg (1963, p. 416) clarified the significant role played by the capital goods
industry in promoting economic dynamism, particularly regarding the introduction and diffusion of technological change, through two key aspects46. Firstly, the aspect of “external
adaptation” states that “all innovations whether they include the introduction of a new product
or provide a cheaper way of producing an existing product—require that the capital goods sector shall in turn produce a new product (capital good) according to certain specifications”. In other words, the industry of capital goods needs to maintain its production at the edge of
the technological frontier in an adaptive and innovative way to develop dynamic systems of production that set the rhythm and path of economic growth.
Secondly, the “internal adaptation” aspect refers to the internal motivation that
machinery producers improve their own techniques of production that affect the price of their
machinery output – cost reduction – and therefore is an important determinant of investment activity throughout the economy and, consequently, it determines the rate at which technological innovations are introduced and diffused in other manufacturing industries.
Furthermore, since cost reduction in the machinery industry is a form of capital saving for the economy, it also raises the marginal efficiency of capital of other industries.
In May 1927, the League of Nations held an International Economic Conference. As part of that conference, Dr. Karl Lange presented a memorandum that discussed the state of the machinery industries. 46 Fajnzylber (1983) also emphasises the central role played by the sector of capital goods for technological progress, and to create an endogenous nucleus of technological dynamism in the economy. 45
41
Over the years the sector of capital goods underwent significant technical
advancements enabling intra and inter-sectoral spillover effects in the economy and pushing
the technological frontier. The machine tools industry also has a significant role in the
industrialisation process transferring production know-how and technology to other manufacturing sub-sectors which enhances industry’s capacity to develop and produce new
products and increases the productivity level and competitiveness of the country’s manufacturing base. As a knowledge-intensive sub-sector of the manufacturing industry, machine tools also enable the transfer of the latest advancements in information and
communication technologies or material sciences into production systems, which increases
the efficiency of the productive process and develops new materials which are used later in
new fields of application such as in railway vehicles, ship building, aerospace and automobile industries. Since the engineering know-how in production technologies accumulated in the
machine tools industry is a competitive advantage, it also benefits first-mover firms in the development of many other new products and processes (Saxena & Sharma, 2014; CECIMO, 2011).
These unique characteristics found in the machine tools industry have a strategic place
within the economic dynamic. Consequently, throughout the twentieth century, countries that
reduced the capacity to make manufactured goods became dependent on imported machinery for the domestic industries and consequently lost economic dynamism. Furthermore, countries
that faced a decline in their machine tools were also those who lost the higher shares in
manufacturing. Due the global shift of machine tool towards Asian countries, the US and Europe have clearly lost global market share in the last four decades. Among developed countries the US underwent the most expressive decrease in the machine tools production
losing around 77 percent. While the US experienced a constant fall in the last four decades, Japan and Germany presented an increase until 1995 reaching respectively 23.5 and 16 percent of the global machine tools production. From 1995 onwards all the most
representative producers of machine tools in Europe, i.e. Germany, the United Kingdom and
Italy, faced a constant fall in their market share, dropping respectively from 22.6% to 16%,
from 8.5% to 8% and 2.7% to 1.7%. In an opposite trend China followed an upward trajectory becoming the world’s biggest producer of machine tools with 32% of the global production,
i.e. one third of the worldwide machine tools production is centralised in one country47.
47
These data were taken from Rynn (2010) and Gildemeister Annual report 2010.
42
Therefore, it is not by coincidence that China has showed an impressive dynamism over recent decades showing the relevance of manufacturing to today’s world economy. 6. Concluding remarks This chapter is a study which makes an effort to combine different theoretical strands
on development regarding the importance of the manufacturing industry to economic growth.
Through a confluence of the Keynesian-Kaldorian, Structuralist and Neo-Schumpeterian
frameworks, this chapter argued that the manufacturing industry presents some special properties which are not found in other sectors. The theoretical discussion presented through
this heterodox triad shows how these theories incorporate different levels of economic theory,
i.e. micro (firm), meso (sector and sub-sectors) and macro (economy) and are mutually complementary about the special role of the manufacturing industry in economic development. Therefore, this chapter constituted the theoretical core of this dissertation.
The first section described the Anglo-Saxon Structuralism also known as Early
Structuralism and the Latin American strand. As a general characteristic among both
structuralist strands, the economic development is narrowly linked to a radical transformation in the structure of production to suppress obstacles, bottlenecks and other rigidities of the
underdevelopment. Based on the hypothesis that the industrial structure affects both the pace and the direction of economic development, the structuralist literature highlighted the
importance of the industrialisation as a process of structural change where the manufacturing sector plays a central role. The structuralist strand states that without a dynamic
industrialisation, it is not feasible to increase employment, productivity and income per capita
and, consequently, to reduce poverty. The main argument stresses that the development process involves a production reallocation from low productivity to high productivity sectors where increasing returns to scale prevail. Inserted in this theoretical background, economic
structuralism has provided many reflections on how economic growth should be understood in a historical perspective of mutual causation in the economic system.
The second section sought to describe the Kaldorian approach to growth, understood
as “laws” where Kaldor argued that it is not possible to understand the development process
and growth rate differences between countries without taking a sectoral approach. In a
complementary line of research to Furtado, Hirschman, Rosenstein-Rodan and Prebisch, 43
Kaldor noted that the manufacturing sector was imbued with special growth-enhancing properties that trigger a process of cumulative causation that is not shared by other sectors.
The so-called Kaldor’s stylised facts were brought back in many contemporary studies that validated the Kaldorian approach to today’s world economy. Moreover the section reviewed
the debate regarding the importance of the manufacturing industry for economic dynamism,
highlighting the debate of three sources of de-industrialisation, i.e. the so-called statistical
illusions, servicification and productive fragmentation. In this sense, this section showed that a non-negligible part of the extent of de-industrialisation reflects changes in statistical classification rather than a real decreasing relative importance of manufacturing.
Additionally, it is also emphasised that despite the considerable rise of services in
recent years, manufacturing is still the main engine of growth because many services
essentially are spin-offs from manufacturing production. Furthermore, the increasing trend of
productive fragmentation over the world has not only decreased the manufacturing share in many economies but also negatively affected these countries through a deterioration of the so-
called “industrial commons” that caused a loss of high-value added activities, such as R&D and design, as well as the capacity to generate technological innovation. The Kaldorian
section still explores the role of manufacturing for productivity growth stating that the rate of productivity growth in the manufacturing sector depends on its rate of output growth due to
the operation, within this sector, of static and, above all, dynamic returns to scale. This section ends showing the role of manufacturing for the equilibrium of balance of payments and highlighting the importance of manufacturing technology-intensive sectors in this dynamic.
The third section investigates the Neo-Schumpeterian route to development, exploring
relations between innovation, economic dynamic and catching-up in a sectoral specific
approach. From this discussion, it is emphasised that the way in which a developing country absorbs and adapts new technologies from leading countries will determine its economic dynamism. However, the technological catching-up depends on its National Innovation
System. Consequently, the more developed the country’s NIS is, the larger the range of goods
produced in the global technological frontier will be. This process stimulates the performance
of exports value and mitigates the value of imports, generating a pattern of exports which can
overcome the structural external vulnerability and the underdevelopment. Additionally,
through the convergence of the neo-Schumpeterian literature and concepts presented in the structuralist economics, studies showed the role of the manufacturing sector as a locus of technological change since the First Industrial Revolution. From this perspective arose the
44
role of the machine tools industry in economic growth, particularly regarding the introduction and diffusion of technological change to the economy.
45
Appendix 1.1 - The Kaldor-Dixon-Thirlwall cumulative causation model In contrast to the neoclassical growth theory, which emphasises the importance of
mechanisms that generate convergence, Kaldor (1966, 1970) highlighted the weight of
cumulative mechanisms that slow down convergence or make economies diverge. A few
years after Kaldor had developed broad ideas about the mechanisms behind the cumulative
causation model, Dixon & Thirlwall (1975)48 presented the first formalisation of the standard cumulative causation model through four equations in order to clarify its structure. The basic model is very recognised and represents that the rate of growth of output is a function of the growth of exports. It is given by:
y = γx
(1.1)
Where (y )denotes the rate of growth of output in time(t). The term (x ) is the rate of growth of exports and (γ) is the elasticity of output growth with respect to exports growth.
This equation underlines the role of external demand in an open economy. In this
sense, a diversified industry in terms of manufacturing goods, which are highly demanded internationally, tends to increase the country’s output growth. The equation of export demand can be defined as: X = P P (Z ) Where (X ) is the quantity of exports, (
(1.2)
) is the price of domestic goods, (
) is the price
of foreign produced goods, ( ) is the price elasticity of demand for exports, ( ) is the cross
elasticity of demand for exports, (Z ) is the level of the world income and ( ) is the income elasticity of demand for exports.
This, for discrete changes, gives the approximation: =
+
+
(1.3)
Assuming that η = δ, as proposed by McCombie & Thirlwall (1994), the growth rate
of exports, in turn, can be expressed as:
= 48
See also Dixon & Thirlwall (1979).
−
+
(1.4)
46
Where lower case letters represent variables in terms of rates of growth. While
and
are determined exogenously, the rate of change of domestic prices is
given by the mark-up pricing equation, taking into consideration that firms set their prices. It can be specified as:
=
−
+
(1.5)
Where w , r and τ respectively represent the rate of change of money wages, the rate of
growth of average labour productivity and the mark-up on unit labour costs49. Finally, the linchpin of the system to complete the model stresses that the rate of labour productivity is partly dependent on the growth of output itself, i.e. “the Kaldor-Verdoorn law”. Thus, the
following equation (6) is Verdoorn’s law, which connects the rate of labour productivity growth and that of output growth. It has been specified as: =
+ (
)
(1.6)
Where ( ) represents the rate of autonomous productivity growth and ( ) the Verdoorn
coefficient. This equation exposes the fundamental mechanism for cumulative causation in the model. This equation allows the possibility of cumulative growth. The growth of output improves the productivity of labour, reducing the price of domestic products (8), leading to new rounds of export growth (7) and more output growth (4). Combining equations (4), (7), (8) and (9), the expression of the equilibrium growth rate of output is given by: = The equation (10) shows that, since
(
]
(1.7)
< 0, the rate of growth of output varies positively as a
function of the autonomous rate of productivity growth ( ), the growth of foreign prices (
), the growth of world income ( ) and the income elasticity for exports ( ). In
contrast, output growth varies negatively with the rates of growth of money wages ( )and
mark-ups on unit labour costs ( ). In this view, the Verdoorn coefficient ( ) constitutes the heart of this model. Moreover, it gives an important contribution to the understanding of why economic growth differs between countries. Therefore, manufacturing production has a central role in determining the productivity of the economy.
It is important to emphasise that the Dixon and Thirlwall model tries to interpret a developed country – such as Britain – where wages and labour productivity are assumed to be high. 49
47
CHAPTER 2 – FALLING BEHIND AND MOVING AHEAD: THE BRAZILIAN AND SOUTH KOREAN PROCESS OF INDUSTRIALISATION “Don't listen to ‘comparative advantage’ advice. Whenever we wanted to do anything the advocates of comparative advantage said, ‘We don't have comparative advantage.’ In fact, we did everything we wanted, but whatever we did, we did well.” Sung Sang Park, Governor of the Bank of Korea from 1986 to 198850. “The best industrial policy you can have is not have one.”
Pedro Malan, Brazil's Finance Minister from 1995 to 200351.
Introduction Comparisons of the Latin American and East Asian industrialisation experiences are very commonplace. At a first glance, until the 1980s, Brazil and South Korea presented similarities in terms of political and economic development. During the 1960s and 1970s, both countries were governed by dictatorial regimes and had their development path based on the so-called national development plans which sought to strengthen the heavy industrial base – metallurgical, chemical and metal-mechanic industries. Under the developmental agenda, although through different strategies, the results achieved by a state-led industrialisation were
not negligible, showing a strong economic and industrial growth with both economic blocks increasing their share of manufactured products in the global value added. From 1950 to
1980, the Brazilian share increased from 1.65% to 3.12% and in South Korea this number rose from 0.33% to 0.76%52.
Quoted in Robert Wade, “East Asia’s Economic Success, Conflicting Perspectives, Partial Insights, Shaky Evidence. World Politics, Volume 44, Issue 2 (Jan., 1992), 270-320. 51 Quoted in David Trubek, “Toward a new law and development”, The World Bank Legal Review, volume 4, 2012, 287. 52 Source: GGDC 10-Sector Database. 50
48
However, in spite of the vigorous growth, in both economies, after the 1980s some
structural problems came up, reversing this similar economic dynamism. In both countries
exogenous shocks like oil crises in 1973 and 1979, the Volcker interest rates shock in 1979 and the debt crisis in 1982 triggered a severe imbalance in the public finances and a deep
current account deficit. On the one hand, Brazil as well as the rest of Latin America was badly affected by these shocks due to its large current account deficits and its large stock of external debt. This vulnerability, associated with an abrupt cut-off in bank financing, plunged the
country into a serious crisis and caused a deep disarticulation of the state to provide active policies for the national industry. Consequently, economic growth was seriously retarded
giving rise to the commonly used term “lost decade”. On the other hand, Korea dealt with the crisis in a much less traumatic way since its strategy of industrialisation was relatively less
dependent on foreign debt and the Japanese banks “recycled” the country’s liabilities. Therefore, the Korean state and corporations consolidated and expanded the domestic industrial base through an industrial partnership with Japan.
In contrast to Korea, the Brazilian economic weakness caused by exogenous and
endogenous shocks gave rise to the neoliberal view that spread through the perception that
severe macroeconomic imbalances and the institutional framework of a model based on the
Import Substitution Industrialisation (ISI) did not promote the development of a competitive industrial base as observed in international markets. The adoption of the neoliberal agenda supported by the World Bank and the International Monetary Fund (IMF) exposed Latin
American economies to a doubtful development strategy based on the free market doctrine to
conduct the development path53. In a different development strategy, Korea, as well as other Asian countries, did not embrace the neoliberal agenda in such “fundamentalist” way. In fact,
the state directed and coordinated investment decisions to expand the productive structure and achieve levels of technology compatible with competing in external markets. While the
Korean strategy of development based on “getting prices wrong” resulted in a trade and
productive dynamism never observed before in the emerging world54, Brazil and Latin America as a whole followed a perverse strategy through neoliberal reforms that subjected the
country to low rates of economic growth followed by cycles of stop-and-go over the last three decades. This debate has reopened different interpretations of the development model adopted
53 54
See, for instance, Frenkel et al. (1992). See Amsden (1989).
49
by Brazil and South Korea as well as endogenous and exogenous dimensions that shaped their industrial structures.
Focusing on by factors which include the sectoral composition of countries and the
role of the state in guiding the development path, the main contribution of this chapter is an identification of factors that determined different routes of economic dynamism followed by Brazil and South Korea from the 1980s onwards. Thus the chapter is divided in eight sections, apart from this introduction. The first section elucidates briefly the whole of the developmental state for economic growth. The second section describes the developmental
era in both countries in a comparative perspective detailing the development plans implemented from 1950s to the late 1970s. The third section makes an attempt to balance the role of public and private sectors in the formation of these late industrialised countries. Thus,
seeking to answer why the decoupling in growth rates was much more drastic in Latin
American countries vis-à-vis Asian economies, the fourth section explains the genesis of the
debt crisis. The fifth section analysis the reason behind the technological decoupling between these two economies and the trajectory of technological learning undertaken by South Korea.
The rise of the neoliberal era is described in the sixth section to give the necessary support to understand the economic policy change after the 1980s. Therefore, the outcomes in terms of industrialisation and sustained economic growth in a long term perspective are approached in
the seventh section highlighting the dichotomy between Brazil and South Korea in terms of
labour productivity, catching-up and exports. The last section presents some concluding remarks.
1. The Developmental State promoting a Big Push in economic growth In the economic literature on development, there are a vast range of studies stressing
the transformative power of industrialisation in the economic system. Classical StructuralistKaldorian contributions by Rosenstein-Rodan (1943), Nurkse (1953), Lewis (1954),
Hirschman (1958), Myrdal (1957), Kaldor (1966, 1967) and Chenery (1960, 1979) pointed
out that the study of long-term economic growth involves the role of industrialisation as
engine of economic growth. These “sector- specific” approaches emphasised the special properties of manufacturing (such as highest potential of productivity, spillover effects, strong
forward and backward linkages, as well as technological and pecuniary externalities) and the way in which these properties spread to the economy as a whole stimulating the economic
50
growth. However, the economic literature has also stressed that successful cases of
industrialisation were not a spontaneous process. Therefore, the developmental literature has discussed the active role played by the state in the industrialisation process of many latecomer economies55.
Although the concept of developmental state has been applied in a number of contexts,
contemporaneously, the state’s commitment to developmentalism has been expressed through common policies and institutions designed to achieve national economic development. In this sense, Chang (1999, p.183-192) defines a developmental state as “a state which can create and
regulate the economic and political relationships which support sustained industrialization (...) This state takes the goals of long-term growth and structural change seriously, ‘politically’
manages the economy to ease the conflicts inevitable during the process of such change (but
with a firm eye on the long-term goals), and engages in institutional adaptation and innovation to achieve these goals.”
Additionally, a central element in this context has been the 'pro-investment'
macroeconomic environment for industrial growth. As a general characteristic, the
instruments implemented by the developmental agenda comprised controls over interest rates and credit allocation, including particularly long-term financing with low interest rates. In
addition to financing, a set of tax and tariff measures such as customs tariff protection, tax exemptions, and special depreciation allowances were applied to provide protection to the
nascent industry. Moreover, measures to boost enterprises’ profit margins and therefore the potential investible resources available to corporations were widely implemented. In the case
of South Korea, for instance, it is also possible to mention policies for technology acquisition, incentives to activities of R&D and the promotion of cartels for specific purposes such as standardisation, specialisation and exports (Akyuz et al., 1998).
As pointed out by Coutinho (1999), the sequence of sectoral priorities, as suggested by
Hirschman,
and companies to support, in order to carry forward the development agenda,
were part of development process that involved financial institutions (e.g. development banks)
and planning (e.g. committees, ministries, departments). In this process, the state’s initiative and leadership was a general rule varying from case to case according to the interaction and
Even the World Bank at the height of the neoliberal revolution acknowledged that in most Asian economies, especially those in East Asia, the State did more than get the “prices right”. Actually, the intervention was carried out basically with three policy instruments: (i) the promotion of specific industries, (ii) directedinvestment programmes and (iii) the promotion of exports. For details, see ‘The East Asian Miracle' published in 1993 by the World Bank. 55
51
coordination with the private sector. In short, elements of planning, selection, intervention and dirigisme were present in all successful cases of rapid industrialisation. The creation of
competent bureaucracies of the state, organised under meritocratic criteria to operate the most
important institutions, constituted an indispensable condition for coordination of industrial policies.
Furthermore, the implementation of development plans, especially in the most critical
stages of heavy industrialisation, demanded a clear concentration of political power in the executive authority that was structured around a certain core of the bureaucratic system able
to organise and give coherence to the multiple instruments used for the implementation of sectoral programmes. In this sense, both in Brazil and South Korea fit paradigmatically in the
pattern described above, evidently under peculiar political and historical contexts. The most important divergences from the pattern of industrial development in these economies refer to
the interrelation between the state and private spheres as well as distinct forms of international trade insertion and investment pattern (Cheng et al., 1998). Therefore, while in South Korea
the domestic private capital, represented by the Chaebols, played a decisive role in the evolution and development of Korean industry, in Brazil economic growth and investments
were driven by state-owned enterprises and multinational companies established in the
country during the 1950s and 1960s. Both dynamics are analysed in the next two subsections.
2. Mapping the Golden Age of the Industrialist Era 2.1. Brazil: 1930-1980 For the five decades between 1930 and 1980, the concern with the development of the
productive structure remained a central element in the analysis of economic growth. The
period of transition from a primary export model to a strategy of Import Substitution Industrialisation (ISI) was widely discussed by theorists such as Furtado (1959), Tavares (1972) and Cardoso de Mello (1982), Suzigan (1988), Serra (1982), Malan & Bonelli (1983). In Brazil, between the 1930s and the end of the Second National Development Plan (PND II)
in 1979, this theoretical framework was extremely important for the development strategy adopted through industrial diversification supported by the state. From 1930 until 1980, the Brazilian economy had a remarkable growth record achieving one of the highest rates of
52
growth in the world. During this period gross domestic product grew at an annual average rate
of 6.5%, while real GDP per capita increased at an annual rate of 3.8%. In this context throughout this fifty-year period, the growth strategy adopted was based on ISI policy. Under the ISI regime, Brazil based its strategy of development in a strongly state-led orientation
which was theoretically formalised by the Latin American structuralist view which
incorporated relevant arguments of the infant industry56, and the Keynesian economics approach.
As presented by Furtado (1959) and Tavares (1972), the Brazilian development until
1930 could be defined as an outward orientation, via a primary-export model, whose demand was determined exogenously. In this dynamic, the agricultural-export sector was responsible for the growth of the product, the formation of national income and the capacity to import. With the primary sector crisis in the late 1920s, together with the effects of the Great
Depression in the 1930s, there was a strong decrease in export revenues – due to the decrease of exports earnings as a result of the plunge of coffee prices – and, consequently, a sharp drop
in the import capacity that represented a reduction of 50% in the quantum of imports. This
phenomenon forced the country to develop new productive activities, with the support of the domestic demand previously met by imports (Tavares, 1972). Therefore, a new dynamic
started to be shaped with domestic demand playing a central role in the strategy of
development57. In contrast to the previous period, the external sector lost relative importance in the composition of national income whereas the participation and dynamism of the
domestic market increased in the economy. Moreover, the external sector which was previously a source of demand started to contribute to the expansion and diversification of the productive structure supplying capital goods and intermediate goods.
Based on this structural dynamic, during Vargas’ government (1951- 54), the
apparatus that enabled the process of a state-led industrialisation started to be consolidated and inspired by the opportunities created by the reconfigured international division of labour
in the post-war period. This view was closely in line with the framework of historical analysis
formulated by the new generation of economists coalesced at the Economic Commission for Latin America (ECLA), created by the Economic and Social Council of the United Nations in
56 57
See Hamilton (1790) and List (1841). Furtado (1959) denominated this phenomenon as a ‘displacement of the dynamic centre’.
53
194858 (Ioris & Ioris, 2013). The perspective in vogue was that the Brazilian economy had to establish the basis for a more dynamic process of industrialisation. During Vargas’s
government, industry advanced though import substitution of consumer goods by national private capital and some intermediate goods through state-owned enterprises (SOE).
Inspired by the ECLAC developmental thinking, in 1951, the Industrial Development
Commission (CDI) was created to formulate a plan of industrialisation alongside with specific
projects to create and expand priority sectors such as energy, metallurgy, mineral processing,
chemical, textile, rubber and building materials. Its creation was a strengthening of the
government's role as an economic agent and favoured the collaboration between industries and the state59. Moreover, in 1952, the Brazilian government concerned with the country’s infrastructure led to the creation of the Brazilian National Bank of Economic Development
(BNDE)60. The BNDE started out as a vehicle to provide long-term financing for the renewal of large infrastructure projects such as energy, steel and transportation, as well as providing
resources for heavy industrialisation. At the same time, many state-owned enterprises were created to support and propel the ongoing process of industrialisation particularly in areas less
appealing to the private sector. A remarkable example is Petrobras, which was established in 1953 to undertake activities of exploration, production, refining of oil and its derivatives.
During the 1950s, credit policies, multiple exchange rates and preferential tariffs for
imports for specific sectors were extensively adopted to boost the industrial growth. In this
way, an important step taken by the Brazilian government was the resolution (Instruction 70) issued by the Superintendence of Currency and Credit (SUMOC) in 1953, which ranked
imports according to their essentiality61. This normative instruction established five exchange rate categories, depending on the item being imported. Imports considered of national interest,
particularly fuel, wheat and print paper, were subsidised while other items were strongly discouraged by over-taxation. Furthermore, the government offered a variety of incentives to
attract Foreign Direct Investment (FDI), such as tax cuts and subsidies. Thus, in 1955, the The commission is nowadays described as the Economic Commission for Latin America and the Caribbean (ECLAC), with its headquarters in Santiago, Chile. 59 The CDI was abolished in 1954 with the end of the Vargas government, but reborn in 1956 during Juscelino Kubitschek’s government with the name of the Development Council. 60 The acronym was later changed to BNDES when “social development” was added to the name in 1982. 61 This instruction represented a stimulus for at least three reasons. First, by rising domestic prices of specific imports it consolidated protection for producers of industrial goods. Second, it provided concession of exchange subsidies for capital goods and basic inputs required for the process of industrial development. Third, with the additional revenues obtained by the auctioning of foreign currency to importers of ‘non-priority’ goods, it raised public funding for government investments in infrastructure (Studart, 1995). 58
54
Superintendence of Currency and Credit (SUMOC) issued a resolution (Instruction 113) which allowed imports of capital goods without exchange cover to be counted as direct
foreign investment62. In practice, under a regime of multiple exchange rates, these resolutions provided a subsidy for imports operations and together they served as the two most important tools of commercial policy to support the process of import substitution.
In 1956, the recently elected President Juscelino Kubitschek launched the Targets Plan
(Plano de Metas – 1956-60) to accelerate the process of industrialisation. The slogan in vogue
at the time was that Brazil would advance “fifty years in five”63. The main aim was to achieve the heavy industrialisation with ISI deepening in sectors such as automotive, shipbuilding, heavy electrical equipment and machinery, allowing a significant expansion of the capital
goods sector. With regard to basic industries, the plan particularly addressed industries such as steel, non-ferrous materials, heavy chemicals, petroleum, pulp and paper. As result of
developmental policies the investment-to-GDP ratio grew from an average of 14.91% in 1951-55 to 16.04% in 1956-60. In this investment promotion agenda, a central role was
played by the state, whose participation in national investment increased from 23.80% in
1951–55 to 29.78% in the period 1956–60. During the Targets Plan, the Gross Domestic Product (GDP) grew in average 7.7% and the manufacturing industry rose 11.37% per annum64.
In the early 1960s, however, the Brazilian economy showed serious economic
imbalances alongside with an unstable political period. In the economic side, the constant
increase in public expenditure during the 1950s led to a severe budget deficit, which was largely financed by the expansion of the monetary base, causing a sharp increase in inflation
rates (Britto, 2008). On the political side, President Quadros’s resignation in 1961 initiated a
serious political crisis that culminated in a military coup in 1964. Due to this critical scenario,
both the GDP growth and investment rate presented a volatile trend. These variables combined with a significantly lower import coefficient, led many economists to diagnose the end of ISI growth model.
With the rise of the military regime, the Government Economic Action Plan (PAEG)
was launched to give emphasis to short-term policies to combat inflation, inherited from the 62
Since the Brazilian Central Bank was created in 1964, prior to this year, the responsibilities of a central bank were shared by the National Treasury, the Brazilian Bank and the Superintendence of Currency and Credit (SUMOC), which was later expanded to become the Central Bank. 63 See Lessa (1983) and Lafer (2002). 64 See Appendix 2.1.
55
Target Plan, and make structural reforms. Thus, from 1964 to 1966, under the mandate of
General Castello Branco, the military government undertook a tight fiscal and monetary policy to tackle increasing inflation and public deficit. The military government conducted
structural reforms which encompassed three pillars, i.e. finance, taxation and external sector65. Therefore, the financial reform implemented by the PAEG sought to create mechanisms of long-term financing to avoid the inflationary financing of the public sector and allow the private sector to recover the industrial investment. The financial reform led to the creation of the Central Bank, and the establishment of a series of indexation mechanisms to protect longterm contracts from inflation. Moreover, the BNDES changed its focus from lending to public
projects to financing private companies66. In terms of tax reform, the state implemented the value added tax (VAT) that increased govern revenues as percentage of GDP from 17% in
1964 to 20.9% in 196667. Despite the success of the Plan, particularly regarding stabilisation and reforms, the country was still trapped in a cycle of mediocre economic growth.
Therefore, in 1967, under the administration of the General Costa e Silva, there was a
radical change in the economic policy. The Minister of Finance, Antonio Delfim Neto,
promoted expansionary monetary and fiscal policies that were successful in inducing
economic recovery. These policies, associated with the return of external liquidity, restored the mechanisms of the state to provide funding for public and private agents. From 1968,
reaching an investment rate of 18.7% of GDP, ISI returned to deepen and to promote the country’s economic growth, under a strong developmental thinking. The First National
Development Plan (I PND: 1972-1974) was launched to promote investments concentrated
especially in the durable goods sector and infrastructure. Consequently, the economy experienced unprecedented economic growth, fuelled by private consumption and public investment in infrastructure.
This period corresponds to the so-called “Brazilian miracle” (1968-1974) in which the
country grew an average of 11.7% per annum. During the peak of the economic miracle, from 1970 to 1973, the capital goods industry grew at an annual rate of 22.5%. In this interregnum,
For more details about reforms implemented during the 1960s, see Simonsen (1970) and Lara-Resende (1989). In 1965, in order to support the development of the machinery and equipment industry, the first subsidiary of BNDES, namely Government Agency for Machinery and Equipment Financing (FINAME) was created. In the ISI model, the domestic machinery industry was seen as a strategic sector to overcome the dependency on foreign imports of capital goods and therefore foster industrial growth. FINAME had the objective of providing medium- and long-term funding for the development of the machinery and equipment industry. It comprised financing purchase and sales operations and exports of Brazilian machinery and equipment, as well as imports of goods of the same nature not produced domestically. 67 Source: Brazilian Development Bank (BNDES). For historical series, see BNDES (2001). 65 66
56
the durable consumer goods industry maintained growth rates of 25.5% per annum. However, given the macroeconomic instability caused by the first oil shock in 1973, the "economic
miracle" ended imposing a new challenge to the government that took office in 1974.
Therefore, the development of a new developmental project faced a scenario in which the
Brazilian industrial structure was not fully diversified and the country was still very dependent on import of capital goods and basic inputs, such as oil.
Under the developmental aegis, the Second National Development Plan (PND II:
1975-1979) emerged as an attempt to maintain the economic growth even in face of a strong
international instability. This last economic programme of the Brazilian developmental era
was announced in order to advance the industrialisation model in an environment marked by the absence of a consolidated and coordinated long-term funding system. The new programme
guidelines focused on continuing ISI, particularly accelerating it in intermediate and capital
goods, and correct productive weaknesses. The industrial policy also sought to propel sectors
related to basic inputs, food and energy as a way to overcome the external constraint.
Thereby, the measures adopted sought to generate profound changes in the productive structure (Castro & Souza, 2004; Castro, 2001).
The main pillars of the Brazilian industrial policy were the combination of trade
protectionism, promotion of investments by state-owned enterprises and financing granted by the BNDES. These measures sought to coordinate the expansion of the domestic supply and
maintain high rates of investment in a gradually adverse scenario (Carneiro, 2002). After the first oil shock in 1973, the refusal of II PND to adopt a strategy more cautious in face of the dramatic external environment led to a gradual replacement of the private investment by the
public sector to maintain the high rate of economic growth68. Therefore, public investments increased from 23.5% in 1974 to 28.5% of the total investment in 1979, while private investments for the same period fell from 60% to 55% (Serra, 1982; Coutinho & Reichstul, 1982).
Although distant
from
the technological
frontier in
many
industries,
ISI
regime resulted in a diversified industrial structure, deeply regulated, integrated and driven by the domestic market which resulted in a profound change in the productive structure and a
progressive de-linking from the international economy with increasing shares in the global GDP.
68
See also Lessa (1977).
57
Table 2.1 - Brazilian Economic Development Plans and Economic Indicators Economic Development Plan
Sectoral Composition
GDP Growth
Export/ GDP
Import/ GDP
GFCF/ GDP
Primary Sector
Manuf.
Services
8.12
5.86
6.22
16.04
11.62
20.42
62.25
PAEG (1964-1968)
5.30
6.46
5.86
16.10
10.32
21.07
62.41
I PND (1972-1974)
11.35
7.60
10.40
20.85
7.24
22.80
63.37
6.42
7.06
9.10
22.54
6.20
21.67
64.58
Targets Plan (1956-1960)
II PND (1975-1979)
Source: Elaborated by the author, using data from The Brazilian Central Bank, Brazilian Institute of Geography and Statistics (IBGE), Ipeadata, World Bank – World Development Indicators, The Conference Board and Groningen Growth and Development Centre and UNCTAD. Note: GDP = Gross Domestic Product, GFCF = Gross Fixed Capital Formation and Manuf. = Manufacturing. PAEG = Government Economic Action Plan, First National Development Plan = I PND and Second
National Development Plan II PND.
2.2. South Korea: 1945-1980 As widely documented in the literature, South Korea is one of the most successful
trajectories of economic development in the second half of the twentieth century (Jones & Sakong, 1980; Bénabou, 1982; Pack & Westphal, 1986; Amsden, 1989, 2001; Canuto & Ferreira, 1989; Chang, 1994, 1998, 2002; Canuto, 1994 and Rodrik, 1994). However, the
immediate post war period was characterised by extreme economic disorganisation and
stagnation due to geopolitical turbulences. In 1945, Korea emerged from World War II under US occupation after a long period of Japanese domination. Shortly after the proclamation of the Republic in 1948, the country was the scene of a new war with North Korea that lasted from 1950 to 1953. During this period, South Korea struggled to take the first steps in a
process of industrial development. At that time, the manufacturing sector was very incipient and the weak industrial bourgeoisie was entirely dependent on the state.
After the Korean Armistice in 1953, South Korea moved from a majority agrarian
economy to an industrialised country, showing levels of income per capita and well-being much higher than any other developing nation. In the 1950s, under President Syngman Rhee’s government, South Korea adopted ISI model and focused in the following measures: (i) support for the non-durable consumer goods sector, particularly with low capital intensity,
58
though favoured credits and import licenses; (ii) the creation of national capitalist groups
through subsidised privatisations of several companies, including banks; (iii) the implementation of a broad agrarian reform in order to reduce social tensions and create a new social base to support the dictatorial regime; (iv) efforts to reduce illiteracy and promote basic
education. Over this decade, Rhee’s dictatorial regime led this process based on the support given by the US and economic groups that were favoured during the period (Coutinho, 1999).
Additionally, as explained by Frank et al. (1975), from 1953 to 1960, most of South
Korea's imports were financed by foreign aid grants from the United Nations Korea Reconstruction Agency (UNKRA) and the United States bilateral assistance programme. Both
sources of foreign aid were used to import food and essential industrial raw materials as well as capital goods. Between 1954 and 1960, foreign assistance, excluding donations by foreign voluntary organisations, financed more than 70 percent of total imports. Furthermore, about
74 percent of South Korean investment was financed by foreign aid from 1953 to 1960. From 1953 to 1960, GDP grew on average 4.37% per annum and the only bad year was 1956 with
0.48% of GDP growth. However, this rapid economic growth also resulted in a surge of
inflation. The consumer price index (CPI) increased on average 40.8% per annum between
1953 and 1957, reaching its highest point in 1956 when the inflation rate peaked to 68%69. Therefore, concerned about inflation, both the South Korean Government and the Office of
the Economic Coordinator (OEC)70 established a plan to control the rampant inflation rate. After the implementation of the programme in 1957, the annual rate of domestic inflation declined sharply.
In 1960, the lack of political support and a wave of popular uprisings led by students
culminated in the resignation of President Rhee. After a year of political instability, in May 1961, a military coup overthrew the Chang Myon government that had come to power following the student revolution. Park Chung Hee, presided over South Korea from 1961 until
his assassination in 1979. During this period, General Park’s administration resulted in an impressive economic growth in parallel to a dynamic process of industrialisation through
successive five-year plans. The remarkable characteristic throughout this process was a
coordinated state planning associated with a sequence of clear objectives that resulted in a substantial increase in the economy's investment rate. The investment rate increased from 69
Source: OECD statistics database. The national reference year for the CPI index is 2010. The US government established the Office of the Economic Coordinator under the UN Command in Korea to coordinate between the US and Korean governments and other aid agencies (Kim & Kim, 2014). 70
59
11.70% in 1961 to 39.00% in 1979, and the GDP grew in average almost uninterruptedly 10.01% per annum71.Additionally, this period was marked by a considerable shift towards the adoption of the strategy of export promotion.
In the beginning of the 1960s, the South Korean industrial structure was still incipient
and poorly diversified. Moreover, it was based essentially on the production of non-durable
products. In this way, to overcome the problem of foreign exchange shortage and US dependence, General Park launched a programme of investments (first five-year plan, from
1962 to 1967) to expand the manufacturing industry with strong incentives for exports. The strategy was based on taking advantage of the alliance with the US government to penetrate the large North American market. The textile and clothing sector led this first export effort, complemented by other light industries. Therefore, a series of policy reform programs were
introduced. One of the first acts of the government of Park Chung Hee was to nationalise all commercial banks and establish many state-owned specialised banks72.With this control over
finance, the government could closely manage and monitor progress of industrial investment,
all development projects, and export performance (Amsden, 1989). Moreover, seeking to
improve competitiveness, the currency was devalued and a unitary floating exchange rate was adopted (Seong, 2001). Tax subsidies were also widely implemented (indirect taxes exemption, income tax reductions, tax premiums linked to performance targets, drawback, etc), estimating its volume as equivalent to 10% of exports in the period (Coutinho, 1999).
The second five-year plan (1967-1971) came to reinforce the Government’s
commitment with the export-oriented growth strategy. Exports as share of GDP increased
continuously from 11.02% in 1967 to 14.16% in 197173. It is important to highlight that, although export promotion was the main aim of South Korean development policy, investments in infrastructure and the domestic market also received attention during the
period. As the industrialisation process progressed, the need for a structured heavy industrial base to provide intermediate inputs domestically became increasingly evident. For instance, the Korean government created the national steel company, POSCO, in order to foster the development of a national industry. Therefore the industrial policy advanced to giving the
necessary support for the development of industries such as chemicals, machinery, and iron/steel. Thus, as explained by Amsden (1989), a central characteristic of the South Korean
Source: Bank of Korea, Economic Statistics System. Although pressures to liberalise in the 1980 led the government to privatise commercial banks, the South Korean government maintained its control over commercial banking system (Amsden, 1989). 73 Source: Bank of Korea, Economic Statistics System. 71 72
60
development relied on the combination of strategies to promote exports and the ongoing process of ISI.
At the beginning of the 1970s, President Park announced the third five-year plan
(1972-1976) for the transition to a heavy and chemical industrialisation. Industries receiving particular attention included iron/steel, nonferrous metals and petrochemicals. Additionally, this plan sought to provide the basis for shipbuilding, automobiles, machinery and equipments
industries. The programme was supported by a broad range of policy instruments. In 1973, the
South Korean government established the National Investment Fund (NIF) to supply funds to support the heavy and chemical industrialisation, as well as to help increase exports, through
low-cost financing. Furthermore, since Korean entrepreneurs' capacities to obtain foreign capital was very limited due to the low creditworthiness of domestic firms, the government
began to guarantee the reimbursement of all foreign loans, regardless of whether they were initiated by public or private companies (Seong, 2001). Additionally, to support the export-
oriented growth further, export incentives were expanded. In this way, tax incentives were deepened and the Export-Import Bank of Korea (Korea Eximbank) was created in 1976 to finance export operations with favourable interest rates (Coutinho, 1999). Along with these
policies, the government overhauled the education and training systems to promote and secure engineers and skilled workers into the heavy and chemical industrialisation74.
The fourth five-year (1977-1981) plan strengthened and fostered the development of
industries designed to compete effectively in the world’s industrial export markets. Therefore,
based on efforts undertaken in the previous plan, these major strategic industries comprised
technology and skilled labour-intensive industries such as shipbuilding, automobiles, electronics, machinery and equipment. In the late 1970s, the measures adopted in the third and
fourth five-year plans resulted in a rapid change in the industrial structure. Under the
developmental perspective, South Korea achieved a substantial increase of the manufacturing
share in the GDP. From 13.17% in 1950 the manufacturing share in the GDP rose to 27.62% in 1979, particularly due to the massive efforts of the developmental agenda to consolidate the
industrial base comprising light, heavy and chemical industries. In an intra-industrial analysis both the productive and export structure shifted gradually from labour-intensive sectors to
Aiming to support the heavy and chemical industrialisation, in terms of education policy, “the government also introduced a skills licensing system to encourage every Korean worker to possess at least one skill. In addition, for each field of engineering the government actively recruited outstanding Korean scientists abroad and established a modern laboratory where research on the improvement of production technologies was encouraged in collaboration with industry researchers and university professors” (Seong, 2001, p. 10). 74
61
capital-intensive ones by the end 1970s. Although costly to establish, from infant industries these capital-intensive sectors became progressively more competitive in the international market.
Table 2.2 - South Korean Economic Development Plans and Economic Indicators Economic Development Plan 1st Five-Year Plan (1962-1966) 2nd Five-Year Plan (1967-1971) 3rd Five-Year Plan (1972-1976) 4th Five-Year Plan (1977-1981)
Sectoral Composition
GDP Growth
Export/ GDP
Import/ GDP
GFCF/ GDP
Primary Sector
Manuf.
Services
41.68
15.25
40.41
11.46
12.65
23.81
25.34
30.45
19.25
46.15
10.50
24.81
30.40
27.16
27.43
24.24
44.23
7.44
28.53
33.23
34.02
21.52
27.44
44.05
8.34
6.70
16.32
16.04
Source: Elaborated by the author, using data from The Bank of Korea (BOK) and The World Bank – World Development Indicators. Note: GDP = Gross Domestic Product, GFCF = Gross Fixed Capital Formation and Manuf. = Manufacturing.
3. The role of the State and private sector in the industrialisation process 3.1. Creating National Champions: The South Korean Chaebols In South Korea, a relatively small domestic market size and scarce natural resources
endowments culminated in an outward-oriented industrial policy in order to re-orient
industrial production in favour of exports. In this perspective, the export orientation was an inevitable strategy to promote economic development given that on one hand the domestic
market was insufficient, particularly for sectors that exhibit increasing returns to scale, and on the other hand extractive industries were not internationally competitive to generate foreign
exchange. Therefore, the production and exports of manufactured goods sought to overcome
the lack of foreign exchange to support the industrial development which usually requires imports of capital goods, components and raw materials not produced domestically. Thus,
taking advantage of its special political status with the United States government, South Korea focused on the large US market as its main export target (Coutinho, 2000)75.
75
See also Amsden (1989) and Zysman & Doherty (1995).
62
Over the decades, South Korea sought to plan and prepare its manufacturing industry
for exports, taking into account the structure of the economy and opportunities in world trade.
This trajectory also represented an industrial upgrading strategy from 1950s to 1980s. Thus,
during the 1950s and 1960s, the industrial policy focused on light manufacturing
characterised by unskilled-labour-intensive sectors, then in 1970s shifted to sectors marked by skilled labour and economies of scale, i.e. particularly heavy and chemical industries. Finally,
in the 1980s, dynamic sectors with high technological content and specialised labour became
part of the industrial structure. In short, South Korea directed their efforts to constitute a
dynamic competitive advantage rather than by their static comparative advantage in cheap and unskilled labour.
Another important characteristic of the South Korean development was the
tight control over the FDI inflows in the 1950s and 1960s. Therefore, the South Korean
government sought to develop privileged national economic groups in order to propel the process of industrial growth. The large diversified corporate conglomerates – the so called
Chaebols – were structured over a robust state-controlled financial sector and closely resembled the Japanese zaibatsu (family-owned conglomerate), which is different from the current Japanese corporate ‘families’ centred on a bank, namely keiretsu (Chang, 2003). The
Chaebols were largely controlled by their founding families, centralised in ownership,
generally formed by subsidiaries to produce components for exports and heavily dependent on government loans and loan guarantees in their early years.
Articulated through trading companies, these Korean conglomerates were very
effective tools for the exploration and development of foreign markets along the
industrialization process. Initially, the Chaebols exported traditional manufactured products,
and subsequently as outsourced suppliers began to export parts and components of complex
products. Later, the Chaebols focused on exports of consumer and capital goods, to assume the position of world leaders in several markets. Recently, these South Korean conglomerates
internationalised their production via direct investments abroad. The following Table presents the ten largest Chaebol groups from the late 1950s to 2000.
63
Table 2.3 – The 10 largest Chaebol groups in South Korea from late 1950s to 2000
Rank Late 1950s 1 Samsung 2 Samho 3 Gaepung 4 Daehan 5 LG 6 Tongyang 7 Keukdong Hankook 8 Glass 9
10
Donglip
Taechang
Mid-1960's Samsung Samho LG Daehan Gaepung Samyang Ssangyong
1974 Samsung LG Hyundai Hanjin Ssangyong SK Hanhwa
1983 Hyundai Samsung Daewoo LG Ssangyong SK Hanhwa
1990 Hyundai Daewoo Samsung LG Ssangyong Hanjin SK
1995 Hyundai Samsung Daewoo LG SK Ssangyong Hanjin
2000 Hyundai Samsung LG SK Hanjin Lotte Daewoo
Panbon
Dong-Ah Const.
Kukje
Daelim
Hanhwa
Hanhwa
Hwashin
Tongyang
Source: Lim (2010, p. 41).
Daenong
HanilSyn. Textile
Hanjin
Daelim
Hanhwa
Lotte
Kia
Lotte
Kumho
Ssangyong
Several studies pointed out that the establishment and expansion of Chaebol
conglomerates were inspired, directed and supported by the state (Amsden, 1989; Wade,
1992; Chang 1993). Although many measures were implemented to promote South Korean industrial development, such as devaluation of the domestic currency and restrictions on
foreign investment76, the expansion of South Korean conglomerates relied on reinvestment of profits and domestic finance, both public and private. The government directed large volumes
of credit to Chaebols through banking institutions, such as The Korean Development Bank,
The Korea Long-Term Credit Bank and The Korea Export-Import Bank, which were directly or indirectly controlled by the state and provided a predominant share of investment capital in
industry77. As a matter of fact, credit was channelled by the state into specific sectors through numerous policies and institutions to enhance economic performance and encourage the formation of export driver clusters. Complementarily, the expansion of South Korean
conglomerates depended on foreign loans (about 20 times the size of FDI), half of which were public.
Furthermore, in this process, a remarkable characteristic of the South Korean industrial
policy over other developing countries, particularly those in Latin America, relates to the role of the state to discipline, penalise and reward big business according to their performance. In
As stated by Laplane et al. (2013) and, until 1980, an essential characteristic of the economy was restrictions on foreign direct investment inflows, relaxed only in cases of new technologies and managerial expertise transfer. According to Leung-Chuen (2001), from 1965 to 1985, foreign direct investment was less than 2% of gross capital formation. 77 These specialised banks received funds partly from the government, from private deposits and by issuing bonds in international financial markets. 76
64
other words, differently from Latin America, incentives and resources to guide private sector
activities were result-oriented, i.e. contingent upon performance. As highlighted by Amsden (1989), in cases of underperforming, badly managed or bankrupt firms, the state refused to bail them out and allowed better managed ones to acquire them. In addition to important
measures mentioned before, the state awarded good performers with licenses in other industries, leading to further diversification. Moreover, the state propelled high-risk infant industries, rewarding entrants with licenses in more lucrative sectors. Therefore, Kim (1993) pointed out that this development strategy not only resulted in rapid economic growth and
productive diversification of the South Korean industry, but also affected market concentration. Thus, in the late 1970s, 93% of all commodities and 62% of all shipments were produced in monopolistic, duopolistic or oligopolistic market conditions, under which the three largest producers dominated more than 60% market share78. 3.2. Contrasting developmental patterns In contrast to South Korea, Brazil has always been recognised internationally for its
large domestic market. Therefore, with an inward orientation, from the 1950s to the end of the 1970s, Brazil achieved high rates of growth through effective industrial policies that succeeded in a strong industrialisation process, especially in emerging sectors of the national
economy79. This strategy was sustained by the tripod of transnational companies (TNCs), state-owned enterprises and private domestic firms. During, for instance, the Brazilian
Miracle, the investment rate grew from 16.20% of GDP in 1967 to 20.37% in 1973 and a large expansion of GDP marked the economy. In this process, the manufacturing share in GDP reached its historical peak of 23% in 1973.
In this process a strong pro-cyclical movement of investments by state-owned
enterprises (SOEs) marked the pattern of economic growth. Between 1966 and 1973, SOE
investments increased about 19% each year80. The military government had an active industrial policy and created SOEs with the explicit purpose of developing new industries essentially to produce basic industrial inputs and to expand the country’s infrastructure. In the 78
At that time this monopolistic pattern was a central characteristic in the South Korean economy. In Taiwan, for instance, the economy was mostly based on private small and medium enterprises (which had very limited and overall unsophisticated access to credit) and large state-owned firms. In comparison to Latin American countries this market concentration did led to the development of rentier capitalism. 79 See also Furtado (1959), Tavares (1972) and Serra (1982). 80 Data calculated using constant domestic prices. For more details, see Trebat (1983).
65
Brazilian developmental agenda, state-owned enterprises were considered a “shortcut to
industrialization—an expediency forced upon policymakers by the absence of a well-financed
domestic private sector and by Brazil’s reluctance to allow transnational corporations into certain” sectors such as infrastructure (Trebat, 1983, p. 116). Additionally, it was in this
period that the military government (1964-1985) promoted the highest expansion of SOEs. Figure 2.1 shows the number of SOEs by their year of creation.
Figure 2.1 – Number of state-owned enterprises created in each year (1950-1990) 25
Brazilian Miracle
20 15 10
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
1958
1956
1954
1950
0
1952
5
Source: Musacchio & Lazzarini (2014)
In the developmental era, Brazil – and Latin America as a whole – also sought to
deepen its industrialisation by opening the economy to a massive FDI inflow from the United
States, Western Europe, and eventually Japan for the production of manufactured goods81. During Kubitscheck’s government there were, for example, policies that aimed to combine foreign investments in the most dynamic segments of the manufacturing sector (e.g. automobile) with national raw material suppliers. Even in the face of Brazilian trade
protectionism, TNCs established industrial plants due the promising large domestic market to explore. In this way, foreign investments were strongly pro-cyclical and associated with
opportunities opened by the industrialisation process particularly during Kubitschek’s government, the Brazilian economic miracle, and also in the final stages of the industrial
Whereas foreign investors in Latin America traditionally had concentrated on export-oriented projects in mining, oil, and agriculture, post-war FDI emphasised import-substituting investments in advanced manufacturing industries like automobiles, chemicals, machinery, and pharmaceuticals whose output was destined primarily for the relatively large domestic markets in Latin America (Gereffi, 1989). 81
66
structure composition by the time of the Second National Development Plan (II PND) – during the General Geisel’s Government.
However, it is important to note that the Brazilian pattern of industrial development
generated a productive imbalance in favour of TNCs. Despite some successful cases in the
manufacturing industry, such as Embraer in the aircraft industry, the industrial policy in
Brazil did not foster the creation of nationally-controlled industries as in South Korea. Moreover, the industrial bases were built on imported ready-made technologies instead of
ones domestically developed through a gradual process of absorption, adaptation and innovation. Consequently, the economy became gradually more dependent of transnational
companies and state-owned enterprises. During the late 1970s, TNCs were responsible for one third of industrial production. Moreover, more than one half of the production was
concentrated in specific sectors such as electrical equipment, transport equipment, pharmaceutical and chemical products. In terms of categories, TNCs had a very significant
share in the production of durable consumer goods and capital goods, but a smaller presence
in intermediate goods and consumer durables. As with the South Korean Chaebols, these enterprises operated with a high market concentration wherein the 100 largest transnational companies represented two-thirds of total production in Brazil (Gonçalves, 1996).
Another factor that differentiates Brazil from South Korea is the country's relationship
with banks. As mentioned before, the South Korean state facilitated the accumulation of
capital through public banks (socialising banking risks and controlled margins) that provided means to business groups to continually increase their debt levels (with long-term financing
and low interest rates) in order to successively undertake ambitious investment projects in consonance with the five-year development plans. In contrast, in Brazil, banks were never
nationalised and the private banking system was relatively distant to the industrialisation process, limited to short-term financing for working capital without offering long-term and
relevant credits for large investments. Therefore, it was up to the public banking, i.e. BNDES and Banco do Brasil (BB), to provide long-term financing to the development of the national industry. In the case of transnational companies (and large state-owned enterprises),
additional resources of long-term financing were obtained through external loans and financial resources provided by parent company (Coutinho, 1999).
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4. External Debt and Exogenous Shocks In spite of different trends regarding the interaction with the external market, in terms
of productive structure, both Brazil and South Korea achieved the phase of heavy industrialisation. However, during the 1970s, the massive effort to climb the ladder of the
world production in a turbulent economic environment profoundly affected the public accounts. In both Brazil and South Korea, although in different proportions, given the lack of
foreign exchange, the military government had gradually accumulated external debts with
international private banks to finance the current account deficit and maintain the booming economic growth. This excessive external financing increased economic vulnerability and
exposed these countries to external shocks. However, South Korea was less affected, as its
path of “self-reliance” and import substitution industrialisation relatively made it less
insolvent in terms of external debt-exports ratio, allowing a leeway in its economy (Maddison, 1985; Singh, 1985).
The two oil price shocks in 1973 and 1979, and the Volcker interest rate hikes in 1979
had huge deleterious effects in both economies. The former affected the trade balance of oil dependent developing countries while the latter triggered the surge of international interest
rates that increased the debt burden of emerging countries. For instance, the Brazilian external
debt in real dollars rose sharply from US$ 14.8 billion in 1973 to US$ 55.8 billion in 197982. At the same time, the net current account deficit increased from US$ 2.0 billion (2.48% of the
GDP) to nearly US$ 11.0 billion (4.79% of the GDP)83. To make matters worse, Brazil's inflation rate peaked dramatically to 77.25% in 197984. In the case of South Korea, adverse
consequences of the economic environment were similar, although of a different magnitude. The external debt in real dollars increased from US$ 4.3 billion in 1973 to U$S 20.3 billion in 1979. Moreover, since South Korea was dependent on imported oil to foster the development
of petrochemicals industries, the increase of oil prices affected negatively not only the
inflation that reached 28.7% in 1980, but also the industrial productive capacity.
Consequently, in 1980, the investment rate in GDP dropped 3.40 percentage points and the country showed a negative economic growth of 1.70%.
Source: Ipeadata. Source: Brazilian Central Bank. 84 Source: Ipeadata. 82 83
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Figure 2.2 – External Debt, total (% GDP) and Total external debt/exports (ratio), 1961 - 2013
60 50
50
40
40
30
30
20
20
10
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013
0
Total external debt/exports (ratio)
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013
Brazil
0
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013
10
5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0
South Korea
5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0
South Korea
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013
60
Brazil
External Debt, total (% GDP)
Source: Elaborated by the author, using data from The Bank of Korea (BOK), Collins & Park (1989), World Bank, Brazilian Central Bank and OECD.
The nail in the coffin of such macroeconomic imbalance was Mexico's default in 1982
that culminated in an abrupt credit crunch for developing countries in the second half of that year. In this context, a recessive economic environment plagued the economies with high
external debt. This problem associated with protectionist policies implemented by developed
countries during the 1980s complicated still further the economic environment for emerging economies. Additionally, a strong economic integration took place between OECD economies under the aegis of financial globalisation. It led to a heavy process of international mergers and acquisitions associated with high direct investment flows by large companies from
69
industrialised nations. In this way, the rise of regional trading blocs and the intensification of intra-industry and intra-firm trade marked the period. In short, the process of greater
interdependence and integration that took place in the 1980s was concentrated within the OECD and a handful of eastern Asian countries, including South Korea (Coutinho, 2000).
The restrictive access to international finance and foreign-exchange constraints began
to obstruct output growth, investment and fiscal revenues. Indeed, Latin American countries were derailed by exogenous shocks mainly because of their high external debt rather than their closed trade regimes (Hughes & Singh, 1991). Moreover, in a strategy of development
based on deficit-financing to keep up growth impetus, the liquidity contraction triggered a fiscal and financial fragility of the state that culminated in a deep disarticulation of the state to provide active policies for national industry (Carneiro, 2002; Belluzzo & Almeida, 2002).
Furthermore, the overall scenario of uncertainty marked by the threat of hyperinflation and disarticulation of the state blocked the private sector from engendering economic recovery.
Unlike South Korea, due to a strategy based on transnational companies and state-owned enterprises, the domestic business sector was unable to centre itself on large private groups
capable of competing internationally (Coutinho, 2000). The glorious decades of the Brazilian developmental era, marked by the highest levels of manufacturing share in GDP and
investment rates, ended with one of the most radical policy shifts in the history of developing economies. It moved away from its state-led ISI policy into a massive process of economic ‘liberalisation’ and de-regulation (Palma, 2005).
South Korea, in contrast, adopted a more pragmatic and progressive neoliberal agenda.
Given the assassination of General Park Chung Hee in 1979 and the debt crisis, in early 1980s, the South Korean economy went through a period of recession and restructuring. However, unlike Brazil, in a much more constructive way, the country implemented measures
to overcome the crisis and strengthen the ambitious growth strategy. Therefore, after this turbulent period, under the government of General Chun Doo Hwan (1980–1987), the economy achieved a rapid recovery. In this process the decisive alliance between the South
Korean government and the Japanese economic system was decisive. On the financial side, as explained by Canuto (1994) and Coutinho (2000), the Japanese banks had a decisive role in face of the US credit crunch giving the necessary means to promote a new dynamic decade.
As described by Iqbal (1988), the US net loans by large US banks declined from US$ 2.3
billion in 1981 to US$ 0.7 billion in 1983, creating a slack taken up by Japanese banks and by alternative instruments such as bonds and notes. From 1981, bonds and notes rose from less 70
than 2% of annual gross medium- and long-term borrowing to around 23% by 1984 (ibid,
147). On the productive side, the country linked its leading industrial sectors to the South Korean production system, enabling the country advance in technological learning and manufacturing upgrading85.
Throughout the 1980s the Korean government introduced additional measures to
enhance industrialisation policies and strengthen the economy’s industrial pillars. The state
did not expose domestic producers to international competition in an ideological fundamentalist neoliberal way, but instead directed and coordinated investment decisions
(‘disciplining’ the capitalist élite) to achieve levels of technology and productive structure to
make them able to compete in external markets. In face of the international economic
recovery led by the American growth after 198386, South Korea and other Asian NICs invested massively in their manufacturing goods exports without a harmful counterpart on
credit levels and inflation as in Latin America. Moreover, the Korean developmental state guided the capital accumulation process in order to overcome the obstacles to peripheral industrialisation.
5. Technological Learning and Industrial Development During the 1980s, while Brazil struggled in the ‘lost decade’, the South Korean
government seeking to embark on a new cycle of expansion encouraged the country’s large Chaebols to establish partnerships with Japanese leading companies. As a bargaining chip, South Korea offered to Japan its capacity to mobilise resources and qualified working force to
produce components and/or assemble electronic products under the original equipment
manufacturer (OEM) agreement. At the same time, Korean enterprises started to acquire complete production units from Japan to accelerate the learning process mainly in the electronics sector (consumer goods, telecommunications, information technology (IT),
memory semiconductors and capital goods). Moreover, Japanese engineers were hired to
transfer manufacturing know-how, essentially new knowledge and techniques, to their South Korean colleagues (Coutinho, 1999).
In this regard, another special peculiarity was the emergence of salaried managers responsible for exploiting the borrowed technology and focus on shop floor management to optimise technology transfer (Amsden, 1989). 86 From 1983 to 1989 the US grew on average 4.43%. In this period, the most expressive GDP growth was in 1984 when the country registered an expansion of 7.26%. GDP growth rate at constant dollars prices. Source: The World Bank. 85
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Despite the neoliberal rhetoric at that time, the state continued determining the
direction and priorities of the development process87. Therefore, the fifth five-year plan (1982–1986) turned to the development of high-tech industries, particularly, IT and electronic industries which received essential support from the state. A strong thrust was given to
electronics, including production of memory chips used in computers, consumer goods, and
telecommunications products. Inspired by the Japanese industrial policy, the Government established Deliberation Councils in order to act as a state instrument to identify and target
industrial opportunities, evaluate process of merging and acquisitions, and approve financing suggestions proposed by lending institutions (Chang, 1994). Furthermore, large Chaebols that
were already present in the electronic consumer goods sector since the 1970s, such as Samsung and Lucky Goldstar, received further incentives to undertake new projects. Additionally, from the mid-1980s, in an effort to lessen the South Korean trade deficit with
Japan, the government strengthened the incentive structure for the automobile industry and capital goods industry sector 88(Coutinho, 2000).
Given the long-term planning of the South Korean economic policy, the sixth five-
year plan (1987-1991) undertook policies to improve competitiveness combined with
measures to enhance the technological capacity of the production system. As stated by Chang (1993), the constant upgrading of the industrial structure based on the development of local
technological capabilities was seen by South Korean policy-makers as the most concrete way of achieving sustained growth and structural change. In this sense, technology acquisition and
licensing contracts were encouraged. Moreover, R&D incentives were expanded in an effort to promote the private sector’s R&D investment. Furthermore, tax credits for corporate
expenditures on human resources development were also implemented (Lee, 2000). Under
clear guidelines, the government sought to encourage the private sector to take initiatives in order to prepare South Korea’s industrial base to reach the world's technological frontier. In a
Schumpeterian perspective, the state provided the necessary means to constitute a dynamic
As argued by Palma (2004), the economic reforms implemented in East Asia were less fundamentalist when compared to Latin America due the distinct economic level of economic fragility during the debt crisis and external political pressure from the US government. 88 In terms of trade policy, during the 1980s, the large US market was the main focus of the South Korean export programme. For this purpose, the government sought to avoid its currency’s overvaluation against the dollar. Moreover, the South Korean government took advantage of its special political relationship with US and expanded the exports. The growth of the US economy pulled Korea’s exports generating a substantial improvement in the trade balance. The surplus of dollars helped to balance the South Korean deficit with Japan. 87
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national innovation system (NIS) for the development and spread of new technologies89. The following Table reveals that these efforts resulted in a drastic jump in terms of innovation activities, principally from 1980 to 1985.
Table 2.4 - Major indicators of innovation activities Total R&D/GNP Private R&D/GNP Governamental R&D/GNP Number of Researchers R&D expediture/researcher (Thousand Won) Researcher/10,000 popular Number of corporate R&D Labs Applied Patents Utility Models Industrial Design Trademark Source: Lee (2000).
1970 0.39 0.09 0.30 5,628
1975 0.44 0.15 0.29 10,275
1980 0.58 0.21 0.37 18,434
1985 1.56 1.17 0.39 41,473
1990 1.88 1.52 0.36 70,503
1995 2.71 2.20 0.51 128,315
1,874 1.80 0 1,846 6,617 4,522 5,124
4,152 2.90 12 2,914 7,290 6,707 9,476
15,325 4.80 54 5,070 8,558 10,075 13,558
27,853 10.10 183 10,587 18,548 18,949 26,069
49,514 16.40 966 25,820 22,654 18,769 46,826
73,574 28.60 2,270 78,499 59,866 29,978 71,852
In this strategy, the alliance with the Japanese economy was decisive. From Japan’s
point of view, the outsourcing of certain products under OEM agreements to countries within the Asian axis represented a crucial strategy. It helped to maintain the Japanese
competitive edge in export markets, especially after the yen overvaluation due to the Plaza accord in the second half of the 1980s. In the South Korean counterpart it was a great
opportunity to assimilate the last stages of the productive process and to develop internally its own technologies. Subsequently, South Korean companies started to develop gradually their
Own Brand Manufacture (OBM), replacing the OEM strategy. For example, while supplying Japan with intermediary inputs such as petrochemical products, paper, steel products, and
non-ferrous metals, South Korea acquired capital goods, especially machinery, from leading Japanese companies and redeveloped them according to its own industrial needs. As a
developing economy, South Korea took advantage of the technological gap with Japan to successfully absorb, assimilate and adapt cutting edge process and products and consequently boost the economy in terms of productivity and GDP growth.
In short, South Korea’s partnership with Japan was fundamental not only for the
recovery of the economy from the debt crisis, but also provided the means to move ahead
enhancing the industrial structure toward the new paradigm of microelectronics90. Through a For a detailed analysis on the dynamic involving technological dynamics, innovation and economic growth, see the first chapter of this thesis. 90 For more details about technological revolutions, see Perez (2002). 89
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strategic export dynamism and industrialisation, South Korean policy makers sought to
maximise the benefits of FDI inflows and technology that they could extract from
transnational corporations, to ensure efforts to strengthen domestic capacity (UNCTAD, 2002). According to Amsden (2009), the development of technological capabilities was the most important factor of differentiation between South Korean developmental trajectory and
the Latin America one. In Latin America, the limited success attained by scientifictechnological development occurred due to the absence of technological learning policies
linked to the expansion of the industrial base and exports promotion. As Fajnzylber (1983)
pointed out, ISI was marked by a ‘frivolous protectionism’, in the sense that it did not protect the domestic industry with the perspective to assimilate and develop cutting-edge technological industries and strengthen competitiveness91.
This situation got worse in face of the external debt crisis of the 1980s that did not
allow Brazil to keep up with the new technologies and the country’s manufacturing industry became delayed compared to other latecomer economies. In contrast, the South Korean state played a central role coordinating the private sector (“disciplining” the capitalist élite), establishing priorities and managing instruments and incentives to establish a dynamic
industrialisation and rapid technological progress. During the debt crisis, unlike Brazil, the
economic policy comprised a strategy to enhance the manufacturing technological upgrading.
Therefore, through a close relationship with Japan in terms of commercial, technological and
financial agreements, the South Korean state strengthened the Chaebols in order to build a competitive electronic complex to become a world leader in terms of brands, technologies endogenously created and large companies with a worldwide presence (Coutinho, 1999).
In broad terms, it is important to emphasise that this pattern of technological assimilation was a common trend in other Asian countries. For example, China has engaged itself in the transformations of global productive structures through a clear orientation of its national development policy aiming not only to compete in various markets, but also to absorb and develop capabilities from the technology transfer of multinational companies operating in the country, in order to create competitive national groups (Nolan, 2001). The Chinese dynamism focused not only on producing cheap manufacturing goods but also on the huge market for the world production of machinery and equipment with high-level technology. The high-performing East Asian countries recognised the imperative of joining the world economy through the promotion of labour-intensive manufactured exports, but clearly did not limit its expansion in this statement. Therefore Asian countries successfully expanded the manufacturing sector in a process of assimilation, incorporation and diffusion of new products and techniques, with a consequent increase in the production and productivity which changed the underdeveloped position in the global GDP share. In this way, it is no mere coincidence that Asia constituted much more technology intensive industry than Latin America. 91
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6. The “fundamentalist” neoliberal shock The abrupt and very painful internal/external macroeconomic adjustment in Brazil –
much larger than suffered by South Korea – opened the way for a radical and widespread change in the economic paradigm of the region and the emergence of the neoliberal agenda92
(Palma, 2003). Both exogenously and endogenously, the neoliberal view spread through the
perception that severe macroeconomic imbalance and the institutional framework of a model based on ISI did not promote internalisation of the changes observed in the external
environment. Authors such as Franco (1998), Bacha & Bonelli (2005), Krueger (1985) and
Balassa (1988) attributed to the ISI model and the strategy based on the infant industry protection the relative prices distortions which, in turn, resulted in low rates of growth,
investment and productivity. According to the neoliberal camp, ISI led to an inefficient allocation of resources and impacted negatively the level of competitiveness of the economy.
Through this interpretation the state-led industrialisation based in the prevailing economic
policy started to be harshly questioned by a new view in the literature known as the "Washington Consensus" or, in the words of Franco (1998), "the new economic model"93.
Therefore, the period which started in the 1980s with neoliberal reforms contrasts with
the preceding decades when economic growth was mainly based on industrial diversification,
with the manufacturing industry playing an important role in the development strategy94. Since the 1980s, the adoption of the neoliberal “fundamentalist” agenda supported by the
World Bank and the International Monetary Fund (IMF) has exposed not only Brazil, but all of the Latin American economies to a doubtful development strategy based on the free-market
doctrine95. In the face of the neoliberal ascendancy, industrial policies and foreign trade interventions were gradually denied. In this sense, policies in favour of more trade and
financial openness were implemented in pursuit of a reduced role of the state in the economy. These guidelines were strongly marked by an extreme move towards trade and financial
liberalisation, market deregulation, attraction of new flows of FDI, privatisation of stateowned enterprises, and withdrawal of selective industrial policies.
Palma (2000, p. 6), states that the rise of the fundamentalist neoliberal thinking in Latin America was mostly a consequence of the substantial economic weaknesses of these economies. Likewise in the 1930s, “an external shock that found Latin America in an extremely vulnerable position not only brought about the need for a very painful internal and external macroeconomic adjustment, but also laid the foundations for a radical and widespread change in economic thinking”. 93 See also Kuczynski & Williamson (2003). 94 See also Hughes & Singh (1991). 95 See, for instance, Frenkel (1992). 92
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The implementation of economic reforms in Brazil began in the late 1980s, after the
onset of reforms in other Latin American countries such as Argentina, Mexico and Chile (Abreu, 2003). The main objective of the reforms was to dismount the ISI apparatus and
establish a market-oriented model. In other words, neoliberalism emerged in Brazil to reverse almost every aspect of the growth strategy previously followed by the country. Thus, it was
taken for granted that the recovery of economic growth would be strictly connected to the
reduction of state intervention. From this perspective, “market deregulation and trade
liberalisation would not only stimulate tradable production but would also significantly increase private investment, while higher interest rates would boost domestic saving and
reverse capital flight” (Palma, 2005, p.18). The recovery of private investments would ultimately lead to an increase in the investment-to-GDP ratio, interrupting the downward trend observed in the 1980s.
The restructuring of production and trade would take an essentially positive character
resulting in significant allocative and in technical efficiency as a result of increased scale of production. Moreover, it would contribute to the resumption of the economic growth
trajectory in a more specialised production structure in line with the country's comparative advantages, allowing the shift of emphasis from domestic to foreign markets as a driver of economic growth (Moreira, 1999). Moreover, the neoliberal view interpreted the weakness of
the domestic industry as a consequence of the protected market and vertical integration of the
productive system, which in turn, would block access to high-quality inputs, impeding domestic industry from adopting large-scale production methods. The industrial policy at that time turned to the adoption of horizontal policies vis-à-vis vertical ones. Furthermore, the
exportability of the economy would increase in face of the specialisation in sectors in which the country has comparative advantages, thus reinforcing the necessity to promote the
development through the market mechanisms. Additionally, it was hoped to have the support
of foreign capital to head a new investment cycle with greater specialisation, modernisation, productivity, technology transfer and international integration.
These propositions have turned to a structural change in the pattern of growth based on
production diversification supported by ISI, with a strong state directing. The model focused on the productive capacity expansion with the protection of the domestic industry was
abandoned in favour of policies for market openness. The domestic industry was exposed to
international competition without any sectoral selectivity. It was expected of the Brazilian industrial sector to produce in terms of price and quality compatible with the world market,
76
enhancing the competitiveness through market mechanisms. The process should not be driven
by demand anymore, particularly by public investment, but based on changes on the supply side and grounded on competition and technological innovation (Barros & Goldstein, 1997).
Although lacking a pragmatic interpretation, the neoliberal view supported by the
World Bank and IMF gradually promulgated the idea that the adoption of the neoliberal agenda would replace positively outdated elements of the “old economic model”. These
interpretations changed the way that economists and policy makers understood the problems faced by peripheral countries and their possible solutions96. Even though distant from a sense of reality, these studies suggested that developing countries which adopted a market led strategy, i.e. liberalisations and great exposure to the free-market forces, achieved high levels of economic growth.
Therefore, the “Structuralist-Kaldorian” way to visualise the problems in the
peripheral countries was left out97. The Kaldorian links running from growth to productivity, related with the presence of underutilised resources during the growth process, have also been ignored, as well as the links between productivity convergence, domestic production linkages
and external balances (Ocampo & Parra, 2006). Policies designed to promote the manufacturing sector lost strength during this period and were virtually abandoned as a result of the then-prevailing maxim that “the best industrial policy is no industrial policy” (Stallings
& Peres, 2000). As pointed out by Palma (2013, p. 3), “what characterises Brazil’s (and the rest of Latin America’s) economic reforms was an attitude of ‘throwing in the towel’ vis-à-vis
the previous state-led import substituting industrialisation strategy (ISI)”98. In this context, the
rentier characteristic of the country’s capitalist élite was reinforced undermining any perspective of sustained economic growth99.
In contrast, as indicated in the vast literature on East Asian industrialisation, the
strategy followed by South Korea (and most East Asian countries) has been remarkably See Williamson (1989). See, Amsden (2001), Lall (2001) and Palma (2004). 98 According to Palma (2004), Latin America moved to “a standardised environment in which the only issue at stake was who would best (and most faithfully) implement the 'new' model”. 99 The term ‘rentier’ is applied in a Keynesian perspective. According to Keynes, the rentier preference for liquidity affects negatively the level of productive investment and employment. In this perspective, for example, the economic dynamic is undermined by rentier forces that operates in a speculative manner and influence the economic policy for its own interests. For that reason, Keynes advocated for 'the euthanasia of the rentier' and the creation of a new kind of capitalist culture of cooperation between private and public authorities (Keynes, 1936). 96 97
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different from trade liberalisation, in the traditional (and “fundamentalist’) sense100. In South Korea, the economic reforms were implemented mainly as a pragmatic mechanism to
strengthen the existing development model (Palma, 2003). It means that, in the same period, South Korea managed to transform its initial catching-up efforts into a dynamic and
sustainable process of capital expansion and development. Rather than a pure and simple adherence to neoliberalism, the Asian experience has been characterised by the maintenance of a strong state control over the socioeconomic transformations and by the pragmatism in the
management of intermediate and instrumental objectives such as the economic internationalisation and administration of the fiscal and monetary policy (Cunha & Acioly,
2009). In this sense, after the 1980s the history in the global development would was very
different from the previous decades, with all gains of economic growth obtained practically
only by the South Korean economy, or in terms of region – vis-à-vis Latin America – by developing Asia101.
7. Brazil falling behind and South Korea moving ahead 7.1. Brazil: FDI flows and the loss of industrial dynamism As aforementioned, after the golden age of the industrialist era, the neoliberal agenda
promulgated by free market prophets in the IMF and World Bank and their faithful apostles – particularly in Latin America – led to a productive restructuring of the Brazilian economy. In
terms of FDI, the massive inflow in the country was prompted by a dramatic process of
privatisation, especially in the second half of the 1990s. Therefore, the amounts of FDI directed to the country were much higher than previous decades mainly due to cross-border
mergers and acquisitions (M&A) involving SOEs. Sales of stated-owned enterprises increased
in the second half of the 1990s, peaking in 1998 at the height of the privatisation process, and remained high in the early 2000s, consolidating the presence of international groups in the
national productive structure102. Moreover, FDI inflows were directed to the consolidation of See, Ocampo & Parra (2006). The booming growth clustered in the 1960s and 1970s were widespread in the developing world during the “golden age”, tended to disappear in the 1980s, except in East Asia, and became somewhat more common in the 1990s, but at levels far below those of the “golden age” (Ocampo & Parra, 2006). 102 During the National Programme of Desestatisation (Plano Nacional de Desestatização – NPD), the sales revenue of federal state-owned enterprises since the creation of PND in 1990 until December 2008, totalled U$S 30.8 billion. This amount, plus the amount of debt transferred to the private sector of around $ 9.2 billion, represented a total result for the NPD in the order of $ 40 billion. With regard to telecommunications, the sales 100
101
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oligopolistic structures on a global scale, the size of which is evidenced by the amount of M&A operations. This profile of FDI flows helps us understand why investment flows
remained high even after the Asian crisis in 1997, the Russian crisis of 1998 and even the
Brazilian crisis that resulted in the devaluation of the Real in 1999 (Sarti & Laplane, 2002). After this period, the data reveals a transformation of the pattern of M&A, i.e. the process was not restricted to the purchase of state-owned enterprises, and thus a representative amount M&A operations involved the private sector between 2003 and 2008 (Carneiro, 2002 ).
US$ billions
Figure 2.3 - Brazil: Foreign Direct Investment, 1990-2008 50 45 40 35 30 25 20 15 10 5 0
FDI
Source: Elaborated by the author, using data from Unctad.
M&A
FDI in the form of M&A involving state-owned enterprises and the private sector
culminated in an increasing foreign participation in the domestic economy structured on the
existing stock of productive capacity, with the aim of directing the production mainly to the domestic and the regional markets. Therefore, especially in the second half of the 1990s, there
occurred an intense change in the ownership structure of the companies. However it did not
trigger a notable expansion of the productive capacity, i.e. greenfield investments, and consequently did not raise the investment rate of the economy. In contrast to previous decades, when investment in new production plants were the main mechanism to reach new markets, the FDI during the 1990s turned to acquisitions of Brazilian enterprises as the main mechanism to access the domestic market.
revenue for the same period was around U$S 29 billion, totalling U$S 31.1 billion when added U$S 2.1 billion of transferred debts. The overall result of privatisations carried out in Brazil from 1990 to 2008 reached US$ 105.8 billion distributed at federal and state levels.
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As noted by Laplane et al. (2001), the increased participation of transnational
corporations in the Brazilian productive structure and foreign trade did not result in significant
structural change in favour to the expansion of the manufacturing sector neither in a positive evolution in terms of international insertion. In addition, Transnational Corporations (TNCs) began to integrate the new global productive paradigm expressed in the concept of global
value chains. Thus, TNC operations began to be fulfilled in a more fragmented value chain
that is geographically dispersed. In this regime, multinational subsidiaries in Brazil operated mostly as buyers of products from other parts of the global value chain to meet domestic and
regional markets. In rare exceptions, these subsidiaries followed the role of global suppliers within this international division of labour (Hiratuka, 2003).
Moreover, it is important to highlight some important changes in the sectoral
composition of FDI flows received by the Brazilian economy after the monetary stabilisation and intensification of neoliberal reforms. Through the comparison of accumulated stocks of FDI until 1995 and until 2000, it is possible to see the depth of changes during the period.
Thus, the data shows practically an inversion of the percentage between manufacturing and
services. Furthermore, unlike 1990 and 1995, between 1996 and 2000, services received 63.96% of FDI, while the industry and primary sectors received 33.71% and 2.33% respectively. These numbers confirm the concentration of FDI flows in non-tradable sectors,
which still require remittance of profits and dividends without generating foreign exchange through exports. Therefore, the boom in FDI flows occurred mainly in the service sector via
privatisations in telecommunications and electricity, as well as the restructuring of the
financial system. Thus, due to the opening of the economy and the privatisation process, there was a fall in the share of industry in FDI vis-à-vis sectors related to public services.
From 2001 to 2003, the net inflow of FDI fell to $ 12.9 billion, largely influenced by
uncertainties regarding the new government and the turbulent international context after 2001. The average share of FDI directed to services declined while that in the primary sector increased. The former fell to 56.5% and the later grew to 7.3%. The manufacturing sector
increased its share to 36.1%, led mainly by the automotive sector. In 2004, with the new wave
of international liquidity and lower domestic economic instability, the FDI inflow reached US$ 20.3 billion, with significant share of 26.4% (US$ 5.3 billion) in the food and beverage
industry. The sectoral analysis of FDI inflows indicates that, in spite of the concentration in services, the primary sector showed a substantial growth impacted by the commodity prices
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boom. The FDI maintained an increasing rate, reaching US$ 21.5 billion in 2005, US$ 22.2 billion in 2006, US$ 33.7 billion in 2007 and US$ 43.9 billion in 2008.
Table 2.5 - Stocks and inflows of foreign direct investment in Brazil, by sector Sector Agriculture , livestock and min. Manufacturing Automobile Chemical Products Food and Beverages Eletric Mat. and Communic. Equip. Services Post and telecommunications Electricity, gas and water Financial Intermediation Sales (retail and wholesale) Total (%) US$ (Millions)
Stocks (%) 1995* 2000* 2.22 2.33 66.93 33.71 11.60 6.17 12.79 5.87 6.78 4.48 1.88 2.11 30.85 63.96 0.96 18.21 0.00 6.91 4.87 11.80 6.72 9.52 100 100 41,696 103,015
Inflows (%) 2001 2002 2003 2004 2005 2006 2007 2008 2009 7.10 3.40 11.53 5.29 10.20 6.13 14.78 29.61 14.70 33.27 40.23 34.92 52.84 29.75 39.33 36.10 31.93 39.17 7.37 9.36 7.48 4.20 4.30 1.29 2.59 2.20 7.11 7.35 8.38 7.10 6.73 3.55 5.10 2.23 2.46 3.62 2.67 9.97 3.17 26.38 9.64 3.33 5.39 5.10 1.78 5.54 2.90 2.53 1.31 1.84 1.46 2.38 1.92 2.46 59.63 56.37 53.55 41.87 60.05 54.54 49.12 38.46 46.13 19.63 22.32 21.77 14.66 8.83 5.47 1.81 2.20 4.82 6.85 8.17 5.03 5.82 7.30 10.49 1.83 2.07 3.19 10.09 6.77 4.69 4.64 6.01 13.46 17.35 8.92 8.30 6.87 7.64 6.30 5.89 12.92 6.57 8.21 5.84 9.09 100 100 100 100 100 100 100 100 100 21,042 18,778 12,902 20,265 21,522 22,231 33,705 43,886 30,444
Source: Elaborated by the author, using data from The Brazilian Central Bank. Note: (*) Stock accumulated.
In short, the strategy adopted by the government to attract FDI flows did not propel the
manufacturing sector or exports in the 1990s due to three main reasons. First, FDI was
directed to non-tradable sectors during the privatisation process, such as public utilities. Second, a large portion of FDI was in the form of mergers and acquisitions, not expanding the
productive capacity. Third, the logic of investment, even in manufacturing sectors, was primarily associated with the aim to explore the potential of the domestic market without
policies to promote internal intersectoral linkages. In the 2000s, except in 2004, the FDI flows
were directed to other industries but not effectively channelled to tradable sectors, specifically manufacturing. Furthermore, during this decade, the FDI focused on the primary sector essentially due to the global commodities prices boom.
7.2.The loss of manufacturing and productive disarticulation Although from the neoliberal rise onwards the average annual growth rate of the world
economy fell from 4.67% (1950-1979) to 3.34% (1980-2010), in Brazil it was still more
drastic. The late 1980s and the whole decade of 1990s were marked by neoliberal reforms that
took form practically eliminating quantitative controls, non-tariff barriers to trade103, reducing 103
According to Carneiro (2002), non-tariff barriers to trade, which many saw as the main protectionist instrument, were completely removed after Annex C (a list of 1,300 products whose imports were forbidden because similar domestic products were available) was abolished.
81
import tariffs104 and denying public policies focused on promoting growth in strategic sectors for the country’s industrial development. This environment, combined with currency appreciation and extremely high interest rates to control inflation resulted in a negative restructuring of the domestic economy in the second half of the 1990s. During this period, to
face the challenges of the new adverse economic environment, companies began to take strict adjustment measures to rationalise their production by replacing local inputs with imported
ones105. Therefore, as argued by Belluzzo & Almeida (2002), there was a “shrinking” of supply chains, which were also affected by “predatory” imports. Thus, industrial companies
began to look for ways to improve their competitiveness by cutting costs, replacing local products with imported inputs and reducing inter-sectoral linkages still under development (Rocha, 2011).
In the face of an adverse economic environment to expand the manufacturing sector,
short cycles of demand were met by imports106. In an economic environment marked by currency overvaluation, as demand expanded, this dynamic was constantly reproduced. From
2002 the commodities boom favoured the economy and it was associated with a better
international context, leading to optimistic expectations about the aggregate demand. In this context, both the levels of investment and the installed capacity showed a rising trend.
However, due to the productive disarticulation legacy and the strategy of economic development strongly dependent on the primary sector, the levels of investment to expand the productive capacity were not sufficient to keep up with demand growth. Moreover, the
massive inflow of capital due to both trade relations with Asian economies and speculative financial transactions resulted in a strong appreciation of the domestic currency. This process
caused a consequent increase in imports of manufactured goods, which rose by 155% at constant prices between 2002 and 2008107.
During the period of “overrated boom”, not even manufacturing activities associated
with commodity extraction and processing were expanded. Moreover, although still relatively 104
The custom tariffs were reduced based on the country’s structure of comparative advantages. Nominal import tariffs were reduced by 55.3% between 1990 and 1994, with the maximum tariff not exceeding 40%. 105 See Rocha (2011), for more information on the imported input coefficients. 106 According to the Brazilian Institute for Geography and Statistics (IBGE), the penetration coefficient for intermediate goods rose from 2.7% in 1990 to 10.5% in 1998. As argued by Laplane & Sarti (2006, p. 276), from a trade balance perspective, this process “turned the surplus in the trade in manufactured goods registered in the first half of the decade into a deficit from 1995 on, clearly indicating that it would be difficult to keep the economy on a growth path. The trade balance was more significantly negative precisely in 1997, when industrial production was growing at the highest rates, reinforcing the interpretation that the increasing imported contents of local products were generating an even more pronounced deficit.” 107 Calculated by the author based on data from FUNCEX (Foreign Trade Study Centre Foundation).
82
diversified, most of the companies operating in Brazil are not closely related to each other and still very concentrated in low-tech segments, expressed by the predominance of resource-
based companies, basic input suppliers and consumer goods producers (Fleury & Fleury,
2009). The absence of a wide manufacturing industry and dense supply chains has limited growth in terms of technological progress and productivity, causing an excessive dependence of exogenous expansions.
Given this aforementioned dynamic, perhaps one of the main results of the
“fundamentalist” process of economic reforms was the undermining of any prospect of rapid
and sustained economic growth. The only achievement of neoliberal policies was to establish an economic dynamic of successive “stop-and-go” cycles derived from a fragile productive
structure. Therefore, from the 1980s onwards, the country’s growth rate collapse was extreme
both in terms of GDP and manufacturing value added growth. The former sharply declined from 6.74% to 2.75%, while the latter slumped from 8.41% to 1.90% in the respective period. In 1980, the share of manufacturing in GDP represented 21.13%, however, in 2010 this number dropped dramatically to 17.96%. Furthermore, data for the Latin American region confirmed this trend. During the period of 1950 to 1979 the region grew on average 5.39%, and from 1980 to 2010 this average rate fell by half, i.e. to 2.73%108.
Figure 2.4 – Brazil: Manufacturing Share in GDP and Value Added by Technology Intensity (%) 100%
40
Manuf. Share in GDP
35 30
GDP (1980-10) = 2.75%
25 20
90%
GDP (1950-79) = 6.74%
18.37
22.03 21.83 21.13
17.89
19.72
17.96
15
60% 50% 40% 20%
5
10% 1950
1960
1970
1980
1990
2000
2010
High Tech
70%
30%
10
0
80%
0%
Medium Tech Low Tech
1970 1975 1980 1985 1990 1995 2000 2005 2010
Source: Elaborated by the author, using data from The Groningen Growth and Development Centre and ECLAC-PADI database. Note: Manufacturing gross value added at constant 2005 national prices (in millions). Classification of manufacturing industries by technology group based on UNIDO (2013). For details, see appendix 2.3. 108
See Appendixes 2.1 and 2.2.
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In contrast, the analysis of the data for South Korea shows a very different
development path. From 1953 to 1979, South Korea registered an average of GDP and manufacturing value added growth of 8.70% and 9.51% respectively. However, after the
neoliberal reforms, the country did not experience such dramatic loss in terms of economic
dynamism. Although from 1994 onwards the economic reforms implemented in the country sought to strengthen liberalising policies initiated in the 1980, its nature was totally different from the huge endeavour seen in Brazil. As pointed out by Palma (2012), economic reforms
in Korea were implemented as pragmatic mechanisms to help lift specific pressing economic
and financial constraints in order to continue and strengthen their existing ambitious industrialisation strategies. Even during the Asian crisis in 1997, in spite of the re-articulation
between state and private sector, the role of the state was central. To overcome the crisis, there was a reorganisation of the corporate structure with processes of mergers and
acquisitions gaining momentum. However, it is important to note that in this process the state
played a central whole to stimulate companies to focus on their core activities. Therefore, the South Korean state remained active either through long-term programmes for the development of high-tech sectors, or ensuring important long-term funding sources through public banks.
Figure 2.5 – South Korea: Manufacturing Share in GDP and Value Added by Technology Intensity (%) 40
GDP (1980-10) = 6.33%
Manuf. Share in GDP
35
30.28
30 25 20
0
1.69 1953
3.34 1960
Medium Tech
50% 40% 30%
7.78
1970
High Tech
80% 60%
17.62
10
90% 70%
23.24
GDP (1950-79) = 8.70%
15
5
35.24
100%
Low Tech
20% 10% 1980
1990
2000
2010
0%
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Source: Elaborated by the author, using data from The Groningen Growth and Development Centre and ECLAC and UNIDO. Note: Manufacturing Gross value added at constant 2005 national prices (in millions). Classification of manufacturing industries by technology group based on UNIDO (2013). For details, see appendix 2.3.
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As shown by Figure 2.5, along the period of 1980 to 2010, the country showed an
average rate of economic growth of 6.33% and the manufacturing sector grew on average at
2.37%. Despite the noticeable slow down in manufacturing growth rate, the manufacturing sector sharply expanded reaching 35.24% of the GDP (in 1980 this number was 17.62%). The
manufacturing sector as an engine of economic growth was also a remarkable characteristic of other Asian economies. From 1980 to 2011, the “first and second-tier” NICs adopted this strategy of economic growth as a common denominator. For instance, in the first-tier NICs, the manufacturing sector increased from 22.52% to 23.10% of the GDP. In a similar trend, the ‘second-tier’ NICs grew from 22.62% in 1980 to 29.14% in 2010109. 7.3.Labour productivity From a Kaldorian perspective there is a positive relationship between the rate of
growth of output in manufacturing and the rate of growth of labour productivity in the
economy. Therefore, the graph bellow (Figure 2.6) illustrates that from 1950 to 1980 Brazil experienced a productivity growth similar to South Korea. Moreover, the data reveals that from 1950 to 1976, Brazil’s labour productivity level was higher than South Korea’s. However, after 1980 the trajectories of these two developing economies diverged. On the one
hand, South Korea (despite 1997) maintaining a strong dynamism reducing its annual growth
rate productivity after 1980 only 0.80 %, i.e. a declining from an average of 5.19% (19501979) to 4.39% (1980-2010). On the other hand, Brazil’s average annual productivity growth rate collapsed to the point of becoming negative until 1993. From 1980 to 2010, despite the widely reported commodities prices boom from 2002 to 2008, the Brazilian labour
productivity growth rate was more than eight times lower than the South Korean one. During the same period, Brazil’s average productivity level was more than twice lower than those of South Korea’s, i.e. US$ 11,760 and US$ 26,997 respectively110.
109
In East Asian countries, the manufacture share in GDP grew at much higher rates than in Brazil (or any other Latin American country) resulting in significant increase in the share of global GDP. More interesting, perhaps, is the fact that in most East Asian economies the share of manufacturing sector in the GDP did not suffer the Latin American slowdown or the reduction like in the developing countries. Furthermore, headed specially by China, India and ASEAN-4 - Malaysia, Thailand, Indonesia, and the Philippines – the Asian axis more than doubled its share in the global GDP. The gains were not higher because controversially China has become the most important participant in many essential markets of these countries and therefore made it harder for them to abandon the industrialisation pattern based on “sub-contracting” and move forward in the direction of industrial development common to NICs – Korea, Taiwan, Hong Kong, and Singapore (Palma, 2005). 110 Labour productivity per person employed in 1990 US$ (converted at Geary Khamis PPPs).
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In terms of productivity “catching-up” with the US, the graph also shows clearly the
dichotomy between Brazil and South Korea. Until 1980 Brazil was ahead of South Korea in the process of “catching-up”. Indeed, from 1950 to 1980 Brazil engendered a strong process
of productivity growth where labour productivity as share of the US labour productivity increased by 11.66 percentage points. In other words, from 18.99% in 1950 this number
jumped to 30.65% in 1980. In a similar trend, for the same period, South Korean productivity grew from 11.86% to 27.52%. However, this productivity trend was drastically reversed after 1980. Thus, while South Korea maintained an upward trend reducing its productivity gap with
the US very rapidly from 27.52% to 65.07% in 2010, Brazil fell behind with productivity level relative to the US declining to 19.56% in 2010. Additionally, it is important to highlight that in terms of regions the South Korean and Brazilian trends were followed similarly by the “first-tier” NICs and Latin America respectively both before as well as after 1980. Figure 2.6 – Labour Productivity and ‘Catching-up’ with the US, 1960-2010 Labour Productivity
50,000
South Korea
Labour Productivity US$ ( PPP - 1990)
40,000
SK LP (1980 - 2010) = 4.39%
35,000 30,000 25,000 SK LP (1950 - 1979) = 5.19%
20,000 15,000
Brazil
10,000 5,000 0
1950
1960
BR LP (1950 - 1979) = 3.32%
1970
1980
BR LP (1980 - 2010) = 0.52% 1990
2000
NICs 1
70%
2010
Labour Productivity as Share of US LP
45,000
‘Catching-up’ with the US
80%
60%
South Korea
50% 40%
LA
30%
Brazil
20%
NICs 2
10% 0%
1950
1960
1970
1980
1990
2000
2010
Source: Elaborated by the author adapted from Palma (2011). Data from The Groningen Growth and Development Centre. Note: Labour productivity per person employed in 1990 US$ (converted at Geary Khamis PPPs).
86
7.4.Manufacturing Share and Income ‘Catching-up’ The Figure below illustrates empirically the dichotomy between Brazil and South
Korea in terms of sectoral composition and economic development. During the whole period (1953-2010), South Korea gradually increased the share of manufacturing in the GDP and
reduced the income gap with the US. Therefore, from 1953 to 2010, the manufacturing share
in GDP relative to US grew from 0.13 to 3.21111. Moreover, except for some periods such as 1995-2000 when the country was affected by the Asian Crisis (1997), the income per capita
showed a constant increase in relative terms to the US. From 8.93% of the US income per capita in 1953, in 1980 and 2010 this variable reached 22.15% and 70.25% respectively.
Figure 2.7 - Share of manufacturing in GDP and relative income gap with the US, 19502010
% Manuf. South Korea in GDP
30
00
25 20 80
15
85
90
23
05
95
5
0%
53
65 60 55
20%
70
21
65
20 19
55
50
80
05 00
85 95 2010 90
17
70
75
60
22
18
75
10
0
24
2010
35
Brazil: Regressive Trajectory
25
% Manuf. Brazil in GDP
40
South Korea: Progressive Trajectory
16 40%
60%
Gap GDP Per Capitawith the US
80%
15
0%
10%
20%
30%
Gap GDP Per Capita with the US
40%
Source: Elaborated by the author, using data from The Groningen Growth and Development Centre. Note: GDP per capita in 1990 US$ (converted at Geary Khamis PPPs) and Manufacturing Gross value added at constant 2005 national prices (in millions).
111
Manufacturing share in GDP relative to US is calculated as:
(
(
)
)
87
In contrast to South Korea which moved ahead even after the advent of neoliberal
reforms, Brazil drastically fell behind (in a cyclical fashion) in terms of manufacturing share
in the GDP and income gap reduction with the US. From 1950 to 1980, the Brazilian economy showed a high volatility in terms of degree of industrialisation and income gap
reduction with the US, but with a substantial improvement of these indicators. In 1950, the
Brazilian income per capita (in PPP) was 17.48% of the US income, and manufacturing
corresponded to 18.37% of GDP. In 1980, the Brazilian income increased to 27.96% of the US income, and, during the same period, the manufacturing sector reached 21.13% of GDP.
However, after 1980, this overall trend changed dramatically. As showed by the Figure above, the Brazilian economy embarked on a regressive trajectory both in terms of manufacturing expansion in GDP and income gap reduction with the US economy. The most dramatic period
was during 1980 to 1995 when the Brazilian economy regressed 15 years both in terms of
income per capita catching-up. From 2005 to 2010, this relative loss was reversed but mostly by a boom in commodities, finance, and household credit112. Taking into account the “Kaldorian-Structuralist” perspective, it is not by chance that the persistent difficulty of overcoming the middle-income barrier appears to be closely related to the manufacturing sector loss in the GDP.
7.5.Export-trajectories: Two historical distinct patterns From 1950 to 1980, Brazil and South Korea had the rise of manufacturing in GDP as a
common denominator in the strategy of economic growth. In South Korea this pattern of
development was followed by a strong increase of exports in GDP. From the 1960s until 1987, both the share of manufacturing and exports in GDP grew practically constantly in a
convergent pattern (see Figure 2.8). This trend was also followed by a significant increase of
manufacturing exports in GDP that represented more than 75% of total exports in the GDP113. By contrast, Brazil pursued a development path based on its large domestic market.
It is important to emphasise that the commodity prices boom started in 2002, while the finance and household credit boomed from 2003 onwards, during the Lula’s government. See, for instance, Gottschalk & Prates (2006). 113 It is important to emphasise that the outward-orientation was a common trend in economic policy principally in East Asian NICs. Therefore, the development mainspring underpinned over the outward orientation coordinated by the State which directed the necessary private investment to sustain the export driver in order to generate foreign exchange via manufactured exports. During this initial phase of export expansion, the rapid growth of the East Asian NICs – Korea, Taiwan, Hong Kong, and Singapore – was founded on light, labourintensive industries like textiles, garments and electronic equipment. In subsequent phases, however, the East Asian NICs achieved success in much heavier industries like steel, petrochemicals, shipbuilding, vehicle manufacture and computers that were less well suited to their original factor endowments (Gereffi, 1989). 112
88
Therefore, different to Korea, Brazil followed a resilient performance of the GDP export-
share. In numbers, while South Korea achieved a share of 23.13% of manufacturing exports in the GDP in 1980, Brazil by contrast had its exports of manufactured goods during the whole developmental era under 5% of GDP. Curiously, due to the inward-orientation, the constant
increase of the manufacturing sector performed inversely to exports share in GDP. In other words, despite a strong growth performance in Brazil, the share of manufacturing in GDP
took place at the expense of the GDP export-share, i.e. in a divergent pattern (see Figure 2.8)114.
Figure 2.8 - Share of Manufacturing and Exports in GDP (%) (1960-2010) South Korea: Convergent Pattern
60
25
50
20
40
15
30
10
20
5
10 0
Brazil: Divergent Pattern
1960
1970
1980
Export/GDP
Manuf. Exp/ GDP
1990
2000
Manufacturing
2010
0
1950
1960
1970
Export/GDP
1980
Manuf. Exp/ GDP
1990
2000
Manufacturing
2010
Source: Elaborated by the author, using data from The Bank of Korea (BOK), World Bank, The Conference Board and Groningen Growth and Development Centre. Note: Export/GDP = Gross exports/GDP and Manufacturing = manufacturing value added/GDP. Data are in constant 2005 US dollars.
In terms of exports, despite the rapid process of industrialisation, Brazil did not
overcome the historical dependence of its Ricardian comparative advantages, i.e. natural
resource endowments. Over the years, Brazilian agriculture and mining sectors were not only important to supply the domestic market but also a central source of foreign exchange. In theoretical terms, it is important to highlight that Raúl Prebisch and his intellectual heirs at the ECLAC had during the 1950s and 1960s an economic thinking characterised by a deep Palma (2005) identifies this phenomenon not only as a strategy characterised by a strong anti-export bias, but also as a consequence of weak demand for Latin American primary commodities in OECD markets since the Korean War. 114
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criticism regarding the growth-enhancing capacity of unprocessed primary commodity exports in “peripheral” countries. However, this strong developmental thinking – which was very influential in Latin America at that time – propelled particularly the diversification of the
productive structure rather also exports. Additionally to a negligent export policy, an
important external factor also affected this trade pattern. The massive inflow of foreign capital contributed to finance the current deficit and consequently eased the pressure to increase the
share of manufacturing products in exports. During the 1970s the Brazilian government tried to work around the situation through stimulus to manufactured exports, however, this in turn
was highly restricted due the turbulent international environment of the decade. In short, due internal and external factors, the Brazilian economic policy was substantially ineffective in
increasing exports of manufactured goods when compared to South Korea (and other East Asian countries)115.
South Korea, in turn, instead of accepting its traditional Ricardian comparative
advantages (essentially associated with cheap labour), sought to manage the industrial policy to create an institutional environment that allowed the country to follow the Japanese example of industrialisation and develop a pattern of production and export upgrading over the
decades116. As pointed out by Palma (2005), the extraordinary success of the East Asian economies was based on external and internal factors. On the external front, following a “flying geese” paradigm led by Japan, South Korea increased the exports to the OECD
markets, especially the USA, for manufactured goods within a process of productive regionalisation. On the internal one, South Korea built a structure around a skilled labour
force, property rights, political settlement and institutional capability that allowed the country to produce competitive manufactured goods. In Kaldorian terms, this dynamic based on the
production and exports of manufacturing products imbued special growth-enhancing properties that triggered a process of cumulative causation not shared by other sectors and
consequently strengthened the foundations for sustained growth. Not by chance, from the 1950s to 1970s, the South Korean (and East Asian) economy climbed the ladder to establish the pillars for long-term economic growth.
In ECLAC’s economic thinking, a key structural economic characteristic of peripheral economies refers to the deterioration in their terms of trade over time due different income – elasticity of demand – as “dynamic disparity of demand”. Therefore, according to ECLAC’s point of view, ISI model was a central measure for diversification of the productive industry and expansion of exports based on a dynamic manufacturing sector. For a detailed explanation of the Latin American Structuralism approach, see the first chapter of this Thesis. 116 About the Japanese leadership on the Asian pattern of development see Arrighi et al. (1993), Akyus (1996), UNCTAD (1996), Ozawa (1991, 1995, 2001) and Palma (2005). 115
90
Nevertheless, the South Korean economy also faced turbulences in trade. In the late
1980s to early 1990s, some of its most important manufactured products, particularly microelectronics, began to experience a persistent drop in prices. It was essentially a result of rapid standardisation (or “commoditisation”) and an increased supply of its manufactured products in the global market. In an attempt to reverse this situation the corporate sector
sought to expand the market share, increasing investment in new productive capacity. This led to overinvestment, which in turn exacerbated the global excess supply in international markets
and further downward pressure on prices117. The declining manufacturing profitability resulted in a strong change in the finance structure of investment118. From an industrial
structure characterised by the retention of profits, the economy shifted to a situation characterised by domestic and foreign debt. Therefore, this process caused an increase in the
microelectronics sectoral deficit that rose from around 5% in 1987 to almost 20% of GNP in 1996 (Palma, 2013). In late 1997, South Korea experienced a severe economic downturn
derived from the so-called Asian Crisis. However, despite important ideological changes that engendered neoliberal reforms, the state maintained an active role, either through long-term policies for the development of high-tech sectors and exports, or by ensuring important longterm funding sources through public banks.
Brazil, by contrast, after the ‘lost decade’ embarked in the neoliberal agenda under the
illusion that the market forces per se would create the necessary conditions to the consolidation of the productive structure and exports promotion. As proved by the facts, neither the manufacturing share expanded in the GDP nor exports of manufactured products
increased. Moreover, as a result of an extremely weakened production structure resulting from
over a decade of strongly market-oriented policies, production and exports of primary
products became the engine of Brazil’s growth. In 2002, demand for Brazilian commodities began to rise more intensely because of the growth of the Asian economies, particularly that
117
Palma (2013) suggests that the collapse of exports in microelectronics was significantly explained by the Taiwanese memory-chips exports that increased massively during the period. For instance, due the excess of supply in the global market, the price of memory chips fell approximately 80% in 1996 alone. In this process, South Korea was strongly affected since a significant amount of its exports consisted in this type of product. 118 Chang et al. (1998), also points out that the political and economic shift of the period contributed to worsen the profitability of the South Korean microelectronics sector. The rise of the neoliberal agenda weakened domestic sectoral policies and affected the transparency between the State and corporations. The manufacturing sector became increasingly exposed to state corruption and vested interests. As argued by Chang “ large sums of money did flow from big business to politicians and top bureaucrats (…) there was a fundamental transformation in the state–business relationship in Korea, which meant that the major manufacturing sectors became less insulated from corrupt political exchanges than they had been previously” (Chang et al. 1998, p. 741).
91
of China119. This demand for natural resources and raw materials has pushed up commodities prices in the world market, benefiting the Brazilian economy. The boom of commodity prices
pulled the Brazilian exports, adding substantial dynamism to the economy but without a
change in the industrial structure to expand the manufacturing sector and increase the export of manufactured products. Without developmental policies, the current export pattern has showed little capacity to generate growth-sustaining processes of cumulative causation.
Therefore, it is not by chance that the Brazilian economy has been over decades limited to a middle-income level. The current productive structure limited the growth-enhancing
characteristics of the manufacturing sector, such as externalities and spillover effects that may help set in motion processes of cumulative causation that take advantage of dynamic economies of scale, increasing returns, etc (Palma, 2012).
Furthermore, this productivity and trade relations resemble in some ways the centre-
periphery relationship outlined by Prebisch, where Brazil (as well as Latin American countries as a whole – with the exception of Mexico and the Central American countries)
exports commodities and raw materials to China, and imports manufactured goods from Asian countries. In this way, Latin America has assumed the role of the periphery, exporting natural resources and raw materials, while Asian Countries have gradually assumed the core or
central position, exporting manufactured goods to the region. Brazil’s development has become strongly dependent on China’s growth and development. Although these structural
bottlenecks had been widely discussed in the Latin America structuralist theory and in the
Kaldorian approach, their contributions seemed to have relatively low influence on economic policy after the neoliberal rise. 8. Concluding remarks Taking into account the role of the state in guiding the development path, this chapter
sought to compare the industrial development in Brazil and South Korea and identify factors
(endogenous and exogenous) that determined different routes of economic dynamism in these economies. Therefore, the chapter showed that a successful process of industrialisation Between 1990s and 2000s, the Chinese economy practically doubled its number both in the GDP growth and productivity, highlighting its dynamism over the rest of the world. A similar trend was followed by India and SEAN-4 which, together with NICs, showed their capabilities to expand and conquer other markets. In both groups, their performance in terms of average of growth rates presented a plateau in 1990s and 2000s with a peak in 2010. 119
92
required an active developmental state to expand the manufacturing sector. Both in Brazil and South Korea during the industrialisation era, policies implemented involved controls over
interest rates, credit allocation, and a set of tax and tariff measures to provide protection to the
nascent industry. Moreover, particularly in South Korea, policies for technology acquisition, incentives to activities of R&D and the promotion of cartels for specific purposes such as standardisation, specialisation and exports were also a central characteristic.
Despite general similarities, while in South Korea the domestic private capital,
represented by the Chaebols, played a decisive role in the evolution and development of
Korean industry, while in Brazil economic growth and investments were driven by stateowned enterprises and multinational companies established in the country during the 1950s
and 1960s. Moreover, while South Korea pursued a process of industrialisation with a clear outward orientation, Brazil, due its large domestic market and restricted access to OECD
markets, followed a pattern of industrial growth with an inward orientation. Moreover, despite
different trends regarding the interaction with the external market, in terms of productive structure both Brazil and South Korea achieved the phase of heavy industrialisation in the late 1970s.
Conversely, this massive effort to climb the ladder of world production in a turbulent
economic environment profoundly affected public accounts. In both economies, although in
different magnitudes, given the lack of foreign exchange, the military government gradually accumulated external debts with international private banks to finance the current account
deficit and maintain the booming economic growth. This excessive external financing raised economic vulnerability and exposed these countries to external crises. Thus, the two oil price
shocks in 1973 and 1979, and the Volcker interest rate hikes in 1979 drastically affected both countries. With the outbreak of the debt crisis in 1982, the Brazilian economy, which was vulnerable due to its large current account deficit and external debt, faced an abrupt cut-off in
bank financing that plunged the country into a serious crisis and caused a deep disarticulation
of the state in providing active policies for national industry. Consequently, during the 1980s, economic growth was seriously retarded giving rise to the commonly used term “the lost
decade”. In contrast, South Korea dealt with the crisis in a much less traumatic way since its strategy of industrialisation was relatively less dependent on foreign debt and Japanese banks “recycled” the country’s liabilities. Therefore, South Korea not only recovered rapidly from
the debt crisis, but also strengthened the manufacturing sector and the production of cutting-
edge technological products. By contrast, Brazil struggled in the debt crisis of the 1980s that 93
did not allow the country to keep up with new technologies and consequently the manufacturing industry became delayed compared to Asian latecomer economies.
From the 1980s, Brazil embarked on a “fundamentalist” neoliberal agenda which
sought to reverse almost every aspect of the growth strategy previously followed by the country. The neoliberal policies were strongly marked by an extreme move towards trade and
financial liberalisation, market deregulation, attraction of new flows of FDI, privatisation of state-owned enterprises and the withdrawal of selective industrial policies. In contrast, the neoliberal polices implemented in South Koreas were remarkably different from the Brazilian
neoliberal fundamentalist agenda. In South Korea, the economic reforms were much more pragmatic, seeking to transform the initial catching-up efforts into a dynamic and sustainable
process of capital expansion and development. Even after the 1980s, the South Korean experience was characterised by the maintenance of a strong state control over the
socioeconomic transformations and by the pragmatism in the management of intermediate and
instrumental objectives such as the economic internationalisation and administration of the fiscal and monetary policy.
In Brazil, the main result of the “fundamentalist” process of economic reforms was to
reinforce the rentier instincts of the country’s capitalist élites and undermine any perspective
of sustained economic growth. Therefore, the neoliberal agenda established an economic dynamic of successive “stop-and-go” cycles derived from a fragile productive structure and
lack of effective demand. From the 1980s onwards, the country’s growth rate collapsed both
in terms of GDP and manufacturing value added growth. Moreover from an intra-industry perspective, the composition of the manufacturing sector stagnated over the decades. In
contrast, South Korea presented a distinct development path. Thus, after the neoliberal reforms, the country did not experienced such dramatic loss in terms of economic dynamism. The economy grew on average by more than 6% per year and the manufacturing sector
expanded sharply. Furthermore, in terms of intra-industry technology composition, the share of high-tech industries rose significantly, reaching around 61% of the manufacturing share.
The deleterious effects of premature de-industrialisation in Brazil vis-à-vis South
Korea’s thriving manufacturing expansion clearly impacted the evolution of labour productivity and catching-up. Analysing the data there is little doubt that the remarkable
neglect of manufacturing since economic reforms lies at the heart of country’s productivity stagnation. In contrast to the period from 1950 to 1980 when in both countries manufacturing
94
and productivity expanded considerably, from 1980 to 2010, due to the manufacturing
collapse, Brazilian productivity practically stagnated. Even during the commodities prices boom from 2002 to 2008, the Brazilian economy productivity growth was extremely poor.
Brazilian average productivity growth was more than eight times lower than that of South Korean. Moreover, during the same period, Brazil’s average productivity level was more than
two times lower than those of South Korea’s. Thus, while South Korea maintained an upward
trend reducing its productivity gap with the US very rapidly, Brazil embarked on a noxious trajectory.
In terms of income catching-up, while South Korea moved ahead after the advent of
neoliberal reforms, Brazil drastically fell behind (in a cyclical fashion) in terms of manufacturing share in the GDP and income gap reduction with the US. The most dramatic period was during 1980 to 1995 when the Brazilian economy regressed 15 years both in terms
of income per capita catching-up. Taking into account the “Kaldorian-Structuralist” approach, it is not by chance, that the persistent difficulty to overcome the middle-income trap appears
to be closely related to the manufacturing sector loss in the GDP. Analysing the exports trajectories the dichotomy between these economies are also very clear. On the one hand,
South Korea pursued an outward strategy of economic growth expanding exports of manufacturing products, particularly high-tech products, taking into account the special
growth-enhancing properties of this sector. In contrast, Brazil was always historically dependent on its Ricardian comparative advantages, i.e. natural resource endowments. During
the developmental era, all efforts made to overcome this structural dependence were very resilient and after the neoliberal rise practically inexistent. Therefore, in KaldorianStructuralist terms, the Brazilian trade composition based on exports of primary products
showed little capacity to generate growth-sustaining processes of cumulative causation and consequently mitigated any possibility of dynamic economic growth.
95
Appendix 2.1 - Brazil’s Macroeconomic Indicators, 1950-2013 (%) Year
GDP Growth
Export/ GDP
Import/ GDP
1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970
6.80 4.90 7.30 4.70 7.80 8.80 2.90 7.70 10.80 9.80 9.40 8.60 6.60 0.60 3.40 2.40 6.70 4.20 9.80 9.50 10.40
9.20 9.60 7.10 6.60 6.70 7.60 6.80 5.60 5.70 5.90 5.30 5.80 6.70 8.60 6.50 7.60 6.50 5.70 6.00 6.70 7.00
7.60 11.30 9.90 5.60 6.80 6.80 5.80 6.20 6.10 6.60 6.40 6.20 8.00 9.00 5.60 5.40 5.80 5.80 6.70 6.70 7.40
Manuf. Exp/ GDP 0.19 0.18 0.36 0.57 0.46 0.53 0.45 0.60 0.86
GFCF
GFCF/ GDP
External Debt/GDP
Public
Private
12.79 15.45 14.82 15.06 15.76 13.49 14.46 15.04 16.98 17.99 15.72 13.11 15.51 17.04 14.99 14.71 15.92 16.20 18.68 19.11 18.83
17.69 15.04 15.20 16.79 13.21 11.00 11.99 12.40 14.66
34.17 23.60 23.33 22.88 24.95 24.26 20.89 30.75 32.71 28.64 35.89 44.20 39.27 31.68 33.69 46.18 38.03 40.74 33.97 38.04 38.59
65.83 76.40 76.67 77.12 75.05 75.74 79.11 69.25 67.29 71.36 64.11 55.80 60.73 68.32 66.31 53.82 61.97 59.26 66.03 61.96 61.41
Primary Sector 14.05 13.35 13.19 12.78 12.36 12.34 11.71 11.96 11.51 11.71 11.24 10.89 10.85 10.79 10.68 11.79 9.75 9.87 9.53 9.08 8.61
Sectoral Composition
Manuf.
Construction
Services
18.37 18.10 17.41 18.32 18.08 18.60 18.92 18.74 20.43 21.98 22.03 22.08 22.64 21.86 22.25 20.41 21.25 20.32 21.13 21.32 21.83
5.82 5.70 4.92 4.57 4.63 4.92 5.36 5.58 5.80 5.92 5.86 5.64 5.95 5.92 6.14 6.13 6.24 6.17 6.30 6.28 6.39
61.76 62.85 64.48 64.32 64.92 64.14 64.01 63.71 62.26 60.38 60.88 61.38 60.56 61.42 60.93 61.67 62.75 63.64 63.04 63.32 63.17
Manuf. Growth 5.59 5.38 9.33 9.48 10.93 5.53 5.58 16.71 12.84 10.60 11.10 8.19 -0.49 5.29 -4.70 11.67 2.18 14.20 11.19 11.86
(Continue) 96
Year
GDP Growth
Export/ GDP
Import/ GDP
1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
11.34 11.94 13.97 8.15 5.17 10.26 4.93 4.97 6.76 9.23 -4.25 0.83 -2.93 5.40 7.85 7.49 3.53 -0.06 3.16 -4.35 1.03
6.50 7.30 7.80 7.70 7.20 7.00 7.20 6.70 7.20 9.00 9.60 7.90 12.20 15.00 12.90 9.20 9.80 11.70 8.90 8.30 8.30
8.20 8.90 9.00 13.30 11.00 9.40 7.90 7.90 9.30 11.20 10.00 8.60 9.70 8.80 7.50 6.60 6.40 6.10 5.50 8.30 8.30
Manuf. Exp/ GDP 0.90 1.28 1.53 1.83 1.77 1.53 1.73 2.10 2.55 3.19 3.46 2.74 4.24 5.34 5.03 4.00 4.42 5.32 4.35 3.53 4.26
GFCF/ GDP
External Debt/GDP
19.91 20.33 20.37 21.85 23.33 22.42 21.35 22.27 23.36 23.56 24.31 22.99 19.93 18.90 18.01 20.01 23.17 24.32 26.86 20.66 18.11
16.85 19.51 17.67 18.15 19.34 20.88 21.41 25.94 24.97 27.03 28.61 31.52 49.48 53.82 49.82 43.13 42.92 37.13 27.77 26.30 30.54
GFCF
Public 32.86 37.18 28.43 35.68 36.06 47.17 44.50 37.94 29.68 28.01 30.14 30.48 30.32 27.12 29.29 27.65 27.20 26.62 20.62 25.23 24.01
Private 67.14 62.82 71.57 64.32 63.94 52.83 55.50 62.06 70.32 71.99 69.86 69.52 69.68 72.88 70.71 72.35 72.80 73.38 79.38 74.77 75.99
Primary Sector 8.45 7.85 7.02 6.85 6.77 6.27 6.44 5.85 5.68 5.87 6.40 6.48 6.85 7.10 7.27 6.46 6.93 6.97 7.03 7.22 7.37
Sectoral Composition
Manuf. 21.97 22.45 23.00 22.95 22.25 22.52 21.77 21.14 20.66 21.13 19.51 19.48 18.82 18.93 19.07 19.67 19.47 18.79 18.88 17.89 17.45
Construction 6.46 6.48 6.52 6.77 6.98 7.20 7.68 7.83 8.06 8.35 8.08 7.89 6.92 6.48 6.39 6.98 6.89 6.67 6.72 6.35 6.12
Services 63.12 63.23 63.47 63.42 64.00 64.02 64.11 65.18 65.60 64.65 66.01 66.15 67.41 67.49 67.27 66.89 66.70 67.57 67.38 68.54 69.07
Manuf. Growth 11.87 13.96 16.62 7.74 3.81 12.12 2.28 6.11 6.86 9.11 -10.38 -0.18 -5.85 6.16 8.34 11.30 0.95 -3.41 2.88 -9.46 -2.36
(Continue)
97
Year
GDP Growth
Export/ GDP
Import/ GDP
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
-0.54 4.92 5.85 4.22 4.09 3.39 0.36 0.49 4.38 1.28 3.08 1.22 5.66 3.15 4.00 6.01 5.02 -0.23 7.57 3.92 1.76 2.74
10.90 10.50 9.50 7.30 6.60 6.80 6.90 9.40 10.00 12.20 14.10 15.00 16.40 15.10 14.40 13.40 13.70 11.00 10.87 11.89 12.59 12.55
8.40 9.10 9.20 8.80 8.40 9.00 8.90 10.80 11.70 13.50 12.60 12.10 12.50 11.50 11.50 11.80 13.50 11.10 11.90 12.62 14.03 15.04
Manuf. Exp/ GDP 5.22 5.18 4.39 3.24 3.06 3.26 3.31 4.42 5.00 5.72 6.31 6.87 7.77 7.12 6.43 5.62 5.37 3.73 3.49 3.53 3.78 3.92
GFCF/ GDP
External Debt/GDP
18.42 19.28 20.75 20.54 18.65 19.13 18.55 17.01 18.33 18.44 17.96 16.67 17.38 17.22 17.26 18.07 19.49 19.21 20.59 20.64 20.21 20.53
35.10 33.91 27.31 20.67 21.07 22.56 27.87 40.12 35.92 40.38 44.74 42.03 32.88 21.06 18.01 17.23 15.54 16.62 15.92 15.46 18.27 20.32
GFCF
Public 27.02 24.30 21.61 18.53 19.98 18.33 20.95 14.24 13.88 15.22 18.34 15.32 14.94 15.09 16.93 15.61 18.14 21.05 22.24 18.50 20.22 20.75
Private 72.98 75.70 78.39 81.47 80.02 81.67 79.05 85.76 86.12 84.78 81.66 84.68 85.06 84.91 83.07 84.39 81.86 78.95 77.76 81.50 79.78 79.25
Primary Sector 7.42 7.78 7.52 7.68 7.82 7.70 7.92 8.12 8.09 8.36 8.78 9.22 8.98 8.98 9.06 8.94 9.06 8.82 8.92 9.03 -
Sectoral Composition
Manuf. 17.47 17.15 17.92 18.52 18.29 18.58 18.51 18.46 19.72 19.50 19.31 19.36 20.25 19.88 19.44 19.48 18.84 17.49 17.96 17.55 -
Construction 6.04 5.81 5.85 6.05 6.19 6.48 6.52 6.27 6.10 5.88 5.60 5.39 5.44 5.38 5.43 5.38 5.58 5.56 5.79 5.86 -
Services 69.08 69.26 68.71 67.75 67.70 67.24 67.05 67.14 66.09 66.26 66.32 66.03 65.32 65.76 66.08 66.21 66.51 68.13 67.33 67.56 -
Manuf. Growth -0.56 -3.65 8.29 6.83 -0.32 5.25 0.14 0.60 12.03 0.41 1.88 0.63 10.45 1.03 1.50 6.03 0.57 -7.51 10.10 0.10 -
Source: Elaborated by the author, using data from The Brazilian Central Bank, Brazilian Institute of Geography and Statistics (IBGE), Ipeadata, World Bank – World Development Indicators, The Conference Board and Groningen Growth and Development Centre and UNCTAD. Note: Data for GDP Growth and Gross Fixed Capital Formation (GFCF) in current Prices. Sectoral composition calculated from data at constant 2005 national prices (in millions).
98
Appendix 2.2 - South Korea’s Macroeconomic Indicators, 1950-2013 (%) Year 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970
GDP Growth
Export/ GDP
Import/ GDP
-
3 5 5 5 6 8 10 11 12 13 13
12.60 14.94 16.50 15.70 13.35 15.92 20.13 21.92 25.30 25.15 22.53
7.20 5.80 0.70 9.20 6.50 5.40 2.30 6.90 3.80 9.20 9.50 7.20 12.00 9.10 13.20 14.50 10.00
Manuf. Exp/ GDP 0.37 1.01 1.64 3.40 3.99 4.55 5.67 6.34 6.80
GFCF
GFCF/ GDP
External Debt/GDP
Public
Private
14.70 11.00 11.70 8.30 14.30 11.50 10.10 9.70 11.70 13.10 17.80 14.70 14.00 20.60 21.10 25.90 28.80 25.70
3.52 3.24 4.06 5.27 6.83 10.30 13.72 20.13 24.08 23.86
23.73
76.27
Primary Sector 49.07 41.69 46.88 49.15 46.39 42.22 35.85 38.17 41.09 37.90 43.66 48.11 41.20 37.51 33.49 29.72 30.05 29.36
Sectoral Composition
Manuf.
Construction
Services
8.41 10.84 10.65 10.75 10.24 11.51 12.76 12.30 12.09 13.17 13.84 14.91 16.95 17.39 17.64 18.96 19.35 20.19
-
40.74 45.30 39.95 37.70 40.54 43.68 48.64 46.90 44.26 46.29 40.07 34.61 39.01 42.07 45.68 47.33 45.85 45.72
1.78 2.17 2.52 2.41 2.84 2.59 2.75 2.63 2.56 2.65 2.43 2.37 2.84 3.02 3.19 3.99 4.75 4.73
Manuf. Growth 16.01 18.48 15.44 3.69 5.68 7.80 5.04 1.01 8.29 9.62 0.64 13.40 7.13 14.90 15.32 8.85 10.24
(Continue) 99
Year
GDP Growth
Export/ GDP
Import/ GDP
1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
10.50 7.20 14.80 9.50 7.90 13.10 12.30 10.80 8.60 -1.70 7.20 8.30 13.20 10.40 7.70 11.20 12.50 11.90 7.00 9.80 10.40
14 18 27 25 25 28 29 27 25 30 32 31 31 31 30 33 35 34 29 26 24
24.19 22.85 29.99 35.67 33.33 30.17 29.41 30.29 31.64 37.63 37.19 33.38 31.81 31.36 29.23 28.42 28.93 27.13 26.62 26.89 26.88
Manuf. Exp/ GDP 8.36 11.95 18.61 18.49 17.65 21.51 21.17 20.68 19.18 23.13 25.11 24.40 24.55 26.68 26.66 26.64 28.92 27.92 23.30 21.35 20.08
GFCF/ GDP
External Debt/GDP
25.20 21.20 25.70 32.30 29.10 27.50 30.60 34.20 38.00 34.60 32.70 32.30 32.90 32.50 33.00 32.80 33.10 34.60 37.10 39.50 41.40
28.05 31.57 29.28 29.05 37.03 33.55 31.42 27.31 29.09 40.07 42.54 45.40 44.60 43.07 45.08 37.16 32.18 21.68 17.08 16.43 16.40
GFCF
Public 24.26 22.60 16.94 15.51 19.14 19.26 18.55 18.53 18.20 21.66 24.32 19.93 19.19 18.32 19.39 17.88 16.18 16.06 15.08 14.15 15.39
Private 75.74 77.40 83.06 84.49 80.86 80.74 81.45 81.47 81.80 78.34 75.68 80.07 80.81 81.68 80.61 82.12 83.82 83.94 84.92 85.85 84.61
Primary Sector 29.64 28.90 27.25 27.27 27.64 26.07 25.44 23.75 22.09 17.75 18.57 17.27 15.90 15.03 14.94 13.47 12.21 12.07 11.20 10.17 9.22
Sectoral Composition
Manuf. 20.10 21.20 23.85 24.68 24.90 26.57 26.27 26.62 27.62 28.27 28.42 28.07 29.19 29.85 29.17 30.69 31.51 32.17 30.76 29.34 29.61
Construction 4.07 3.75 4.05 4.15 4.36 4.21 5.17 7.24 7.96 7.82 6.75 7.26 7.61 7.42 7.29 6.70 7.01 7.34 8.57 11.20 12.40
Services 46.18 46.15 44.85 43.90 43.11 43.15 43.12 42.39 42.32 46.17 46.26 47.40 47.31 47.69 48.60 49.14 49.27 48.43 49.48 49.29 48.77
Manuf. Growth 9.77 9.78 17.25 9.92 6.64 12.67 5.08 11.64 3.04 0.41 3.39 -1.45 3.83 7.91 -0.49 7.98 7.56 2.21 -2.56 0.36 1.17
(Continue)
100
Year
GDP Growth
Export/ GDP
Import/ GDP
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
6.20 6.80 9.20 9.60 7.60 5.90 -5.50 11.30 8.90 4.50 7.40 2.90 4.90 3.90 5.20 5.50 2.80 0.70 6.50 3.70 2.30 3.00
25 25 25 27 26 30 42 36 35 33 31 33 38 37 37 39 50 48 49 56 56 54
25.70 24.15 25.27 27.66 28.96 30.39 30.55 29.65 32.94 31.18 29.33 30.69 34.47 34.37 36.39 38.06 49.97 42.86 46.23 54.25 53.55 48.86
Manuf. Exp/ GDP 19.98 19.54 19.54 20.86 19.86 22.10 32.10 27.02 27.83 25.60 24.59 26.39 30.59 28.79 28.78 29.52 36.60 36.11 37.91 39.68 38.12 36.99
GFCF/ GDP
External Debt/GDP
38.50 37.50 38.60 39.20 39.90 37.60 27.90 31.20 33.20 31.90 31.20 32.30 32.30 32.50 33.00 32.80 33.00 28.60 32.10 32.90 30.80 28.80
16.57 16.83 17.61 19.48 24.00 28.84 40.26 28.75 24.07 21.77 21.13 20.33 19.39 18.03 22.66 30.17 31.52 38.21 32.52 33.27 33.44 32.46
GFCF
Public 16.50 16.18 15.61 14.97 14.87 16.22 19.17 17.88 17.24 18.02 17.01 18.34 18.28 17.58 16.73 16.47 16.88 20.75 17.11 16.31 16.09 15.98
Private 83.50 83.82 84.39 85.03 85.13 83.78 80.83 82.12 82.76 81.98 82.99 81.66 81.72 82.42 83.27 83.53 83.12 79.25 82.89 83.69 83.91 84.02
Primary Sector 8.79 8.00 7.91 7.49 7.07 6.49 6.02 6.14 5.60 5.29 4.92 4.58 4.56 4.14 3.92 3.61 3.42 3.27 3.10 3.15 -
Sectoral Composition
Manuf. 29.35 29.71 30.19 30.69 29.90 29.50 30.50 31.45 32.38 30.64 30.70 30.18 32.19 32.10 31.71 31.99 32.81 32.50 35.36 36.35
Construction 11.89 11.97 11.30 11.41 11.69 11.83 10.07 8.83 7.87 8.14 8.29 9.29 8.95 8.81 8.70 8.61 8.17 8.03 7.25 6.77 -
Services 49.97 50.32 50.60 50.41 51.34 52.17 53.41 53.58 54.15 55.93 56.09 55.95 54.30 54.95 55.66 55.79 55.60 56.20 54.29 53.73 -
Manuf. Growth 0.43 0.40 3.59 3.19 0.44 0.04 -2.97 12.60 8.86 -2.70 2.38 1.74 4.44 0.17 2.55 0.45 -1.54 0.66 7.53 7.53
Source: Elaborated by the author, using data from The Bank of Korea (BOK), Collins and Park (1989), World Bank, OECD and The Groningen Growth and Development Centre. Note: Data for GDP Growth and Gross Fixed Capital Formation (GFCF) in current Prices. Sectoral composition calculated from data at constant 2005 national prices (in millions).
101
Appendix 2.3 – Classification of manufacturing industries by technology group International Standard Industrial Classification full description Food and beverages Tobacco products Textiles Wearing apparel, fur, leather products and footwear Wood products (excluding furniture) Paper and paper products Printing and publishing Furniture; manufacturing, not elsewhere classified Coke, refined petroleum products and nuclear fuel Rubber and plastic products Non-metallic mineral products Basic metals Fabricated metal products Chemicals and chemical products Machinery and equipment, not elsewhere classified; office, accounting and computing machinery Electrical machinery and apparatus; radio, television and communication equipment Medical, precision and optical instruments Motor vehicles, trailers, semitrailers and other transport equipment
Abbreviation used in this chapter
International Standard Industrial Classification code Revision 3 Food and beverages 15 Tobacco 16 Textiles 17 Wearing apparel 18 and 19
Low-tech Low-tech Low-tech Low-tech
Wood products
20
Low-tech
Paper Printing and publishing Furniture, not elsewhere classified Coke and refined petroleum Rubber and plastic Non-metallic minerals Basic metals Fabricated metals Chemicals Machinery and equipment
21 22
Low-tech Low-tech
36
Low-tech
23
Medium-tech
25 26
Medium-tech Medium-tech
27 28 24 29 and 30
Medium-tech Medium-tech High-tech High-tech
31 and 32
High-tech
33
High-tech
34 and 35
High-tech
Electrical machinery and apparatus Precision instruments Motor vehicles
Technology group
Source: Unido (2013).
102
CHAPTER 3 - PRODUCTIVE DIVERSIFICATION, STRUCTURAL TRANSITION AND DENSITY OF INDUSTRIAL CHAINS: ARE BRAZIL AND SOUTH KOREA VERY DIFFERENT? Introduction120 Since the outbreak of the debt crisis in 1982, Brazil and South Korea have shown distinct economic performances. During the 1990s in both Brazil and South Korea, although to
different extents, neoliberal reforms were intensified under the assumption that economies could adjust effectively to a tough international environment with a hastily devised trade and
financial liberalisation. In Brazil, more specifically after the Real Plan (in 1994), the economic environment began to be characterised by an overvalued currency, high interest
rates and increasing participation of foreign capital in the domestic market. Under the fundamentalist process of economic reforms, the role of the State become secondary since the main goal of the proponents of the neoliberal view was strong market-friendly policies to
define the allocation of resources. Therefore, as a result this pro-market environment, the neoliberal agenda has resulted in poor economic growth for several decades.
Despite of the Brazilian economic boom from 2002 until the global financial crisis of
2008, the neoliberal shock of the 1990s produced deleterious economic changes. The country faced a productive disarticulation and the absence of sustained economic growth. In a “stop-
and-go” performance, the manufacturing sector has gradually shrunk. In this process,
domestic industrial chains have shrunk with the increase of imported inputs121. In other words, imported inputs played a substitutive role in the productive chain. Moreover, the economy has
experienced a specialisation in less dynamic sectors such as services and commodities. Furthermore, in terms of trade, the economy has increased its dependence on exports of
primary products. For instance, the share of agricultural and mineral commodities in total
I would like to thank Guilherme Magacho for his helpful comments on this chapter. For an explanation of the industrial dynamics of the Brazilian economy resulting from the economic reforms, see chapter 2. 120 121
103
exports rose from 6.27% and 6.43% in 1995 to 11.38% and 13.11% respectively in 2009, negatively affecting the Brazilian trade pattern.
In South Korea, during the same period, reforms regarding trade and financial
liberalisation were also adopted. However, the economic reforms were totally different to the
full-scale overhaul seen in Brazil. In fact, economic reforms in South Korea were much more
pragmatic in order to continue and strengthen the existing ambitious strategy of industrialisation. Even during the Asian crisis in 1997, in spite of the re-articulation between
state and private sector, the role of the state remained fundamental. To overcome the crisis there was a reorganisation of the corporate structure with processes of mergers and
acquisitions gaining momentum. However, it is important to note that at no time was the
manufacturing sector neglected. Therefore, the South Korean state remained active promoting the consolidation and expansion of industrial structure and exports. In this process, imports of
inputs had fundamentally a complementary role in the productive process. Moreover, in a strategy of productive and trade upgrading, South Korea took advantage of the special
properties of manufacturing as an engine of growth. Not by coincidence, the South Korean economic growth has been higher and much more sustainable when compared to the Brazilian economy.
Therefore, inserted in this short background, this chapter seeks to analyse the
structural transition of Brazil and South Korea. Through the input-output framework, from a comparative perspective, the chapter makes an effort to investigate these economies regarding their pattern of productive diversification, structural transition and density of industrial chains. Therefore, the contributions of this chapter to the existing literature are threefold. First, the
chapter adopts the methodology proposed by Imbs & Wacziarg (2003) in an inter- and intra-
sectoral perspective to identify the path of economic diversification undertaken by Brazil and
South Korea over the decades. Second, in a complementary analysis, the input-output
framework is used to identify and quantify factors that contributed to this pattern of specialisation. The method used was based on the Structural Decomposition Analysis (SDA) inspired particularly by Chenery’s studies.
Third, the chapter advances in the input-output
methodology employed by Rocha (2011) to estimate imported input coefficients for Brazil and South Korea through the World Input-Output Database (WIOD).
The chapter is organised as follows. The first section discusses the long-lasting debate
on specialisation or diversification and applies the method proposed by Imbs & Wacziarg 104
(2003) to investigate the stages of sectoral diversification presented by Brazil and South Korea over the decades. The methodology is also described in this section, including database
sources and the level of sectoral aggregation. The second section focuses on the sectoral
composition of manufacturing in these economies and their economic dynamism in a global perspective. The third section, through the so-called structural decomposition analysis (SDA),
investigates distinct factors, i.e. demand, trade and technological change, which contributed to the movement of structural change observed in these economies. In the fourth section, the chapter consolidates the understanding of the structural economic dynamics via movements related to the density of industrial chains. The fifth section concludes the chapter.
1. Structural change and economic dynamic: Specialisation vs. Diversification The neoclassical view stresses that specialisation based on comparative advantages,
whatever its nature, was a superior solution for economic growth. In this thinking, through the
process of specialisation, resources become more efficiently allocated and consequently countries benefit mutually in terms of welfare (Krugman & Obstfeld, 2006)122. Influential neoclassical visions such as Lipton (1968), Davis, (1995) and Mikesell (1997) grounded their
analyses on the neoclassical theory of comparative advantage and recommended that late
development countries (LDC) should specialise in the production and exports of primary commodities and import manufactured products from industrialised economies. Although the
idea of comparative advantage has received further developments in the current mainstream approach, particularly in the New Structural Economics (NSE) framework123, specialisation according to the country’s factor endowment structure continues to be an integral part of
policy advice. As pointed out by Rodrik (2004, p. 6) many economists that “associate underdevelopment with inadequate exposure to international markets generally imply –
although this is often left unstated – that specialisation according to comparative advantage is 122
The comparative advantage theory was developed by David Ricardo in his Principles of Political Economy in 1817. Ricardo uses trade between England and Portugal in cloth and wine respectively to advocate in favour of free trade policies. In this example, these countries would benefit mutually because they would be specialising in the good that has lower opportunity cost (Ricardo, 1817). Despite the simplicity of Ricardo’s theory, it has been interpreted in several different ways, and continues to have a remarkable impact on the current mainstream theory. 123 According to the former chief economist of the World Bank Justin Yifu Lin, “the economic structure of an economy is endogenous to its factor endowment structure and that sustained economic development is driven by changes in factor endowments and continuous technological innovation”. In other words, “the new structural economics argues that the best way to upgrade a country’s endowment structure is to develop its industries at any specific time according to the comparative advantages determined by its given endowment structure at that time”. (Lin, 2012, p. 5).
105
an essential ingredient of development”. Currently this understanding is also supported by the World Trade Organization (WTO), which advocates in favour of market-friendly policies.
The WTO (2011) states that “countries prosper first by taking advantage of their assets in order to concentrate on what they can produce best, and then by trading these products for
products that other countries produce best”. Moreover, specialisation on comparative
advantages through liberal policies would sharp competition, motivate innovation and breed success (ibid, 2009).
From a critical perspective, the Structuralist-Kaldorian view points out the limitations of
a strategy of economic development based on comparative advantages. Therefore, based on the argument that diversification in manufactured products is the main engine of growth, authors such as Rosenstein-Rodan (1943), Prebisch (1949), Lewis (1954), Rostow (1952),
Furtado (1961), Hirschman (1958), Kaldor (1966, 1967) and Chenery (1960, 1979) belong to
the handful of economic thinkers that have emphasised the importance of diversification to economic development. According to them, development is essentially a process of structural
change. In other words, sustained economic growth is associated with the capacity to diversify
the structure of domestic production, i.e. generate new activities to expand possibilities of production, linkages and higher value-added goods by providing incentives to manufacturing.
According to Kaldor (1966), economic growth is brought about by shifting productive sectors
with constant or decreasing returns to those with increasing returns to scale. This shift creates
dynamic economies of scale and triggers a process of cumulative causation in the economy.
The author states that manufactured goods is the sector with the greatest capacity to do so and therefore its expansion plays a key role in promoting sustainable growth in the long term and in the consequent modernisation and diversification of the production structure124. 1.1. The U-shaped curve for Brazil and South Korea Recently, this long-lasting debate regarding economic specialisation or diversification
has been approached by empirical studies that tried to model the trajectory of economic
diversification undertaken by a vast range of economies. In an important paper, Imbs &
Wacziarg (2003) investigated the stages of sectoral diversification in a large cross-section of countries. Using OECD, ILO and UNIDO databases, this study employed a non-parametric
methodology based on locally robust weighted scatter plot smoothing (Lowess) to identify 124
For a detailed discussion on the special growth-enhancing properties of manufacturing, see chapter 1.
106
regularities regarding the process of productive diversification. Thus, the authors detected a
non-linear relationship between specialisation and GDP per capita, described as a U-shaped curve.
In this U-shaped curve, low-income countries present a very specialised productive
structure. As countries move from low to medium levels of income, diversification takes place in the economy. This process goes on until relatively late in the process of economic
development. On average, the diversification takes place until the country reaches a turning point around $ 9,000 GDP per capita. Thereafter, the sectoral distribution exhibits respecialisation with the curve presenting an ascendant trajectory. From this perspective, as
pointed out by Rodrik (2004), Imbs and Wacziarg’s findings suggest that specialisation according to comparative advantage as conventionally understood cannot be the driving force
of economic development. In other words, countries grow and reach a high level of income per capita during the phase of diversification and not specialisation.
Therefore, seeking to evaluate the movement of structural change undergone by Brazil
and South Korea, from a comparative perspective, this section employed the methodology of Imbs and Wacziarg to investigate these economies from both an intersectoral perspective, i.e.
between primary sector, manufacturing, civil construction and services, as well as from an
intra-sectoral perspective (among manufacturing subsectors)125. In order to calculate each economy’s inter-sectoral curve of specialisation, the GGDC 10-Sector Database and the IBGE database were used for South Korea and Brazil respectively. For the intra-sectoral analysis of
South Korea, the manufacturing value-added of 23 subsectors from the UNIDO database was
used. In the case of Brazil, due to lack of long-term data, this study used the ECLAC-PADI database with 28 manufacturing subsectors. Since this chapter seeks to compare Brazil and
South Korea, both databases were aggregated on a common level involving 14 manufacturing
subsectors126. In addition to using the same aggregation level, Figures 3.1 and 3.2 present two distinct graphics. The first graph plots the Gini-Hirschman index (GHI) against GDP per capita, along with a non-parametric Lowess curve. The second shows the sectoral share
between the primary sector, manufacturing, civil construction and services. The graphs are presented together to investigate particularities regarding the process of economic diversification and structural change undergone by these economies. 125 126
Technical details about methodology are summarised in Appendix 3.1. For details about the aggregation see Appendix 3.2.
107
From an inter-sectoral view, based on a developmental premise that industrialisation in
general and manufacturing specifically is a central condition to economic development, South
Korea consistently raised its share of manufacturing followed by a substantial decrease of the primary sector. From 1953 to 2010, the former rose from 8% to 35% while the latter fell from 49% to 3%. Moreover, a joint analysis between data from the curve of diversification and the
sectoral share of the economy reveals that the movement of intersectoral structural change
pursued by South Korea followed two stages of manufacturing expansion. In the first stage, from 1953 to 1980, South Korea moved to a strategy of economic diversification expanding
remarkably not only the manufacturing sector but also civil construction (and strongly services during the 1950s). During this period the manufacturing share rose by 236.6%, while civil construction increased by 337.9% and services by 13.3%. Thus, by the end of the 1980s, the South Korean economy achieved a considerable degree of diversification.
Figure 3.1 - The inter-sectoral U-shaped curve and sectoral share for South Korea 100%
68 66 64
(GHI)
62
53 60 65 70
60
95
75
58
80
56
85
00
05
08
80%
41
60%
2 8
70% 50%
90
40% 30% 20%
54 52
90%
10% 0
5,000
10,000
15,000
GDP per capita
20,000
25,000
49
47
3
12
38
39 3
17
41
46 43
5
4
20 25
29 28
0% Primary Sector
46
8 28
18
Manuf
49 49
7 29 15
50
11
11
29
31
10
7
CC
54 55 54
8
9
7
32 32 35 6
4
3
Services
Source: Own calculations based on data from GGDC 10-Sector Database. Note: Data calculated in current US dollars.
In the second stage, from 1980 to 2010, although the pace of structural change
decreased, with the share of manufacturing and services growing respectively by 25.1% and 17.6%, the economy engendered a process of economic specialisation. The changes in the
shares of services and manufacturing from the beginning to the end of this stage show the magnitude of this trajectory. While in 1980 manufacturing and services together accounted for approximately 74% of the economy value-added, in 2010 this number jumped sharply to 90%.
108
It was only possible because the expansion of both sectors took place mainly as a result of the reduction of the primary sector. Even during the decades of 1990s and 2000s, the clear rise of
services was not followed by a loss in manufacturing. Therefore, the Figure 3.1 illustrates clearly that despite of the large share of services in the economy, South Korea has showed a pattern of specialisation based on the expansion of the manufacturing sector.
In a manner distinct from South Korea, Brazil did not experience the same process of
structural change and productive diversification for the period analysed. As a matter of fact, the country smoothed data did not fit well to the U-shaped curve. However, two important
issues must be considered. Firstly, an important period of economic diversification not
captured by the data was engendered by the Brazilian economy during the 1930s and 1940s. In other words, as widely documented in the Brazilian economic literature, the process of economic diversification was initiated in the 1930s after the great world economic crisis in
1929. At that time, Brazil moved from a primary export model to a strategy of Import
Substitution Industrialisation (ISI)127. Secondly, despite an upward sloping, the country maintained a diversified inter-sectoral productive structure until the first half of the 1970s. As a matter of fact, from 1950 to practically 1980, the share of manufacturing and civil
construction grew respectively by 67.6% and 66.6%, while the primary sector and services dropped by 54.7% and 3.5%. Moreover the GDP per capita expanded continually.
However, with the outbreak of the debt crisis (in 1982) and the rise of neoliberal
policies, Brazil embarked on a regressive trajectory128. From 1980 to 2010, not only manufacturing and civil construction declined sharply in terms of GDP share (from 31.29% to 16.23% and from 6.81% to 5.65% in each sector respectively) but also income per capita
regressed in many periods such as 1981–1983, 1988–1992 and 1998–1999. In this sense, in contrast to South Korea, Brazil did not experience the same long-term dynamism in manufacturing and GDP per capita growth. Additionally, one of the most notable effects of market-friendly policies, which intensified during the second half of the 1990s, was the
collapse of manufacturing share in the total GDP. The economy gradually lost the manufacturing sector to the point where it represented a lower share than in 1950. Figure 3.2 illustrates these processes.
127 128
For details on the Import Substitution Industrialisation (ISI) in Brazil, see chapter 2. For details on the Brazilian economic dynamic after the 1980s see chapter 2.
109
Figure 3.2 - The inter-sectoral U-shaped curve and sectoral share for Brazil 82
100% 90%
77
08
(GHI)
72 67 62
47
57 52
50 55 60 65 70
75
00 95 80 90 85
05
80% 70% 60% 50% 40% 30% 20% 10%
0
2,000
4,000
GDP per capita
6,000
53 52 51 54 55 51 51 49
0%
4
4
19 20 25 24
5
5
26 25 19 17
5
6
7
27 31 31
62
5 32
7 23
12 12 11 14
Primary Sector
Manuf
69 70 69 70
CC
8
5
6
5
7
7
8
6
19 17 18 16 8
Services
Source: Own calculations based on data IBGE. Note: Data calculated in current US dollars.
As previously mentioned, the intra-sectoral movement inside the manufacturing sector
was also analysed. As it is possible to see in Figure 3.3, both Brazil and South Korea
experienced a U-shaped trajectory. However, from a comparative perspective, the U-shaped pattern also presented three important differences. First, the phase of economic diversification was more intense in South Korea. Second, in terms of value-added, the South Korean
economy showed the point of maximum diversification in 1988 with $7,621 GDP per capita129, while in Brazil it occurred in 1975 with $4,187 GDP per capita. After these stages, both economies engendered an ascendant and constant trend of re-specialisation. Nevertheless, as showed by the Figure 3.3, after 1988 South Korea specialised its
manufacturing in subsectors that enabled a substantial increase in terms of GDP per capita.
Thus, from 1988 to 2008 the GDP per capita increased by 168.8%, reaching $ 20,482 in 2008.
In the case of Brazil, the premature trajectory of re-specialisation culminated in a less dynamic productive structure that trapped the economy into a 'low-growth landscape'. From
1975 to 2008, the GDP per capita increased only by 54.7% (on average an annual increase of 1.42%) and the economy showed a chronic dynamic of ‘stop and go’. The following section analyses manufacturing subsectors and their evolution over time.
It is important to note that the turning point of a trajectory of re-specialisation is significantly lower than those observed in advanced countries. For more details see Imbs & Wacziarg (2003). 129
110
Figure 3.3 - The intra-sectoral U-shaped curve South Korea (1963-2008)
33
42
34
00 80
32 0
(GHI)
(GHI)
70
36
5,000
85
05
31.5
00
70
31
95 90
10,000
08
32
05
63
38
30
32.5
08
40
Brazil (1970-2008)
75
30.5
15,000
GDP per capita
20,000
25,000
30 2,000
3,000
4,000
90 85
5,000
GDP per capita
95 80
6,000
7,000
Source: Own calculations based on data from UNIDO and ECLAC-PADI. Note: Data calculated in constant US dollars for Brazil and in current prices for Korea due the lack of data.
1.2. Sectoral composition and economic dynamism Another dimension that deserves a close analysis to understand the path of
specialisation undertaken by the Brazilian and South Korean manufacturing industries in
relation to the GDP per capita is the evolution of this process over time. In this context, by simply taking into account the share of each manufacturing subsector in the total value-added
and specialisation indexes over decades it is possible to trace the pattern of specialisation
under way in these economies. Moreover, through this analysis is also possible to investigate the pattern of specialisation in terms of technology intensity. Therefore, starting in 1990, Table 3.1 shows the evolution of sectoral composition of the manufacturing value-added in Brazil and South Korea, at an interval of five years in each decade.
The trajectory of intra-sectoral specialisation in South Korea was marked by a
significant drop of low-tech sectors compensated by a strong expansion in high-tech sectors. From 1990 to 2008, the share of the former in the total manufacturing slumped from 33.2% to 13.9% while the latter increased sharply from 43.4% to 59.3%. In this trend, the sharp
111
increase of the ‘Machinery’ subsector draws attention particularly due to its substantial rise in the total value-added of the economy, i.e. by 10.1 percentage points. Recognised as a
knowledge-intensive subsector of manufacturing, the Structuralist-Schumpeterian literature has stressed the growth-inducing effects of the machinery subsector particularly regarding the
introduction and diffusion of technological change130. Another sector that contributed to expanding the high-tech group was ‘Transport Equipment’, which rose from 10.5% to 16.8%. Additionally, the increase of medium-tech subsectors, although to a lesser extent, also
contributed to productive specialisation (and economic dynamism), increasing by 3.4
percentage points. In short, the South Korea's pattern of intra-sectoral specialisation was marked by a gradual share concentration in medium- and high-tech sectors that together reached 86.1% of the total value-added in 2008.
Table 3.1 – Sectoral composition of the manufacturing sector (%), 1990-2008 Subsectors Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Total manufacturing Low-Tech Medium-Tech High-Tech GHI
90
South Korea 95 00 05 8.4 8.8 1.4 0.8
8.3 7.1 0.9 0.6
6.6 4.8 0.5 0.5
6.1 3.6 0.4 0.4
15.1 9.7 2.3 1.5
13.4 7.9 1.4 1.1
14.5 7.0 1.0 1.2
13.6 5.5 0.8 1.1
15.1 4.9 0.7 0.9
4.9
4.9
4.8
4.0
2.1
6.5
7.8
7.7
7.8
7.1
10.7 10.3 3.6 0.9
08
90
Brazil 95 00
05
08
3.0 3.4 2.6 3.5 4.6 6.1 7.6 8.6 7.8 6.9 9.2 9.3 9.5 8.6 8.7 12.7 11.1 11.3 10.0 9.0 3.9 3.9 4.0 4.7 4.3 4.6 3.3 3.4 2.9 2.6 5.1 4.8 3.8 3.4 3.3 2.6 2.3 2.4 2.1 2.1 11.4 11.5 10.4 13.2 14.6 13.3 13.9 13.4 13.6 13.0 19.7 24.8 28.2 30.2 29.8 8.1 10.4 9.8 12.0 12.8 4.0 4.3 4.8 4.5 4.0 8.2 10.5 10.9 11.8 11.4 10.5 11.3 13.1 13.8 16.8 7.1 7.8 7.6 10.0 12.4 2.9 2.3 1.8 1.6 1.3 2.2 1.6 1.3 1.1 0.9 100 100 100 100 100 100 100 100 100 100 33.2 26.6 23.4 18.0 13.9 37.4 33.2 32.7 30.0 29.7 23.4 23.7 20.9 24.9 26.8 26.5 27.0 27.7 26.2 24.7 43.4 49.7 55.7 57.2 59.3 36.1 39.8 39.6 43.7 45.7 32.3 34.8 37.1 38.8 39.8 31.0 31.3 31.5 31.9 32.3 Source: Own calculations based on data from UNIDO and ECLAC-PADI. Note: Data calculated in 2008 constant US dollars for Brazil and in current prices for Korea due the lack of data. Nec = Not elsewhere classified.
In Brazil, the pattern of productive specialisation was also marked by the expansion of
high-tech subsectors such as ‘Machinery’, ‘Electrical and Optical Equipment’ and ‘Transport 130
1.
For a detailed explanation about the growth-enhancing particularities of the machinery subsector, see chapter
112
Equipment’. However, in spite of the substantial increase of 9.6 percentage points in this group, the pace and proportion of this expansion was clearly lower than in South Korea.
Moreover, although the low-tech sector showed a clear drop of 7.7 percentage points, the Brazilian economy remained dependent on less dynamic sectors such as ‘Food, Beverages and
Tobacco’, which represents 15.1% of the total value-added in the economy. Furthermore, the
medium-tech group presented a slight descendent trajectory varying from 26.5% in 1990 to 24.7% in 2008. In this group, the clearest loss was in ‘Rubber and Plastics’ which dropped by 2 percentage points. In brief, Brazil presents a manufacturing sector more diversified than South Korea but in less dynamic sectors. From the perspective of comparative economic development, this dichotomy stimulates different processes of cumulative causation and, consequently, results in divergent growth rates.
The inter- and intra-sectoral composition of Brazil and South Korea culminated in
distinct economic performances. From a comparative perspective it can also be illustrated in relation to the global economy. Thus, figure 3.4 shows the evolution of their shares in both
global manufacturing and GDP, elucidating the South Korean thriving economic dynamism
vis-à-vis the poor performance of Brazil. Therefore, over the decades, South Korea showed a sustained economic growth taking advantage of dynamic economies of scale, increasing returns and spillover effects that set in motion processes of cumulative causation. From 1950
to 1980, the share of South Korea in global GDP expanded by 133.1% and manufacturing rose by 210.7% (from 1970 to 1980). Even after the turbulent 1980s and the rise of neoliberal
policies in the developing world particularly in the 1990s, the economy kept the impetus of growth, increasing its share in the global GDP and manufacturing. Brazil, by contrast,
although with a considerable increase of these variables from 1950 until 1980, collapsed with
the outbreak of the debt crisis. During the 1980s, Brazil was trapped in an economic dynamic
that sentenced the country to a poor economic performance. From the 1990s, with the advent of neoliberal reforms the economy not only remained stagnated in the evolution of the global GDP share and but also lost a significant share in global manufacturing.
113
Figure 3.4 - Shares in global manufacturing and GDP Share in Global GDP
3.50
2.49
2.50
1.50
1.65
1.92
0.00
0.33 1950
2.06
2.59
2.47 1.91
1.90
0.35 1960
0.49
1970
2.50 2.00
0.50
1990
2.68
2000
2010
Brazil
0.00
2.55 2.09
1.54
1.98 1.43
1.00
0.76
1980
3.27
3.00
1.50
1.25
1.00 0.50
3.50
3.12
3.00
2.00
Share in Global Manufacturing
0.19 1970
1.76
0.59
1980
1990
2000
2010
South Korea
Source: Elaborated by the author, using data from The Groningen Growth and Development Centre and UNCTAD. Note: Sectoral shares calculated at 2005 constant national prices.
2. The structural decomposition analysis Seeking to understand the results found in the previous section, this section tries to
find factors that directed the path of structural change observed in Brazil and South Korea in light of liberalising policies implemented in these economies during the second half of the
1990s. Therefore, based on the pioneer analysis developed by Leontief (1936, 1941), the
theoretical approach is based on the input-output method. Over the years, this methodology has been widely used in structural analyses to study effects of distinct economic policies over
the structure of production. Thus, from an analytical input-output framework, the so-called
structural decomposition analysis (SDA) inspired by Chenery (1960), Chenery et al. (1962), Chenery & Syrquin (1980) and Chenery et al. (1986), has been applied for many countries in
vast range of contexts and periods to identify and quantify factors that contribute to a given
change in the sectoral structure. This method is usually adopted to investigate distinct factors,
114
i.e. demand, trade and technological change, which contributed to a certain change in the industrial structure131.
In contrast to the framework of neoclassical models, which consider economic growth
as a process limited by the supply side, the SDA is a method of growth accounting on the demand side. Furthermore, it takes account of inter-relationships between various sectors (and
subsectors) of the economy, rather than sectoral trends in isolation from one another. Using this methodology, it is possible to empirically investigate the economic role of a productive
sector without restricting the analysis to its “direct effects” on the economy regarding generating production, employment, value-added products, tax revenue, and exports. With
this method, it is also possible to investigate the “indirect effects”, i.e. the effects that a sector can exert on other sectors through channels established by input-output transactions between different economic sectors.
Over the years, the SDA methodology was improved as analytical tool and different
methods were developed. In this sense, Feldman et al. (1987), Skolka (1989), Rose & Casler
(1996) and Dietzenbacher & Los (1998) were particularly relevant. More recently, many studies analysed the economic structure through this line of methods. Kupfer el al. (2003) decomposed the output and employment variation of the Brazilian economy between 1990
and 2001. Tregenna (2012) applied this method to South Africa from 2000 to 2007. In addition, Zakariah & Ahmad (1999) used the factor decomposition approach to Malaysia from 1978 to 1987. However, none employed the SDA methodology from a comparative
perspective between Brazil and South Korea through a common database. Therefore, the data available at the World Input-Output Database (WIOD) was used to analyse the output
decomposition between two periods: 1995-2002 and 2003-2008. These breakdowns were applied more as a result of data availability than because of distinct economic policies. In
addition, input-output tables were estimated in constant prices using the database available in
both current and previous years’ prices132. Therefore, analogously to Chenery et al. (1986) this chapter decomposed output growth (∆ ) in manufacturing into the following four components133:
These explanatory factors are commonly used in the debate on industrialisation/deindustrialisation to understand a given pattern of specialisation. 132 Previous analysis showed that for this type of methodology, data for 2009 was strongly affected by the global financial crisis. Therefore, exclusively in this chapter, this year was excluded in the input-output analysis. 133 Technical details about methodology are summarised in Appendix 3.1. 131
115
Domestic demand (∆ ): Refers to the direct and indirect effects of the variation in the domestic final demand on the sector (or subsector) output. Domestic demand includes household consumption expenditure, government consumption expenditure and gross
capital formation.
Export (∆ ): Indicates the direct and indirect effects of the variation of exports on
each sectoral (or subsector) output. It is important to note that this component is affected by intersectoral relationships. In other words, it is affected not only by exports
of the sector under analysis, but also by exports of other sectors with which this sector
is linked.
Import substitution (∆ ): Refers to the direct and indirect effects of the variation of
sectoral output associated with the substitution of imports (intermediates and final goods) by domestic production. Analogously to export expansion, this component is
affected by intersectoral relationships and consequently reflects not only import substitution in a specific sector, but also import substitution in other sectors with
which a sector is linked.
Technological change (∆ ): Indicates the variation on sector (or subsector) output
associated with changes in the production processes which affect the economy technical coefficients (input-output coefficients). Thus, this component is obtained through changes in the table of technical coefficients, which shows the flow of intermediate inputs (domestically and imported) into the production of all goods and services of the economy.
Tables 3.2 and 3.3 show the results for both countries from 1995 to 2002 and 2003 to
2008. For each sector (or subsector) the contributions of the four components (domestic demand, export, import substitution and technological change) to economic growth are
presented. Inter- and intra-sectoral results are presented to provide subsidies to understand the process of specialisation in Brazil and South Korea. In order to maintain a robust intrasectoral analysis, results of the SDA were presented as close as possible to the aggregation of
the last section. Thus, manufacturing was aggregated in 15 subsectors. Additionally,
manufacturing was divided by technology intensity (low-, medium- and high-tech) according to UNIDO classification.
116
3. Interpreting results in light of distinct economic policies During the 1990s, Brazil and South Korea experienced distinct economic policies. In
Brazil, after a turbulent and critical passage through the 1980s marked by economic stagnation and high inflation rates, the Real Plan (Plano Real) was adopted in 1994, aiming to
stabilise the economy. The economic policy of the period was essentially based on liberalising
reforms that sought to stabilise the economy through high interest rates, currency overvaluation and wage squeezes. Measures such as trade liberalisation (the reduction of tariff and non-tariff barriers), privatisation of state-owned enterprises and capital account openness culminated in a disastrous economic environment for the national industry. Moreover, from 1998 to 2003 the Brazilian economy experienced a period of balance-of-payment crisis and
currency depreciation that was associated with a restrictive macroeconomic policy based on
the inflation target regime which undermined any attempt of significant recovery in the manufacturing sector.
Therefore, as shown in Table 3.2, from 1995 to 2002 manufacturing output increased
by only 9.1% despite exports increasing by 15.9%. Additionally, it is important to note that
during this period, with the exception of exports, all components (domestic demand, import substitution and technological change) of the Brazilian manufacturing sector registered
negative variations. In an intra-sectoral perspective, the results of the structural decomposition analysis reveal that many manufacturing subsectors affected were those belonging to the medium- and high-tech group. Remarkable examples are the subsectors of ‘rubber and
plastics’, ‘non-metallic mineral’ as well as ‘electrical and optical equipment’. In contrast the
primary sector output based on the Brazilian comparative advantage grew by 43.0%, mostly driven by exports which represented 26.0% of this expansion. Furthermore, during this period
services output expanded by 18.0% probably as a result of the privatisation process of the decade, particularly in subsectors of infrastructure such as energy and telecommunications134.
In a distinct economic dynamic, South Korea did not embark on the same type of
‘fundamentalist’ economic reforms. As a matter of fact, although financial and trade
liberalisation marked South Korea during the 1990s, it was much more pragmatic in order to continue and strengthen the existing ambitious strategy of industrialisation. Over the decades,
the South Korean history of economic development has been notable for the special properties 134
For details on the process of privatisation see chapter 2.
117
of manufacturing as a key sector to economic growth. Therefore economic reforms were
implemented as a pragmatic mechanism to help lift specific pressing economic and financial
constraints in order to expand the manufacturing sector. Even during the Asian crisis in 1997, in spite of the re-articulation between the state and private sector, the role of the state was central in maintaining industrial dynamism. To overcome the crisis there was a reorganisation
of the corporate structure with processes of mergers and acquisitions gaining momentum. Additionally, the South Korean state remained active both through long-term programmes for the development of high-tech sectors and by ensuring important long-term funding sources through public banks.
Table 3.2 - Inter and Intra-sectoral decomposition of output growth (%), 1995-2002 Sectors Primary Sector Manufacturing Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Services
(∆ )
21.0 -9.7 14.7 -2.1 -14.3
South Korea (∆ ) (∆ ) (∆ )
(∆ )
(∆ )
-16.8 6.3 3.7 9.2 2.4
-8.7 11.0 -4.9 5.6 -1.4
4.5 50.7 4.8 8.1 -15.7
0.0 58.3 18.3 20.8 -29.0
-28.6
18.7
11.3
12.4
13.8
-14.6
11.9
21.9
30.3
-38.6
4.9
13.9
-2.9 -10.9 -23.5
14.0 1.5 -1.8
-22.2 -9.3 24.5 8.9
9.6 -2.7 -3.3 -4.5 -5.4
Brazil (∆ ) (∆ ) (∆ ) (∆ ) 1.0 -0.8 1.0 1.9 0.6
6.3 -3.3 5.4 -17.9 -19.1
26.0 15.9 16.3 6.3 17.2
43.0 9.1 19.3 -14.1 -6.7
-27.4
-0.1
-2.2
32.7
3.0
49.5
-1.9
3.3
6.7
12.5
20.6
47.8
28.1
7.2
-0.5
-2.9
13.7
17.5
6.3 10.4 18.5
57.8 50.7 29.3
75.1 51.7 22.7
7.9 -8.5 -1.3
-2.5 -0.6 0.0
-1.8 -4.8 -4.6
11.1 14.8 10.0
14.7 0.9 4.0
5.2 8.3
9.2 18.0
45.7 50.6
37.9 67.7
-8.7 -4.1
-1.4 -1.6
-1.4 3.7
19.4 16.6
7.9 14.5
7.5 4.2
63.1 3.5
222.1 69.7
317.2 86.4
-1.2 -8.7
-5.7 -2.4
-21.0 -6.8
14.6 28.7
-13.4 10.7
-4.0 3.2 -1.2 -4.0 0.4 36.8 Source: Own calculations based on data from WIOD. Note: Data calculated in 2008 US constant dollars.
16.6 11.7
14.6 44.9
-5.0 3.3
-0.1 0.0
-4.0 10.5
7.9 4.2
-1.2 18.0
Indeed, from an inter- and intra-sectoral perspective, Table 3.2 highlights the
dichotomy between Brazil and South Korea. From 1995 to 2002 manufacturing production in
South Korea increased by 58.3% of which 50.7% was explained by increase in exports.
Moreover the booming expansion of medium- and high-tech industries composed one of the main sources of economic dynamism. During the 1980s and 1990s, the South Korean 118
government engendered a massive effort to constitute a solid strategy based on technology development enhancing the industrial structure toward dynamic manufacturing industries. For
example, the output in ‘chemicals and chemical products’, ‘rubber and plastics’, ‘basic metals and fabricated metal’, ‘machinery’, ‘electrical and optical equipment’ and ‘transport
equipment’ expanded significantly, mainly as a result of exports. ‘Electrical and optical
equipment’ and ‘transport equipment’ increased their outputs by 317.2% and 86.4% respectively where exports corresponded to 222.1% and 69.7%. Not by coincidence, the
South Korean economic growth has been higher and much more sustainable when compared to the Brazilian economy.
From 2003 until the outbreak of the global financial crisis in 2008, the pattern of
economic development for these two economies showed interesting movements. According to
Table 3.3, in South Korea exports of the manufacturing sector were maintained as an engine of economic growth. However, the ‘flying geese’ movement of regional productive
fragmentation associated with the economic policy based on a paradigm of global value
chains negatively affected import substitution135. Although the country showed a higher output expansion when compared to the Brazilian economy, the productive reallocation of
components and labour-intensive assembly-end parts to other countries within the Asian block
such as the 'third-tier' NICs (particularly China) slowed the pace of output growth during the period.
As shown by Table 3.3, although the output growth rose by 39.1%, mainly pushed by
exports, the component of import substitution negatively affected the manufacturing sector by a factor of 8.6%. From an intra-sectoral view, despite the consolidation of medium- and hightech manufacturing subsectors as engines of economic dynamism, the same industries were
badly affected with a negative variation of import substitution. In this aspect, notable
examples were ‘Coke, Refined Petroleum and Nuclear Fuel’, ‘Chemicals and Chemical Products’, ‘Rubber and Plastics’, ‘Other Non-Metallic Mineral’, ‘Basic Metals and Fabricated
Metal’, ‘Machinery’, and ‘Transport Equipment’. In short, the economic dynamism of the South Korean economy was not higher because of deleterious effects of imports on domestic production.
135
For a detailed explanation about the ‘flying geese’ paradigm, see chapter 2. See also Ozawa (1991, 1995).
119
Table 3.3 - Inter and Intra-sectoral decomposition of output growth (%), 2003-2008 Sectors Primary Sector Manufacturing Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Services
(∆ )
117.5 4.8 3.9 2.7 -1.3
South Korea (∆ ) (∆ ) (∆ ) -118.5 -8.6 -3.3 0.9 0.7
11.7 3.9 3.0 13.5 -19.0
4.3 39.0 3.9 -13.8 -10.3
2.3
-1.9
8.1
9.3
-9.8
-4.0
3.9
27.3
-20.8
-11.2 3.7 5.7
(∆ )
15.0 39.1 7.4 3.3 -29.9
Brazil (∆ ) (∆ ) (∆ ) (∆ ) (∆ ) 9.2 3.1 1.6 -6.9 -1.3
-11.8 -8.2 -1.6 -5.0 -0.5
13.7 26.8 13.7 29.5 14.3
10.2 0.5 1.2 -3.3 -18.0
21.3 22.2 14.9 14.3 -5.6
17.7
-2.8
-2.1
16.1
-24.1
-12.9
15.2
5.4
-1.0
-5.1
25.4
0.4
19.7
1.3
28.1
35.9
2.9
-11.6
15.4
6.6
13.4
-9.6 -6.6 -7.2
4.9 5.0 6.5
32.8 37.2 19.4
16.9 39.4 24.4
6.0 -0.6 3.4
-16.6 -9.8 -4.9
21.5 27.4 30.1
-0.4 2.4 -0.8
10.5 19.5 27.8
8.1 17.5
-18.3 -7.7
4.7 5.6
33.5 49.2
28.1 64.5
0.5 3.4
-11.3 -6.6
26.8 49.6
-1.3 3.2
14.6 49.5
-0.6 0.2
3.9 -4.9
5.5 -2.1
88.3 59.3
97.1 52.4
13.2 11.4
-16.5 -6.9
44.4 56.5
-0.3 6.0
40.8 67.0
19.6 -2.3 14.8 2.4 34.4 -1.9 4.8 -5.2 12.4 8.3 20.2 4.8 Source: Own calculations based on data from WIOD. Note: Data calculated in 2008 US constant dollars. Nec = Not elsewhere classified.
-1.8 -2.8
27.2 24.1
-3.4 1.0
20.1 27.1
In Brazil, inter and intra-sectoral results indicates a different pattern of economic
growth but also some common trends. While in South Korea the pattern of economic
development was in both periods (before and after 2003) driven by exports of manufacturing
products, in Brazil the domestic demand from 2003 to 2008 composed the key variable of economic growth. In this period, the so-called commodity prices boom and the credit-led
consumption-boom boosted the economy. The former affected the economy promoting the exports of primary products, while the latter pushed the domestic demand as a whole.
However, even in this context, once again manufacturing performed worse when compared to
the services sector, which showed the most dynamic output growth. Not even the Brazilian National Development Bank (BNDES) providing many benefits for national producers, such
as funding with very low interest rates and certain benefits to stimulate exports (especially for
producers that use domestic inputs), was capable of reversing this trend. In an extreme adverse macroeconomic policy marked by high and volatile interest and exchange rates, the industrial policy became ineffective.
120
Moreover, a comparative intra-sectoral analysis between Brazil and South Korea
reveals that low-tech manufacturing subsectors such as ‘leather, leather and footwear’ and
‘wood and products of wood and cork’ (in the case of Brazil) showed a negative output
variation while ‘machinery’, ‘electrical and optical equipment’ and ‘transport equipment’
expanded significantly in both economies. Finally, another common trend between Brazil and South Korea was the clear negative variation of import substitution in the total output. In both
economies, the demand has been met by imports of either capital goods or intermediate inputs. Seeking to evaluate this common trend in detail next, the section turns to this issue. 4. The density of industrial chains Data regarding import input coefficients for Brazil and South constitutes an important
indicator to analyse the density of domestic industrial chains. Thus, through data available at
the World Input-Output Database (WIOD) and some input-output techniques, it is possible to measure the evolution of such coefficients over time136. In this way, Tables 3.4 and 3.5
elucidate that in each economy these coefficients followed a distinct trend marked by
contrasting economic policies and strategies of development137. In South Korea, over the years the process of industrialisation was characterised by a constant expansion of manufacturing and gradual density increase of the domestic industrial chains, i.e., relative
increase of domestic inputs in the productive process vis-à-vis imported ones. However, as
shown by Table 3.4, from 1995 to 2002 this process was accompanied by an increasing share
of imported inputs in the domestic manufacturing sector that were consolidated in the subsequent period.
As a matter of fact, from 2003 to 2008, the South Korean economy significantly
increased the share of imported inputs not only in the manufacturing sector but also in the economy as a whole. The reasons for that are twofold. The first relates to the new productive
environment marked by global value chains, where the productive structure has been gradually fragmented over the years. From this perspective, productive fragmentation is seen as an important source of firm efficiency through improvements in competitiveness both in
domestic and international markets and by cost savings. The second reason relates to the Technical details about methodology are summarised in Appendix 3.1. Rocha (2011) analysed the participation of imported input coefficients only in the Brazilian industrial chains. Additionally, in this study the analysis adopted the IBGE database. 136
137
121
‘flying geese’ process of industrialisation, where the productivity capacity at a certain stage of
the economic development is transferred to the less-developed country (particularly Nics-2 and China) in a process of regional fragmentation of the productive chain. Although both reasons are associated with the concept of productive fragmentation, they might be seen as
different sides of the same coin. It is because the first reason is related with cost savings per se and a premature process of de-industrialisation in most developing countries, while the
second one relates to a regional strategy of development and the expansion of manufacturing
in the economy. Since South Korea expanded not only the use of imported inputs in its productive structure but also the share of manufacturing, the second reason becomes seems likely.
Table 3.4 - Import input coefficients for Korea, 1995-2008 Sectors Primary Sector Manufacturing Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Services
95
96
97
98
99
00
14.6 31.2
14.4 32.5
13.6 31.8
11.5 27.0
11.8 27.9
13.1 30.9
25.4
25.7
23.2
19.2
19.8
40.2
39.7
38.4
35.2
30.3
28.7
29.4
45.9
44.8
22.7
South Korea 01 02 03
04
05
06
07
08
12.0 27.8
11.5 26.9
12.0 29.1
12.9 32.7
14.7 35.7
16.1 38.5
16.7 39.4
19.5 44.2
20.3
18.8
18.3
19.0
20.6
22.3
23.5
24.6
29.1
33.8
35.0
31.6
28.3
29.3
30.2
31.2
31.4
31.0
30.4
24.9
23.8
26.7
27.2
24.9
23.9
25.9
26.9
28.3
29.2
29.0
43.1
30.4
33.2
34.3
31.1
32.0
31.2
33.6
34.9
36.3
38.4
39.2
22.6
21.7
20.9
19.8
23.5
19.7
18.3
19.1
21.4
22.8
23.5
24.5
28.0
28.1
31.9
31.0
22.9
25.7
37.6
32.9
30.8
36.3
40.7
51.0
61.2
63.8
82.0
29.7 28.7
28.8 29.3
27.7 28.0
23.3 22.9
23.5 23.7
28.0 25.5
25.4 23.7
23.1 23.4
26.3 25.3
31.8 28.5
35.8 32.3
39.5 34.3
41.4 34.9
48.1 37.4
31.0
31.5
29.9
25.0
24.7
25.4
24.1
24.2
25.5
26.7
29.3
30.7
29.8
32.5
26.4 34.4
27.9 36.3
27.8 35.5
24.4 29.7
23.8 30.9
23.9 29.5
21.7 27.5
22.0 27.8
25.0 29.5
31.5 32.1
33.5 35.1
38.0 36.8
40.8 37.2
48.8 36.8
83.2 25.3
87.4 26.4
86.7 27.3
67.7 24.4
62.1 25.3
60.6 25.6
52.7 23.9
48.1 24.5
47.0 25.0
46.3 27.0
46.5 29.2
43.8 31.3
41.7 32.6
41.1 34.4
31.7 11.5
32.6 12.1
30.4 12.2
24.9 9.6
26.6 10.2
28.3 12.6
26.0 11.3
26.2 10.8
26.9 11.8
29.8 13.4
32.0 15.3
34.2 16.8
34.5 17.5
32.2 19.2
Source: Own calculations based on data from WIOD. Note: Data calculated in 2008 US constant dollars. Nec = Not elsewhere classified.
In the Brazilian economy, unlike in South Korea, the manufacturing sector fell apart
during the so-called lost decade in the 1980s. Moreover, the restrictive neoliberal economic
122
policy grounded in market-friendly mechanisms led to a process of premature de-
industrialisation without an end in sight. In this dynamic, industrial restructuring involved mainly defensive adjustments in a context where investments were kept to a minimum level.
Thus, the productive fragmentation seeking cost savings was widely adopted without any long-term economic planning. Additionally, under high and volatile interest and exchange
rates, in periods of demand expansion (as during the 2000s), substitution of national inputs for
imported ones constituted the easiest way to attend the demand. By analysing the import input coefficients, it is possible to realise the dependence of the Brazilian domestic industry in
relation to the international supply and the progressive loss of density in its industrial chains.
A gradual shift to free-market policies intensified the presence of imported inputs for the domestic industry.
Table 3.5 - Import input coefficients for Brazil, 1995-2008 Sectors Primary Sector Manufacturing Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Services
95
96
97
98
99
00
Brazil 01 02
03
04
05
06
07
08
3.7 6.9
4.0 7.4
4.1 7.6
4.1 7.4
3.9 6.9
4.5 8.5
4.6 8.5
4.4 7.5
4.6 7.8
5.3 9.0
5.6 9.9
5.9 11.1
7.1 12.7
9.4 16.1
4.7
5.7
5.9
5.5
4.9
5.6
5.1
4.6
5.0
5.0
5.5
6.0
7.2
9.6
6.5
5.7
6.2
6.2
5.6
6.4
6.2
5.7
5.5
6.0
6.3
7.6
9.1
10.5
7.1
6.8
7.3
7.1
6.5
7.7
7.5
6.3
6.1
7.2
6.8
7.6
9.2
10.9
2.7
2.9
3.1
3.1
2.9
3.5
3.5
3.5
3.7
4.7
4.9
5.2
6.3
8.2
7.6
7.6
8.1
8.3
7.4
8.8
8.2
7.1
6.5
7.0
7.5
7.8
9.3
10.8
10.0
11.7
10.5
8.2
8.3
11.5
11.2
9.8
10.3
14.1
15.9
18.9
21.6
26.5
6.1 8.4
7.0 8.7
7.2 9.1
6.9 9.2
6.8 9.1
9.4 11.1
9.3 10.6
8.5 9.2
9.4 10.3
11.3 11.6
10.9 12.3
11.4 13.1
13.9 15.3
18.9 18.5
6.9
6.6
6.9
7.2
6.3
6.9
7.8
6.0
6.5
6.5
6.8
8.0
9.5
12.7
6.6 7.2
6.1 7.1
6.5 7.8
6.7 8.2
6.1 7.4
6.5 8.7
6.7 9.4
6.5 8.2
6.3 8.3
7.2 8.8
8.8 10.1
10.6 11.5
12.2 12.8
15.6 15.2
8.7 8.7
9.2 8.9
9.8 9.9
10.0 10.5
9.9 10.0
12.9 11.8
12.7 13.2
12.1 11.5
11.4 11.5
13.3 12.5
15.3 14.0
17.2 15.2
16.2 16.6
21.8 19.8
5.9 3.0
5.9 3.2
6.3 3.4
6.6 3.5
6.1 3.1
7.0 3.8
6.7 3.8
5.7 3.3
5.9 2.9
6.5 3.1
6.7 3.6
7.3 4.0
8.3 4.5
10.6 5.4
Source: Own calculations based on data from WIOD. Note: Data calculated in 2008 US constant dollars. Nec = Not elsewhere classified.
123
From 1995 to 1999, the rising trend of import input coefficients appeared blurred.
However, from this period onwards these coefficients raised almost constantly. Furthermore,
particularly after 2002, this process gained speed essentially due the economic recovery (pushed by the commodity boom) and the structural mismatch between the structures of
supply and demand. The most representative examples of subsectors that showed a substantial rising trajectory of imported inputs were ‘coke, refined petroleum and nuclear fuel’,
‘chemicals and chemical products’, ‘rubber and plastics’, ‘electrical and optical equipment’ and ‘transport equipment’. Additionally, it is important to note that the most affected manufacturing subsectors were those which formed part of the medium- and the high-tech
groups. In this sense, it is not by chance that the Brazilian economy has not structured the
basis for a long-term economic growth. In fact, the only achievement of the Brazilian economic policy has been the establishment of successive short cycles of ‘stop and go’, arising from a decreasing share of manufacturing in the value-added and the disarticulation of domestic industrial chains especially in medium- and high-tech subsectors. 5. Concluding remarks This empirical chapter sought to provide an understanding of the structural transition
undertaken by Brazil and South Korea from a comparative perspective. Therefore, the first
section, through the methodology of Imbs and Wacziarg, analysed the pattern of inter and
intra-sectoral diversification presented by these economies before and after the 1980s. Firstly the data showed that Brazil was affected by a process of premature specialisation at the interand the intra-sectoral levels. Secondly, the intra-sectoral data of manufacturing revealed that
during the specialisation stage South Korea increased sharply the share of medium- and highsectors in the economy, while Brazil, although more diversified, remained dependent on less
dynamic sectors. From a comparative perspective of economic development, this dichotomy propelled different processes of cumulative causation and, consequently, impacted the countries’ growth rates distinctly. Therefore, it is not by coincidence that the constant drop of
the Brazilian share in the global manufacturing was followed by a regressive evolution in the global GDP. Consequently, Brazil remained trapped in a middle-income landscape resulting in an unsustainable economic performance.
In the second and third section, the analysis turned to the understanding of factors
(demand, trade and technological change) that contributed to the formation of these
124
productive structures in light of liberalising policies implemented during the second half of
1990s. Thus, from 1995 to 2002 during the height of neoliberal reforms, Brazil increased its
manufacturing output by only 9.1%. In this period, with the exception of exports, all
components registered negative variations. In a distinct economic dynamism, the South
Korean manufacturing production increased by 58.3% of which 50.7% was explained by exports. Furthermore, this expansion was composed mainly by medium- and high-tech industries. In the subsequent period, from 2003 to 2008, South Korea maintained
manufacturing as an engine of economic growth but with an significant increase of imports
mainly due to the ‘flying geese’ movement of regional productive fragmentation marked
specially by the rise of China as the world's factory. While the South Korean pattern of economic development was in both periods (before and after 2003) driven by exports of manufacturing products, in Brazil from 2003 to 2008 economic growth was mainly propelled by domestic demand fuelled by the credit-led consumption of the period. In this dynamic, the
so-called commodity prices boom also played a central role to boost the economy. However,
even in this context, once again manufacturing performed worse when compared to services, which presented the most dynamic output growth.
In the fourth section, the density of domestic industrial chains through imported input
coefficients was measured. In South Korea, from 1995 to 2002, the productive structure sketched movements related to an increasing share of imported inputs in the domestic
manufacturing sector that were consolidated in the subsequent period. From 2003 to 2008, the South Korean economy significantly increased the share of imported inputs not only in the
manufacturing sector but also in the economy as a whole. This finding is consistent with the aforementioned ‘flying geese’ process of industrialisation where the productivity capacity at a
certain stage of the economic development is transferred to the less developed country (in this case particularly China) in a process of regional fragmentation of the productive chain. In
contrast, Brazil did not follow this pattern of economic development. As a matter of fact, the manufacturing sector fell apart during the 1980s and 1990s in a process of premature de-
industrialisation without an end in sight. In this productive disarticulation, many manufacturing industries kept investments to a minimum level. Furthermore, the productive fragmentation seeking cost savings per se was widely adopted without any long-term
economic planning. Additionally, under high and volatile interest and exchange rates, in
periods of demand expansion (as during the 2000s), substitution of national inputs for
imported ones constituted the easiest way to meet the demand. This fact not only revealed the 125
dependence of the Brazilian domestic industry in relation to international supply but also the absence of important intra-sectoral linkages.
126
Appendix 3.1 – Technical Details Lowess Methodology and the U-shaped curve Analogously to the procedure adopted in Imbs & Wacziarg (2003), the study employs a non-
parametric methodology based on locally robust weighted scatter plot smoothing (LOWESS)138. In this procedure, each estimate
is a function of the
’s in the
neighbourhood to be estimated, with the closest observations receiving more weight than the more distant observations. The LOWESS smoother requires specification of a span, which is the percentage or total number of observations to be included in the estimated regression at
observation . In this study the span adopted is 0.60 which means that 60 of total observations
are used in each local regression. Moreover, the LOWESS uses a tricubic weighting function with the following formula:
w = 1− Where
is the smoothed response,
(3.1)
( )
are the nearest neighbours of
span, and ( ) is the distance along the abscissa from
as defined by the
to the most distant predictor value
within the span. In the present study, as well as in Imbs & Wacziarg (2003), the response variable
corresponds to a measure of sectoral specialisation, while the independent variable
is the GDP per capita of each country (in 2005 dollars). The observations of
and
annual values of each indicator for the country under consideration. In this sense, the
are the values
estimated by the nonparametric local regression will give form to a smoothed curve (Ucurved) that connects
to
and represents the relationship between specialisation and GDP
per capita. The measure of sectoral specialisation employed is the Gini-Hirschman
index (GHI) which is obtained by taking the square root of the Hirschman-Herfindahl Index (HHI) and multiplying it by a factor of one hundred. These indexes are defined as follows:
138
HHI = ∑
(3.2)
GHI = 100. ∑
(3.3)
This method was first proposed by Cleveland (1979) and further developed by Cleveland & Devlin (1988).
127
In these equations, xij is the value-added of sector i and x is the total value-added of the
country j and n is the number of sectors. Therefore, the higher the GHI is, the more specialised the economy is. The GHI is within a certain limit value. The maximum value of the index is 100 and in this case there is only one sector in the economy. Decomposition of output growth Analogously to the method used in Chenery (1960) and Chenery et al. (1962), the so-
called Structural Decomposition Analysis (SDA) is applied following Miller and Blair’s (2009) approach. The total output is defined as: =( − Where,
) ( + )
is the matrix of domestic inputs,
(3.4)
is the domestic demand of national goods and
and +ℎ , the vector
is the exports. Considering the basic Leontief model for two periods
of gross output ( ) can be written as follows: = Where the matrix (
(
+
) and
=
(
+
)
(3.5)
) represents the Leontief matrix of direct and indirect production
=( −
coefficients defined as
) . Thus, the change in gross output between two periods
and +ℎ , can be rewritten as: =
−
=
(
+
)−
(
+
)
and D + E, and
Then through basic matrix algebraic manipulation, changes in
consequently effects on ∆ are represented as: = =(
(
+
+
)(
+
+ +
)−( )−
)(
− (
+
+
(3.6)
)
−
(3.7) −
)
(3.8)
Additionally, the equations are summarised according to the average approach. As
argued by Dietzenbacher and Los (1998) this method enhances the SDA methodology. Thus, summing
equations (3.7) and (3.8), and applying the average approach, the following
equation is obtained: = (
)(
+
+
+
)+ (
+
)(
)+ (
+
)(
)
(3.9) 128
Where the first term indicates the effects of the change in the Leontief coefficients over the change in gross output, the second term refers to the effects of the change in domestic demand, and the third, exports. =
Assuming
−
, where
is the matrix of total inputs and
is the matrix of
imported inputs, equation 3.9 can be re-written as: =
)+
(
+
(
)(
) ](
)
+
(
+
)(
+
+
) +
)
+
(−
) ](
+
+
+
(3.10)
The four components of total output change for any sector or subsector over the period
ℎ are thus calculated as follows: Domestic demand (∆ ) = ( Export (∆ ) = (
+
)(
)(
+
+
)
) ](
+
)
Import substitution (∆ ) = Technological change (∆ ) =
(− (
) ](
+
+
+
+ +
) )
The density of industrial chains Through the input-output framework, Rocha (2011) decomposed import coefficients
between inputs and final goods. In this analysis, import input coefficients by sector are and the total import input coefficient for the economy as TIIC.
defined as
Firstly define
(
)
as the matrix of direct import input coefficients: =
where
is the vector of gross output and
(3.11)
is the matrix of intermediate consumption.
Considering the Leontief matrix of direct and indirect production coefficients defined as
=( −
)
and multiplying it by
the following equation is obtained:
=
( −
)
(3.12) 129
= ∑ = ∑
(3.12) .
where and indicate each economic sector (seller and buyer, respectively) and of these sectors.
(3.12) is the total
130
Appendix 3.2 – Map of sectoral aggregation (UNIDO) Aggregation – 14 Subsectors Food, Beverages and Tobacco Food, Beverages and Tobacco Textiles and Textile Products Textiles and Textile Products Leather, leather products and footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Basic Metals and Fabricated Metal Machinery Machinery Electrical and Optical Equipment Machinery Electrical and Optical Equipment Transport equipment Transport equipment Manufacturing, Nec; Recycling Manufacturing, Nec; Recycling Total manufacturing Source: Elaborated by the author. Note: Nec = Not elsewhere classified.
UNIDO Database – 23 subsectors Food and beverages Tobacco products Textiles Wearing apparel, fur Leather, leather products and footwear Wood products (excl. furniture) Paper and paper products Printing and publishing Coke, refined petroleum products, nuclear fuel Chemicals and chemical products Rubber and plastics products Non-metallic mineral products Basic metals Fabricated metal products Machinery and equipment n.e.c. Office, accounting and computing machinery Electrical machinery and apparatus Radio, television and communication equipment Medical, precision and optical instruments Motor vehicles, trailers, semi-trailers Other transport equipment Furniture; manufacturing n.e.c. Recycling Total manufacturing
131
Appendix 3.3 – Map of sectoral aggregation (ECLAC-PADI) Aggregation – 14 Subsectors Food, Beverages and Tobacco Food, Beverages and Tobacco Food, Beverages and Tobacco Textiles and Textile Products Textiles and Textile Products Leather, Leather and Footwear Leather, Leather and Footwear Wood and Products of Wood and Cork Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Pulp, Paper, Paper , Printing and Publishing Chemicals and Chemical Products Chemicals and Chemical Products Coke, Refined Petroleum and Nuclear Fuel Coke, Refined Petroleum and Nuclear Fuel Rubber and Plastics Rubber and Plastics Other Non-Metallic Mineral Other Non-Metallic Mineral Other Non-Metallic Mineral Basic Metals and Fabricated Metal Basic Metals and Fabricated Metal Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Electrical and Optical Equipment Manufacturing, Nec; Recycling Total manufacturing Source: Elaborated by the author. Note: Nec = Not elsewhere classified.
ECLAC-PADI Database – 28 subsectors Food Beverages Tobacco Textiles Wearing apparel Leather products Footwear Wood products Furniture Paper and cellulose Printing and publishing Chemical industry Other chemicals Refined petroleum Petroleum and carbon products Rubber products Plastic products Ceramic Glass Other non-metallic minerals Iron and Steel Nonferrous metals Metal products Nonelectric Machinery Electric Machinery Transport Equipment Professional and scientific instruments Other Manufacturing Total Manufacturing
132
Appendix 3.4 – Classification of manufacturing subsectors by technology group Aggregation – 14 Subsectors Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling
Technology group (UNIDO) Low-Tech Low-Tech Low-Tech Low-Tech Low-Tech Medium-Tech High-Tech Medium-Tech Medium-Tech Medium-Tech High-Tech High-Tech High-Tech Low-Tech
Source: Elaborated by the Author based on Unido (2013). Note: Nec = Not elsewhere classified.
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CHAPTER 4 – ENGINES OF GROWTH AND SECTORAL INTERDEPENDENCE IN BRAZIL AND SOUTH KOREA “Ordinarily economists have been content with general references to the advantages of external economies, complementarities, cumulative causation, etc. But no systematic effort has been made to describe how the development path ought to be modified so as to maximize these advantages even though the existence of input-output statistics supplies us with a few tools of an analysis of this kind" (Hirschman 1958, p. 100).
Introduction139 During the neoliberal decades, economic growth between Brazil and South Korea has been remarkably distinct. In Brazil, although it peaked from 2002 until the outbreak of the global financial crisis, the economy has been marked by successive “stop and go” cycles. In this
dynamic, the performance of manufacturing has been poor, while services have been
increasing as a share of GDP. The former decreased to 16% and the latter increased to 70% in 2010. From a comparative perspective, South Korea has engendered an economic growth much more sustained than Brazil. Except for the year of 1998, due to the Asian financial crisis, South Korea has shown a consistent trajectory of economic growth. In this process,
manufacturing expanded continually reaching 35% of GDP in 2010140. These divergent dynamics of economic growth and sectoral structures are likely to be closely related to each other141.
In the developmental literature, manufacturing is traditionally regarded to play a
special role as engine of economic growth. In this sense, poor manufacturing performance would imply in deleterious effects in sustainable economic growth. The Structuralist-
Kaldorian rationale behind this dynamic is the existence of increasing returns to scale that is at the heart of cumulative causation processes. Additionally, learning by doing, spill-over effects and intra-sectoral linkages are considered particularly stronger in manufacturing. In a I would like to thank Guilherme Magacho and Joaquim Guilhoto for their helpful comments on this chapter. Data calculated in current US dollars. 141 The loss of the Brazilian economic dynamism is associated to the process of negative de-industrialisation. For a detailed distinction between the process of natural and the so-called negative de-industrialisation, see chapter 1 (section 2.2). 139 140
134
Schumpeterian sense, manufacturing has been also recognised as the main engine of
technological dynamism and specifically a locus of innovation. From this perspective, it is argued that technological change is mainly triggered and diffused from the manufacturing sector.
Nevertheless, recently the capacity of services to act as an engine of economic growth
has attracted considerable interest in academic and policy circles. According to this type of
narrative, services and manufacturing have been increasingly combined through a synergistic and symbiotic relationship that raised the share of services in the economy (Pilat & Wolfl,
2005; Pilat et al. 2006; Lodefalk, 2010; Nordås & Kim, 2013). Additionally, many studies have shown that manufacturing has been using more intermediate services over the years. In
this sense, the share of services in manufacturing value-added has been increasing steadily,
surpassing 60% in middle-income countries and 65% in high-income countries (CNI, 2014). Although these inter and intra-industrial relationships reveal an increasing importance of services in the economy, their role is still more limited than those of the manufacturing sector (Park & Chan, 1989).
Therefore, in this context, the chapter uses principally input-output methodologies to
compare the Brazilian and South Korean productive structures in terms of productive dynamisms and leading sectors. Moreover, aspects regarding the interdependence of the
manufacturing and services are also investigated. The contributions of this chapter are twofold. First, the analysis employs the input-output methodology to identify key sectors in
both economies. This analysis provides a useful framework to understand specificities and
regularities of each economy and methodological referential for further empirical studies
about sectoral specificity of growth. Second, this chapter estimates the interdependence between services and manufacturing through a new input-output methodology. Therefore, this
study advances some findings presented by the literature and opens an interesting window for future research.
The chapter is organised as follows. Section 1 provides a brief discussion about the
relevance of industrial linkages for economic growth, based mainly on Hirschman’s theory.
Section 2, from a comparative analysis between Brazil and South Korea, measures the output
multipliers, Hirschman-Rasmussen backward and forward indices, as well as pure normalised
indices comprising all productive subsectors of manufacturing, services and the primary 135
sector. Section 3 analyses the interdependence between manufacturing and services. Concluding remarks are provided in Section 4.
1. The relevance of industrial linkages: a Hirschmanian perspective Albert Hirschman through the study The Strategy of Economic Development (1958)
provided the first solid critique of the ‘balanced growth’ approach proposed by Nurkse and
Rosenstein-Rodan142. According to him, the ‘balanced growth’ theory is not only impractical
but also does not capture the nature of the development process. Therefore, as stated by Hirschman (1958), economic growth is essentially an unbalanced dynamic process, in which successive disequilibria produce the conditions for development in different sectors. In this sense, growth proceeds as a ‘series of uneven advances of one sector followed by the catching-up of other sectors’ (ibid, p.63).
As pointed out by Toner (1999), Hirschman made a number of important contributions
to the theory of economic development. First, Hirschman detailed the industrial structure to
explain the development process in an intra-sectoral analysis. Second, input-output methods were adopted to analyse sectors and subsectors. Third, input-output multipliers were seen as providing
a
means
of
quantifying
pecuniary
externalities
arising
from
demand and supply interactions. Last but not least, the orientation of final demand by the state was viewed as the best way to alter the industrial structure by creating strong inducements to
domestic investments in selected manufacturing subsectors. The criterion for such decisions
was based on the capacity of a given subsector to generate externalities which act to induce investments in other subsectors in a circular and cumulative chain. In this dynamic,
manufacturing plays a central whole since the primary sector has very limited linkages with other sectors.
In Hirschman’s thinking, the state is a central agent to direct investments toward
dynamic manufacturing subsectors, which posses the strongest linkages with the rest of the economy. In this framework, linkages are responsible for providing necessary means for the expansion of domestic demand and supply. Thus, Hirschman defines an underdeveloped
economy by its absence of linkages or inter- and intra-sectoral interdependences. Consequently, an underdeveloped economy is characterised by a very large leakage of 142
For a detailed explanation about these theoretical approaches see chapter 1.
136
demand for both intermediate and final goods into imports. Moreover, in an underdeveloped industrial structure, cumulative expansion in demand and supply resulting from investments
in intermediate and capital goods are restricted due to the lack of dynamic industrial linkages. Therefore, the main aim of the economic growth process is to develop an interdependent industrial structure.
The extent of backward and forward linkages in a productive structure determines the
size of the stimulus to an economy though a given expansion in final demand. Hirschman, on
the one hand, explains that backward linkages are related to derived demand, i.e. the provision
of input for a given sector. According to him, every non-primary economic sector will induce attempts to supply through domestic production the inputs needed in that sector. On the other
hand, forward linkages will induce attempts to utilise outputs as inputs in some new activities (Hirschman, 1958, p.100). Tregenna (2009, p.143), argues that forward linkages can raise overall economic growth, increasing the capacity utilisation, technological upgrading and
productivity in downstream sectors. However, Hirschman states that backward linkage is the dominant form of linkage. In his words, “forward linkage could never occur in pure form. It
must always be accompanied by backward linkage which is the result of the pressure of demand. In other words, the existence or anticipation of demand is a condition for forward
linkage effects to manifest themselves”. Unlike backward linkages, forward linkages cannot
therefore be regarded as an independent inducement mechanism (Hirschman, 1958, p.116117).
In this framework, manufacturing is referred to as a sector with special properties in
terms of strong backward and forward linkages. Hirschman states that the significance of
manufacturing for development is that there is a close correlation between income per capita and the proportion of people occupied in manufacturing. Additionally, in his view, from a
growth perspective manufacturing is superior to the primary sector not as a result of higher
productivity but rather because linkages that agriculture and mining have to the rest of the
economy are lower than those that manufacturing has. In this way, the author points out that, for instance, mining in underdeveloped countries usually culminates in an enclave problem
since “exports slip out the country without leaving much of a trace in the rest of the economy143” (ibid, p.110).
143
Hirschman does not mention the services sector in this analysis.
137
Based on this theoretical background, the following section presents the forward and
backward linkages for the Brazilian and South Korean economies as a whole, i.e. covering the primary sector, manufacturing and services. The study used input-output analyses to
investigate the capacity of sectors and subsectors to promote economic growth. This
methodology is useful because these models incorporate inter-relationships between various
sectors in terms of linkages. Using this method, it is possible to empirically investigate the economic role of a productive sector without restricting the analysis to its “direct effects” on
the economy regarding generating production, employment, value-added, tax revenue, and exports. This analysis, also considers “indirect effects”, i.e. effects that a given sector exerts
over other sectors through channels established by transactions of inputs and outputs between different economic sectors.
2. Output Multipliers and Hirschman-Rasmussen Linkages144 2.1.Output Multiplier The analysis of engines of growth in Brazil and South Korea is assessed through the
use of input-output methods. Initially, simple output multipliers and Hirschman-Rasmussen
indices are calculated and analysed. The output multiplier indicates how much is produced for
each monetary unit spent on final demand. These multipliers incorporate direct and indirect
effects to measure the impact of a demand shock on the economy. For the purposes of this
analysis, multipliers are used only considering linkage effects restricted to demand for intermediate inputs, that is, without making household demand endogenous to the
model145.Moreover, the data was compiled in two periods, namely 1995-2002 and 2003-2009, for both countries.
As shown by Table 4.1, the output multipliers are significantly different among
countries both in terms of absolute and relative magnitudes. From 1995 to 2002, South Korea presented higher output multipliers for the majority of subsectors, particularly in
manufacturing. The exceptions were ‘Mining’, Petroleum and Nuclear Fuel’ and a few
services subsectors such as ‘Financial Services’, ‘Business Services’, ‘Public Admin’, ‘Health and Education’, ‘Utilities’ and ‘Construction’. In the subsequent period, i.e. from 2003 to Technical details on methodology are summarised in Appendix 4.1. This type of multiplier is recognised as type I. Models that present household demand endogenised in the system and induced effects provide type II multipliers (Guilhoto, 2009). 144 145
138
2009 South Korea increased its output multipliers with only four sectors with lower
multipliers than Brazil. In this sense, only ‘Mining’, Petroleum and Nuclear Fuel’, ‘Utilities’ and ‘Transport Services’ had a higher output multiplier in Brazil. Table 4.1 - Output Multipliers Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
South Korea Brazil 1995-2002 2003-2009 1995-2002 2003-2009 Mult Rank Mult Rank Mult Rank Mult Rank 1.67 1.44 2.21 2.38 2.45 2.05 2.20 1.17 2.09 2.20 2.30 2.02 2.52 3.07 2.44 2.36 1.59 1.90 1.66 1.73 1.70 1.67 1.53 1.40 1.46
18 23 8 5 3 12 9 25 11 10 7 13 2 1 4 6 20 14 19 15 16 17 21 24 22
1.71 1.55 2.26 2.18 2.33 2.04 2.15 1.21 2.08 2.20 2.11 2.18 2.39 2.16 2.53 2.40 1.57 2.00 1.65 1.74 1.62 1.64 1.61 1.48 1.54
16 22 5 8 4 13 10 25 12 6 11 7 3 9 1 2 21 14 17 15 19 18 20 24 23
1.59 1.50 2.13 1.94 2.15 1.66 2.01 2.12 1.82 1.94 1.88 1.72 2.04 2.05 2.11 1.97 1.69 1.92 1.35 1.51 1.55 1.69 1.66 1.48 1.53
19 23 2 9 1 18 7 3 13 10 12 14 6 5 4 8 16 11 25 22 20 15 17 24 21
1.67 1.66 2.26 1.93 2.14 1.88 1.92 2.27 2.05 2.06 1.93 1.90 2.10 1.98 2.24 1.91 1.70 1.75 1.40 1.51 1.66 1.56 1.57 1.48 1.51
17 19 2 9 4 14 11 1 7 6 10 13 5 8 3 12 16 15 25 23 18 21 20 24 22
Source: Author's own elaboration based on WIOD tables. Note: Data calculated in 2008 US constant dollars. ‘Mult’ = Output Multipliers and “Rank’ = Ranking. Nec = Not elsewhere classified.
The aforementioned ‘landscape’ indicates that the South Korean subsectors are more
interrelated to each other than the Brazilian ones are and, consequently, an increase in final
demand in South Korea has a higher impact on the domestic economy than that in Brazil.
Additionally, as shown by Table 4.1, except for ‘Petroleum and Nuclear Fuel’, all manufacturing subsectors in South Korea have a multiplier higher than 2.00. This numbers
139
indicates that for both periods, the South Korean manufacturing sector is able to more than double its output given a unitary increase in demand. Distinctly, Brazil showed this dynamism in only a few manufacturing sectors and with some shifts between 1995-2002 and 2003-2009.
Therefore, from 1995 to 2002, the subsectors with highest capacity (with a multiplier higher than 2.00) to increase output in face of a demand rise were ‘Leather and Footwear’, ‘Food and Beverages’, ‘Petroleum and Nuclear Fuel’, ‘Transport Equipment’, ‘Electrical and Optical
Equipment’, ‘Machinery’ and ‘Paper, Printing and Publishing’. From 2003 to 2009, the subsectors of ‘Paper, Printing and Publishing’ and ‘Electrical and Optical Equipment’ left this
group while ‘Rubber and Plastics’ and ‘Chemicals’ showed output multipliers of 2.06 and 2.05 respectively.
2.2.Hirschman-Rasmussen Linkages The results of the previous analysis of output multipliers can be complemented by the
Hirschman-Rasmussen Linkages (Figure 4.1). The seminal works of Hirschman (1958) and
Rasmussen (1956) gave rise to a wide range of studies attempting to investigate interrelationships between sectors, i.e. backward and forward linkage effects in a given
economic structure146. The Backward Linkage (BL) index indicates the extent to which a given sector demands from other sectors. In other words, it measures the capacity of a
hypothetical sector to stimulate the output of other sectors. The Forward Linkage (FL) index, in turn, measures the extension to which a given sector is demanded by other sectors, i.e. the importance of a hypothetical sector as an input supplier. In this sense, these indices allow the
investigation of productive structures in detail and identify sectors that depend on inter- and
intra-sectoral supply and inter- and intra-sectoral demand or those that are relatively independent from other sectors147.
In this way, as shown by Figure 4.1, South Korean and Brazilian subsectors are
classified into the following four groups depending on their indices values: (i) located in the
lower-left are subsectors that expose both BL and FL indices lower than 1, and consequently These indices were first presented by Hirschman (1958) with a particular interest in Latin American economies. It was based on his experiences as an official advisor and private consultant in Colombia in the first half of the 1950s (Hirschman, 1984). 147 The backward and forward linkages for Brazil and South Korea are presented in terms of averages from 1995 to 2009 since the focus of this chapter is the comparison between sectors/subsectors and not the tendency over time. Moreover, subsectors did not expose significant changes in terms of quadrants. Tables for backward and forward linkages for each year are presented in the appendices 4.2, 4.3, 4.4 and 4.5. 146
140
are highly independent from other subsectors; (ii) located in the upper-right are subsectors with both linkages higher than 1, denoting subsectors that are strongly dependent on other
sectors in terms of both supply and demand of inputs; (iii) located in the lower-right are subsectors that presents only BL indices greater than 1 and are strongly dependent on inter-
and intra-sectoral supply (or stimulate production in other sectors); and (iv) located in the upper-left are subsectors that present only FL greater than 1 and are strongly dependent on inter- and intra-sectoral demand (or dependent on the production of other sectors). Figure 4.1 – Hirschman-Rasmussen BL and FL indices (Average 1995-2009) South Korea Min FL
1.70 1.50
Bs
1.10
Pnf
Sal
Trs
0.70 0.50
Pa
0.60
0.70
Tex
Con
He
0.80
Rp Te
Ts
0.90
1.00
Fb
Lf
Min Ut
1.30
Nmm
Ch
Ag
Fs
0.90
0.30
Wp
Ut
1.50
Ppp
Bm
1.30
Brazil
1.70
Man Mac
BL
1.10
Sal
0.90
Eoe
1.20
1.30
1.40
Tex
Con
Pa
0.60
0.70
0.80
0.90
1.00
PnF
Ch
Te
He
0.70
0.30
Bs
Rp Nmm Ppp
Ts
0.50
1.10
Bm Wp Ag Trs Fs
FL
Eoe
Man
1.10
Lf
1.20
BL
Fb Mac
1.30
1.40
Source: Author's own elaboration based on WIOD tables. Note: Data calculated in 2008 US constant dollars. Colours: Black dots = manufacturing, green dots = primary sector and, orange dots = services. Ag = ‘Agriculture’, Min = ‘Mining’, Fb = ‘Food and Beverages’, Tex = ‘Textiles’, Lf = ‘Leather and Footwear’, Wp = ‘Wood and Products of Wood’, Ppp = ‘Paper, Printing and Publishing’, Pnf = ‘Petroleum and Nuclear Fuel’, Ch = ‘Chemicals’, Rp = ‘Rubber and Plastics’, Nmm = ‘Other Non-Metallic Mineral’, Bm = ‘Basic Metals and Fabricated Metal’, Mac = ‘Machinery’, Eoe = ‘Electrical and Optical Equipment’, Te = ‘Transport Equipment’, Man = ‘Manufacturing, Nec’, Ut = ‘Utilities’, Con = ‘Construction’, Sal = ‘Sales’, Ts = ‘Traditional Services’, Trs = ‘Transport Services’, Fs = ‘Financial Services’, Bs = ‘Business Services’, Pa = ‘Public Admin’, and He = ‘Health and Education’.
The inter- and intra-sectoral dependence both in terms of supply and demand varies
between countries. In the case of South Korea, located in the upper-right quadrant, there are six manufacturing subsectors characterised by a strong dependence on other sectors in terms
of both supply and demand of inputs. These ones are ‘Basic Metals and Fabricated Metal’, 141
‘Paper, Printing and Publishing’, ‘Other Non-Metallic Mineral’, ‘Rubber and Plastics’,
‘Chemicals’ and ‘Wood and Products of Wood’. By contrast, Brazil does not present the same
composition. Thus, as seen in Figure 4.1, ‘Basic Metals and Fabricated Metal’ and ‘Wood and Products of Wood’ are not situated in this quadrant. Moreover, ‘Petroleum and Nuclear Fuel’,
which is situated in this quadrant, showed one of the highest BL linkages of the Brazilian economy148. Distinct to mining and agriculture, a large portion of petroleum is consumed
domestically supplying inputs for manufacturing149. For instance, the main industrialised products of the ‘Chemicals’, ‘Rubber and Plastics’ and ‘Textiles’ subsectors demand inputs originating in the ‘Petroleum’ subsector. Additionally, this sector demands inputs significantly from the machinery industry for the refining process.
Regarding the lower-right quadrant, except for ‘Construction’ in the Brazilian
economy150, both countries had the same manufacturing subsectors, i.e. ‘Transport Equipment’, ‘Textiles’, ‘Food and Beverages’, ‘Manufacturing, Nec’, ‘Machinery’, ‘Leather and Footwear’ and ‘Electrical and Optical Equipment’. Although Hirschman had anticipated the special growth-enhancing properties of manufacturing, the figure 4.1 shows that the
majority of medium- and high-tech subsectors are presented in the lower-right quadrant. It
indicates not only that technologically advanced subsectors are very dependent on the inter-
and intra-sectoral supply, but also that they stimulate production in other sectors.
Additionally, the biggest difference between the Brazilian and South Korean linkages refers to their levels. As a matter of fact, South Korea presented an economy with higher backward and forward linkages indicating a more dynamic productive structure.
In the lower-left quadrant there are no manufacturing subsectors (backward and
forward linkages lower than the unity). This result indicates that manufacturing subsectors are generally more inter-related to other sectors, particularly in pulling the domestic productive
chain, than the primary sector or services. In fact, in both countries this area is filled exclusively by services. In South Korea and Brazil it comprised respectively five and three subsectors. The former was represented by ‘Sales’, ‘Traditional Services’, ‘Transport
The highest increase in linkage indices in this sector was registered from 2004-2006, during which Brazil became self-sufficient in oil production. For details on this series, see appendices 4.2, 4.3, 4.4 and 4.5. 149 As it is possible to realise by analysing the national accounts, Brazilian petroleum is not exported as a raw material, as are mineral commodities. According to the national accounts, Brazilian exports of petroleum and natural gas were 21.3% of the total production in 2009, whereas in the case of iron, 90.2% of the total production was exported. 150 Construction presented a BL linkage of exactly 1.00. Therefore it is not clear which quadrant this subsector belongs to. 148
142
Services’, ‘Health and Education’, and ‘Public Admin’. The latter included the same
subsectors, with the exception of ‘Sales’ and ‘Transport Services’. In this manner, as a general
picture, services have showed a high independence from other subsectors both in terms of supply and demand. In the upper-left quadrant, subsectors characterised by high dependence
on the production of other sectors are presented. These subsectors usually are characterised by the primary sector such as ‘Mining and ‘Agriculture’ and other subsectors marked by a lower processing level. In South Korea this quadrant revealed that sectors such as ‘Mining’ and ‘Petroleum and Nuclear Fuel’ are less interconnected with the rest of the economy than in Brazil.
2.3.Pure Normalised Backward and Forward Linkages Although Hirschman-Rasmussen indices have been widely used in input-output
analysis, they do not consider the size of sectors in the economy. Therefore, an important aspect to analyse the productive structure in Brazil and South Korea is the index
normalisation according to the sector size. Based on Guilhoto, Sonis & Hewings (1996), Table 4.2 and 4.3 were compiled in two periods and ranking positions presented according to the index size. With reference to the Pure Normalised Backward Linkage (PNBL) index, most evident dichotomies between Brazil and South Korea are twofold. First, South Korea, despite the presence of the ‘Construction’ subsector, presents important manufacturing sectors ranked as the top six. Second, in this group, high-tech manufacturing subsectors such as ‘Electrical
and Optical Equipment’, ‘Transport Equipment’, and ‘Machinery’ figure with higher pure
backward linkages than those in the Brazilian economy. Hence, it shows that in South Korea,
dynamic manufacturing sectors have been used to stimulate the production of inputs of other sectors and create a cumulative productive environment.
In Brazil, ‘Food and Beverages’ is ranked among the sectors with the highest PNBL.
Nonetheless, although this sector demands substantially from other subsectors of the economy, it is classified into the low-tech group. Moreover, taking into account the top six
subsectors, it is possible to see that the economy is also dependent on services such as
‘Traditional Services’, ‘Public Admin’ and ‘Health and Education’ to drive the economy151. Additionally, an interesting movement has been undertaken by ‘Agriculture’ and ‘Mining’.
From 1995–2002 to 2003 –2009, both subsectors increased their PNBL and improved ranking 151
Services represent nearly two thirds of the Brazilian value-added. For more details, see chapters 2 and 3.
143
positions (Table 4.2). The explanations for this phenomenon are twofold. First, it is a consequence of a significant share of the primary sectors in the Brazilian GDP. Second, it is a result of an economy articulated and still dependent on its natural resources endowments. In
short, the Brazilian productive structure indicates a significant dependence on services subsectors to stimulate the economy and also an increasing dependence on the primary sector. Table 4.2 – Pure normalised backward linkages South Korea 1995-2002 2003-2009 Subsectors PNBL Rank PNBL Rank Agriculture 0.30 16 0.22 18 Mining 0.00 25 0.00 25 Food and Beverages 1.48 7 1.07 8 Textiles 1.02 10 0.56 12 Leather and Footwear 0.24 18 0.10 22 Wood and Products of Wood 0.01 24 0.00 24 Paper , Printing and Publishing 0.14 22 0.12 21 Petroleum and Nuclear Fuel 0.18 20 0.21 19 Chemicals 0.66 12 0.75 11 Rubber and Plastics 0.26 17 0.26 16 Other Non-Metallic Mineral 0.05 23 0.05 23 Basic Metals and Fabricated Metal 0.43 13 0.49 13 Machinery 1.23 8 1.40 6 Electrical and Optical Equipment 2.44 2 2.82 3 Transport Equipment 2.37 3 3.15 2 Manufacturing, Nec 0.36 14 0.24 17 Utilities 0.15 21 0.13 20 Construction 5.04 1 4.68 1 Sales 1.66 6 1.39 7 Traditional Services 2.29 4 2.28 5 Transport Services 1.05 9 0.83 10 Financial Services 0.36 15 0.32 14 Business Services 0.20 19 0.30 15 Public Admin 1.02 11 1.07 9 Health and Education 2.05 5 2.54 4
Brazil 1995-2002 2003-2009 PNBL
0.62 0.19 3.22 0.46 0.38 0.06 0.28 0.97 0.85 0.14 0.08 0.45 0.88 0.89 1.51 0.50 0.29 2.67 0.90 2.15 0.56 0.72 0.93 2.42 2.89
Rank
14 22 1 17 19 25 21 7 12 23 24 18 11 10 6 16 20 3 9 5 15 13 8 4 2
PNBL
0.78 0.40 3.52 0.38 0.31 0.08 0.29 0.96 0.93 0.12 0.08 0.59 1.13 0.77 1.92 0.42 0.29 1.85 0.94 2.15 0.60 0.58 0.79 2.46 2.68
Rank
12 18 1 19 20 24 22 8 10 23 25 15 7 13 5 17 21 6 9 4 14 16 11 3 2
Source: Author's own elaboration based on WIOD tables. Note: Data calculated in 2008 US constant dollars. ‘PNBL’ = Pure Normalised Backward Linkage and “Rank’ = Ranking. Nec = Not elsewhere classified.
The Table 4.3 shows the results of pure normalised forward linkages (PNFL). As
expected, except for ‘Chemicals’, in both countries subsectors that produce products with a
lower degree of processing in relation to other subsectors exhibited relatively higher forward linkages. In this manner, the top six subsectors demanded by other subsectors in the South
144
Korean economy during both periods (1995-2002 and 2003-2009) were ‘Basic Metals and
Fabricated Metal’, ‘Petroleum and Nuclear Fuel’, ‘Business Services’, ‘Chemicals’, ‘Traditional Services’ and ‘Financial Services’. In the case of Brazil, ‘Sales’, ‘Agriculture’, ‘Basic Metals and Fabricated Metal’, ‘Chemicals’, ‘Traditional Services’ and ‘Business
Services’ ranked as the top six subsectors. Additionally, it is important to note that, although ‘Mining’ is characterised by a low degree of processing, it is ranked only 8th in the last period.
This position is mainly due to the low significance of this sector as a domestic supplier. In other words, a massive output share is directed to exports and consequently not processed domestically.
Table 4.3 – Pure normalised forward linkages South Korea 1995-2002 2003-2009 Subsectors PNFL Rank PNFL Rank Agriculture 1.06 8 0.84 12 Mining 0.18 20 0.12 23 Food and Beverages 0.76 11 0.76 14 Textiles 0.13 23 0.21 20 Leather and Footwear 0.04 25 0.03 25 Wood and Products of Wood 0.15 21 0.14 22 Paper , Printing and Publishing 0.74 14 0.75 15 Petroleum and Nuclear Fuel 2.45 2 1.89 5 Chemicals 2.09 4 1.92 4 Rubber and Plastics 0.78 10 0.93 10 Other Non-Metallic Mineral 0.75 13 0.72 16 Basic Metals and Fabricated Metal 4.54 1 4.52 1 Machinery 0.60 16 0.85 11 Electrical and Optical Equipment 0.32 18 0.82 13 Transport Equipment 0.32 17 0.45 17 Manufacturing, Nec 0.14 22 0.20 21 Utilities 1.01 9 1.16 8 Construction 0.60 15 0.32 18 Sales 1.36 7 1.38 7 Traditional Services 2.05 5 1.97 3 Transport Services 0.76 12 0.98 9 Financial Services 1.73 6 1.55 6 Business Services 2.12 3 2.13 2 Public Admin 0.07 24 0.07 24 Health and Education 0.24 19 0.29 19
Brazil 1995-2002 2003-2009 PNFL Rank
1.91 1.41 0.94 0.26 0.01 0.30 0.71 1.39 1.64 0.78 0.63 1.95 0.28 0.43 0.27 0.14 1.15 0.40 2.87 1.67 1.37 1.38 1.91 0.14 1.07
4 7 13 22 25 19 15 8 6 14 16 2 20 17 21 23 11 18 1 5 10 9 3 24 12
PNFL Rank
2.04 1.46 0.84 0.21 0.01 0.21 0.67 1.37 1.53 0.68 0.54 1.77 0.23 0.41 0.30 0.11 1.28 0.43 2.96 1.92 1.26 1.51 2.02 0.14 1.12
2 8 13 21 25 22 15 9 6 14 16 5 20 18 19 24 10 17 1 4 11 7 3 23 12
Source: Author's own elaboration based on WIOD tables. Note: Data calculated in 2008 US constant dollars. ‘PNFL’ = Pure Normalised Forward Linkage and “Rank’ = Ranking. Nec = Not elsewhere classified.
145
3. The interdependence between manufacturing and services The increasing share of services in middle-income countries has been studied in the
economic development literature. The analysis made by Rowthorn & Wells (1987), and more recently by Palma (2005), Dasgupta & Singh (2006) and Tregenna (2009), addresses this phenomenon through the classical de-industrialisation approach. In this line of thinking, countries follow a broadly similar trajectory of economic development. As development gets
under way, in low-income countries, the share of the primary sector in the economy’s total value-added and employment fall and there is a rapid increase in the share of manufacturing.
This process takes place until the economy reaches a certain level of per capita income152. From this stage, manufacturing stabilises and then starts to fall back, taking the form of an ‘inverted-U’ curve. This trend is also followed by a corresponding increase in the share of
services in national employment and value-added and is often described as a natural process
of de-industrialisation. Nevertheless, some developing economies seem to present an anomaly, i.e. a process of premature de-industrialisation153. For instance, on the one hand, the Brazilian share of services in GDP of nearly 70% is similar to that of countries with much
higher incomes per capita. On the other hand, In South Korea, whose income per capita is at least 2.5 times larger than in Brazil, services account for 54% of the GDP154.
This rising trend of services in GDP has stimulated not only a number of hypotheses to
explain the fall in manufacturing155, but particularly also studies that sought to investigate the interdependence between manufacturing and services. According to this type of study, services and manufacturing have been increasingly combined through a synergistic and
symbiotic relationship. In this way, Pisano & Shih (2009) state that manufacturing and services share a collective pool of resources (industrial commons) that sustains innovative
process. Therefore, it is not mere coincidence that many studies have shown that
manufacturing has been using more intermediate services over the years. In this new productive landscape, the share of services in manufacturing value-added has been increasing
152
According to Rowthorn & Wells (1987), considering a sample of 70 countries, this level would be around US$12,000 in 1991. 153 For details on the process of de-industrialisation, see chapter 1. 154 Data calculated for 2010 in current US dollars. 155 For a detailed explanation about the three better-known hypotheses about de-industrialisation, see chapter 1.
146
steadily, surpassing 60% in middle-income countries and 65% in high-income countries (CNI, 2014)156.
Figure 4.2 compares the intermediate consumption of services in manufacturing value-
added for two periods in order to indentify an increasing evolution. As it is clear, although these countries showed a distinct trend in terms of sectoral composition over the decades, both
presented an increasing trend of services in manufacturing value-added. From a comparative perspective, Brazil presented a higher share of services in its manufacturing value-added than
South Korea. In numbers, comparing the averages for 1995 to 2009, Brazil and South Korea
showed respectively 40.37% and 38.51% of intermediate services in the manufacturing valueadded. Through this data it is also possible to identify a distinct evolution over time. During
the first period (1995 – 2002), South Korea presented a ratio of intermediate consumption of services to manufacturing value-added of 37.19% and Brazil 35.78%. In the subsequent
period (2003-2009), not only did both countries expose a rising trend, but Brazil also surpassed South Korea considerably. The former reached 45.62% and the latter 40.03%.
Figure 4.2 – Intermediate consumption of services in manufacturing value-added (%) South Korea
50
50
48
48
46
46
44
42
40 36 34
40.03 37.19
40 38.51
36 32
1995-2002
2003-2009
1995-2009
40.37
38 34
32 30
45.62
44
42 38
Brazil
30
35.78
1995-2002
2003-2009
1995-2009
Source: Author's own elaboration based on WIOD tables.
3.1. Opening intersectoral linkages As mentioned previously, distinctions in terms of growth-enhancing effects between
manufacturing and services have blurred. In this context, although Brazil and South Korea undertook distinct sectoral evolutions in GDP over the years, both countries have increased 156
See also Arbache (2015).
147
the ratio of services in manufacturing value-added. This information is in line with pure normalised linkages presented in the previous section that showed an increasing relevance of services in
the Brazilian and South Korean productive structures. Therefore, in order to
clarify this supposed new trend, this section adopted once again the input-output methodology to understand the intersectoral interdependence between manufacturing and services. For this
purpose, in a new methodological approach, each sectoral forward and backward linkage index was decomposed. The idea is to understand the extension to which a given linkage is
composed by the primary sector and principally manufacturing and services. Both backward and forward linkages were decomposed in terms of percentage shares. 3.1.1. Forward Linkage decomposition As mentioned in Section 2.2, the forward linkage measures the extension to which a
given sector is demanded by other sectors, i.e. the importance of a hypothetical sector as an
input supplier. In Figure 4.3 it is possible to see the forward linkage decomposition for two periods, 1995–2002 and 2003 –2009. The main findings are twofold. First, the linkage composition, i.e. sectoral shares, did not vary significantly between the periods analysed.
Second, the data illustrated that in both countries, despite a considerable share of services in
GDP, its role is still more limited than those of the manufacturing sector157. In South Korea, where services represented more than 50% of the GDP, about 50% of the services forward
linkage is represented by manufacturing. In other words, 50% of services supply is destined to
manufacturing. This relationship is distinct in the manufacturing sector. As showed clearly by the manufacturing forward linkage, only approximately 25% of the manufacturing intersectoral supply is destined to services.
In the Brazilian case, this distinct inter-sectoral dependence is even clearer. In Brazil,
even in a context where services represent 70% of the total value-added, services are more
dependent on manufacturing than vice versa. Data shows that the services forward linkage is made up of manufacturing by approximately 40%. This means that 40% of services supply is
directed to manufacturing. In contrast, following the same trend observed in South Korea, a smaller share of manufacturing is directed to services. Only about 30% of manufacturing products, either inputs or outputs, are destined to services. This finding is consistent with
Walker (1985), who pointed that many services, particularly knowledge-intensive activities, 157
This finding is in line with Park & Chan (1989).
148
can only be performed with physical goods, i.e., manufacturing products, serving as inputs or outputs. The most remarkable example is the service subsector of Information and Communications Technology (ICT) that needs manufacturing products primarily to fulfil or
enable the function of information processing and communication by electronic means,
including transmission and display. Complementarily, the primary sector also showed a higher dependence on manufacturing than on services. As a matter of fact, in both countries, more than 70% of the primary sector forward linkage is represented by manufacturing. Figure 4.3 – Forward Linkage decomposition (%) South Korea FL (Manuf) 100
90 80
23.56
23.58
70
FL (Serv)
Brazil
16.56 47.92
20.72
49.17
40 30
74.42
74.72
20 10 0
90 80
29.81
29.49 55.53
60
2.02
1.71
78.57 50.22
1.86
74.99
49.23 1.60
50 40 30
66.00
64.86
4.19
5.64
39.69
20
4.88
4.29
Primary Sector
FL (Serv)
100
70
60 50
FL (Manuf)
FL (Prim)
10 0
Manufacturing
4.78
FL (Prim)
17.77
17.99
73.39
71.75
8.85
10.26
52.21
41.11 6.68
Services
Source: Author's own elaboration based on WIOD tables. Note: Manuf = Manufacturing, Serv = Services, Prim = Primary Sector.
3.1.2. Backward Linkage decomposition The backward linkage indicates the extent to which a given sector demands from other
sectors. The backward linkage decomposition adopted in this subsection is analogous to the method previously used to the forward linkage. Therefore, this section sought to identify the
sectoral composition of the backward linkage for each sector, i.e. manufacturing, services and
the primary sector. In this analysis, two movements stand out. First, the backward linkage 149
intersectoral change of services in South Korea was more evident than in Brazil. This means that although in both countries manufacturing is demanding more services over the periods
described, in South Korea this movement was clearer. Second, while for South Korea the backward linkage of manufacturing has a lower share of services than the backward linkage of services has of manufacturing, the opposite holds true for Brazil. Figure 4.4 – Backward Linkage decomposition (%) South Korea BL (Manuf)
BL (Serv)
Brazil
80
26.87
27.37 53.92
70 60 50 40 30
67.16
0
5.97
57.94
5.03
37.41
39.69
90 80
39.61
2.50
2.46
36.82 63.11
60
53.53
43.59
33.85
70 50
67.59
20 10
BL (Serv)
BL (Prim)
100
100
90
BL (Manuf)
BL (Prim)
51.97
40 30
54.36
50.58
20
9.05
8.34
Primary Sector
10 0
11.79
Manufacturing
64.07
31.18
29.35
5.71
6.59
12.60
41.16
44.34
41.91
38.85
16.93
16.81
Services
Source: Author's own elaboration based on WIOD tables. Note: Manuf = Manufacturing, Serv = Services, Prim = Primary Sector.
This overall picture can be detailed by the numbers shown in the Figure 4.4. In South
Korea, during the first and second period, respectively 43.59% and 39.61% of the services backward linkage was made up of manufacturing. Nonetheless, the backward linkage of
manufacturing is represented approximately by only 27% of services, illustrating the distinct
interdependence between these sectors. In Brazil, data shows that services backward linkage not only experienced a drop in terms of manufacturing share for the periods analysed, but also
manufacturing makes up approximately 30%. It means that the magnitude of services demand from manufacturing is approximately only 30%. In the case of the manufacturing backward
linkage, the share of services increased over the periods. Moreover, as indicated before, the 150
share of services in the manufacturing backward linkage is greater than the share of
manufacturing in the services backward linkage. Additionally, the composition of the primary sector backward linkage in both countries showed an increase of services. Nevertheless, in Brazil it surpassed the manufacturing share during 2003–2009. 4. Concluding Remarks This chapter sough to analyse the productive composition of the Brazilian and South
Korean economies through an input-output analysis. In this way, the first section discussed briefly Hirschman’s theory particularly about the relevance of industrial linkages for
economic growth. In this approach, an underdeveloped economy is marked by the absence of linkages or inter- and intra-sectoral interdependences that affect cumulative effects on demand
and supply. Moreover, in an underdeveloped industrial structure, investments in intermediate and capital goods are restricted due to the lack of dynamic industrial linkages. Therefore, a
central condition in the economic growth process is an interdependent industrial structure. For this purpose, the state is a central agent to direct investments particularly to dynamic
manufacturing subsectors which present the strongest capacity to articulate strong linkages to the rest of the economy.
In this context, the chapter advanced to an applied analysis that outlined key sectors
and productive specificities of each economy. The first section initially measured output multipliers and Hirschman-Rasmussen indices. The output multipliers indicated that South
Korean subsectors are more interrelated than the Brazilian ones. From 1995 to 2002, South Korea presented higher output multipliers for the majority of subsectors, particularly in
manufacturing. In the subsequent period, i.e. from 2003 to 2009, South Korea expanded its output multiplier showing only four sectors with lower multipliers than Brazil. Consequently,
an increase in the South Korean final demand has a more dynamic effect on the domestic economy than in Brazil.
In terms of Hirschman-Rasmussen backward and forward linkages, as a general
picture, in both countries manufacturing showed high backward indices, while services and
the primary sector presented high forward linkages. The most evident exception was the
‘Petroleum’ subsector that in Brazil showed one of the highest backward linkages, while in South Korea presented a very low one. Although Hirschman had anticipated the central role
151
of manufacturing, this analysis showed specifically that medium- and high-tech subsectors are very dependent on the inter- and intra-sectoral supply, and consequently have the highest
potential to stimulate the production in other sectors. Furthermore, the main difference between the Brazilian and South Korean linkages refers to the level of the linkages. From a comparative perspective, South Korea presented an economy with higher backward and forward linkages than Brazil.
In a complementary way, seeking to refine the analysis of the productive structure, the
Hirschman-Rasmussen indices were normalised according to the sector size in each economy.
Therefore, in a cross-country analysis, the different productive structures of Brazil and South Korea become more evident. In terms of backward linkages, the main dichotomies between Brazil and South Korea were threefold. First, South Korea had important manufacturing
sectors ranked as the top six. Second, in this group, high-tech manufacturing figured with
higher pure normalised backward linkages than those in Brazil. Thus, it illustrates that in South Korea, dynamic manufacturing sectors have been used to stimulate the output of other sectors and create an environment of cumulative productive causation. Third, despite a general increase of the share of services in GDP in both economies, the Brazilian productive
structure indicated a significant dependence on services subsectors to stimulate the economy and also an increasing dependence on the primary sector. With regard to forward linkages, in
both countries, except for ‘Chemicals’, subsectors that produce products with a lower degree of processing in relation to other subsectors exhibited relatively higher forward linkages.
In the face of the increasing role of services in these indices and the rising trend of
intermediate consumption of services in manufacturing value-added, the third section
examined essentially the interdependence between services and manufacturing. Therefore, the forward and backward linkages for each sector were decomposed between manufacturing,
services and the primary sector through a new input-output method. First, the forward linkage
decomposition showed that: (i) the sectoral share of each linkage did not vary significantly between the periods analysed; and (ii), in both countries despite a considerable share of
services in GDP, their role in terms of forward linkage composition is still more limited than those of manufacturing. Second, the backward linkage decomposition showed that: (i) the backward linkage of all sectors are using more services over the periods (moreover, this trend
is more evident in South Korea than in Brazil); however (ii), in South Korea, the backward
linkage of manufacturing has a lower share of services than the backward linkage of services
has of manufacturing, while the opposite holds true for Brazil. Additionally, compared to 152
South Korea, the smaller share of the Brazilian manufacturing sector in both forward and backward linkages illustrates pervasive effects of neoliberal reforms.
After trade
liberalisation, the share of imported manufacturing inputs in final manufacturing production in Brazil increased significantly. In other words, production chains were broken and
manufacturing moved more to a final output assembly type of production. As many services are non-tradable, the impact was different in this sector.
153
Appendix 4.1 – Technical Details Output Multipliers and Hirschman-Rasmussen Linkages The indices calculated in this chapter through input-output methods used data from the
World Input-Output Database (WIOD) for the period 1995-2009 at the level of 34 sectors.
Additionally, this session was elaborated on the models described by Guilhoto (2009) and Guilhoto et al. (2010)158. Therefore, the basic Leontief model can be represented as: X = (I − A) Y Where ( ) represents the economy’s total production, and ( − A)
(4.1) = L is the inverse of
Leontief’s and ( ) is the final demand. From equation (4.1), it is possible to calculate a
number of important indices, such as generators, multipliers and linkages. Therefore, firstly define
as the direct coefficient:
k =
(4.2)
Where K is the variable (e.g., employment, value-added goods, and wages) of the corresponding sector X . Once
is calculated, along with Leontief’s inverse matrix ( ), it is
possible to calculate the amount of K directly and indirectly generated for each monetary unit
produced for the final demand for each sector. This value is referred to as the generator, which relates production for final demand to a given variable of the economy. Thus, the generator of a variable GK as follows:
for each sector can be calculated by summing each column of matrix =∑
.
(4.3)
Dividing the generator, GK, by the respective direct coefficient, it is possible to obtain the
multiplier of variable K that associates the direct effect of a variable regarding its total (direct and indirect) effect on the economy as follows: = 158
(4.4)
For more details, see also Miller & Blair (2009), Guilhoto (2011), Haddad et al. (2007) and Borghi (2013).
154
In this way, multipliers for employment and production can be obtained. In addition,
the input-output methodology allows other indicators of economic importance to be
calculated. The seminal works of Hirschman (1958) and Rasmussen (1956) led to the
development of backward and forward linkage indices that become a basic instrument to identify key sectors in the economy. The Hirschman-Rasmussen backward linkage (
measures the demand of a given sector for other sectors, while the forward linkage (
) index
) index
measures the degree to which this sector is demanded by other sectors. To calculate the Hirschman-Rasmussen of all elements of
index, l is defined as the elements of matrix , L∗ is the average
and L∗ is the sum of a column of . The =
is expressed as follows:
( ∗ ⁄ )
(4.5)
∗
Defining F as being the matrix of the row coefficients obtained from the intermediate
consumption matrix, G as the Ghosh matrix obtained from value of all elements of , and
∗
=( − ) ,
∗
as the average
as the sum of the elements in each row, then the forward
indices (FL) are represented as follows:
=
( ∗⁄ ) ∗
(4.6)
Sectors can be classified into the following four groups depending on their index
values: (i) independent from (or not highly related to) other sectors if both linkage indices are
less than 1; (ii) dependent on (or strongly related to) other sectors if both linkage indices are greater than 1, denoting sectors that play a key role in the economy; (ii) dependent on intersectoral supply (or stimulates production in other sectors) only if the BL index is greater
than 1; and (iv) dependent on intersectoral demand (or dependent on the production of other sectors) only if the FL index is greater than 1. However, as observed by Cella (1984) and Clements (1990), these indices do not take into account the different production levels in each sector of the economy.
Therefore, to correct and refine the solutions presented by Cella (1984) and Clements
(1990), Guilhoto et al. (1994) elaborated the first version of the so-called pure linkage index,
which later became known as the GHS methodology. Guilhoto, Sonis & Hewings (1996)
present decompositions of Leontief’s inverse matrix that incorporate the main methods used 155
in input-output analysis to decompose and differentiate the impact of an economic sector on
its various components. The consolidated GHS methodology is based on a block matrix of technical coefficients (A), represented as follows: =
where A and A
=
0
0 0
+
0
=
(4.7)
+
represent square matrices of the direct technical coefficients of sector and
the rest of the economy (the entire economy minus sector
), respectively. A
and
A represent rectangular matrices of direct inputs purchased by sector from the rest of the economy and direct inputs purchased by the rest of the economy from sector , respectively. Additionally,
refers to the sector isolated from the rest of the economy; and
the rest of the economy.
represents
Based on matrix A in (4.7), a triple multiplicative decomposition of Leontief’s inverse
matrix can be expressed as follows: =( − )
=
∆ 0
0 ∆
∆=
−
=
∆ 0
0 ∆
∆
∆
(4.8)
where,
∆ = ∆ =
∆ =( −
(4.9)
−∆
∆
−∆
∆
)
(4.10) (4.11) (4.12)
From equation (4.8) it is possible to reveal the process of production in an economy as
well as derive the Pure Backward Linkage (PBL) and the Pure Forward Linkage (PFL). The indices are defined as:
=∆
∆
(4.13) 156
=∆
∆
(4.14)
In Equation (4.13), the index indicates the impact of the value of the total output of sector j on the remainder of the economy, minus demand for inputs that sector j produces for itself and
the returns of the remainder of the economy for sector j and vice versa. The PFL in Equation
(19) indicates the impact of the value of the total production of the remainder of the economy on sector j. The PBL and PFL are summed to calculate the pure total linkage (PTL) index for each sector of the economy, expressed in current values: =
(4.15)
+
However, because these indices do not consider the size of the sectors, which is an
important aspect for identifying key sectors of the economy, a “normalisation” procedure should be applied to these indices based on the approach of normalised pure linkage indices.
For this purpose, the pure indices of each sector are divided by the average of pure indices for
the economy as a whole. Thus, the normalised PBL (PBLN) index, the normalised PFL (PFLN) index and the normalised PTL (PTLN) index can be represented as follows:
=
⁄∑
⁄
(4.16)
=
⁄∑
⁄
(4.17)
=
⁄∑
⁄
(4.18)
The interdependence between manufacturing and services As previously defined, the Hirschman-Rasmussen backward and forwards linkages
measure the magnitude that a given sector demands and supplies other sectors in the economy as a whole. In this sense, to identify and quantify the interdependence between sectors,
backward and forward linkages for each sector were broken in primary sector, manufacturing and services. Defining
=
−
to exclude the direct impact on the sector itself, equation
4.5 was broken in the three aforementioned sectors:
157
where ′ , ′
and ′
′
=
(
′
=
(
′
=
⁄ )
∗
⁄ )
∗
⁄ )
(
∗
(4.19)
(4.20) (4.21)
is the summation of the rows corresponding to the sector analysed
(primary sector, manufacturing or services, respectively) for each column (sector ), and ′ =
( ∗ ⁄ ) ∗
(4.22)
is the backward linkage excluding the direct impact on the sector itself. 4.6 as:
In the case of forward linkages, an analogous method was applied redefining equation =
′
=
′ = where ′ , ′
⁄ )
(
′
∗
⁄ )
(
∗
⁄ )
(
∗
(4.23) (4.24) (4.25)
and ′ is the summation of the lines corresponding to the sector analysed
(primary sector, manufacturing or services, respectively) for each line (sector ), and =
∗
⁄
∗
(4.26)
is the forward linkage excluding the direct impact on the sector itself.
158
Appendix 4.1 – Map of sectoral abbreviation and aggregation WIOD input-output table – 34 subsectors Agriculture, Hunting, Forestry and Fishing Mining and Quarrying Food, Beverages and Tobacco Textiles and Textile Products Leather, Leather and Footwear Wood and Products of Wood and Cork Pulp, Paper, Paper , Printing and Publishing Coke, Refined Petroleum and Nuclear Fuel Chemicals and Chemical Products Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery, Nec Electrical and Optical Equipment Transport Equipment Manufacturing, Nec; Recycling Electricity, Gas and Water Supply Construction Sale, Maintenance and Repair of Motor Vehicles and Motorcycles; Retail Sale of Fuel Wholesale Trade and Commission Trade, Except of Motor Vehicles and Motorcycles Retail Trade, Except of Motor Vehicles and Motorcycles; Repair of Household Goods Hotels and Restaurants Inland Transport Water Transport Air Transport Other Supporting and Auxiliary Transport Activities; Activities of Travel Agencies Post and Telecommunications Financial Intermediation Real Estate Activities Renting of M&Eq and Other Business Activities Public Admin and Defence; Compulsory Social Security Education Health and Social Work Other Community, Social and Personal Services Source: Author’s own elaboration Note: Nec = Not elsewhere classified.
Abbreviation – 34 subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Sales Sales Traditional services Transport services Transport services Transport services Traditional services Traditional services Financial services Traditional services Business services Public Admin Health and education Health and education Health and education
159
Appendix 4.2 - Hirschman-Rasmussen Backward Linkage index (Brazil) Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
95 0.87 0.82 1.17 1.07 1.23 0.92 1.11 1.14 0.95 1.08 1.05 0.96 1.16 1.20 1.24 1.12 0.88 1.08 0.74 0.81 0.86 0.94 0.93 0.81 0.86
Source: Author's own elaboration based on WIOD tables. Note: Nec = Not elsewhere classified.
96 0.88 0.82 1.19 1.08 1.21 0.92 1.13 1.12 0.99 1.08 1.05 0.97 1.16 1.19 1.22 1.12 0.89 1.09 0.74 0.82 0.84 0.94 0.92 0.81 0.85
97 0.88 0.82 1.19 1.08 1.21 0.91 1.13 1.16 0.99 1.07 1.04 0.96 1.14 1.18 1.20 1.11 0.89 1.08 0.75 0.83 0.84 0.94 0.94 0.82 0.86
98 0.88 0.81 1.18 1.06 1.18 0.91 1.13 1.21 0.98 1.07 1.06 0.94 1.12 1.16 1.16 1.10 0.93 1.07 0.75 0.84 0.85 0.96 0.95 0.83 0.87
99 0.90 0.82 1.19 1.09 1.17 0.92 1.13 1.21 1.00 1.09 1.05 0.93 1.11 1.11 1.12 1.10 0.94 1.06 0.76 0.86 0.87 0.97 0.93 0.82 0.85
00 0.90 0.82 1.20 1.06 1.17 0.92 1.13 1.20 1.08 1.12 1.04 0.95 1.12 1.08 1.14 1.10 0.93 1.06 0.75 0.85 0.86 0.97 0.90 0.82 0.84
01 0.88 0.87 1.17 1.08 1.17 0.93 1.10 1.22 1.05 1.07 1.05 0.95 1.13 1.10 1.14 1.07 1.05 1.03 0.75 0.85 0.88 0.90 0.91 0.81 0.84
02 0.89 0.90 1.16 1.11 1.19 0.95 1.09 1.18 1.05 1.05 1.01 0.98 1.12 1.10 1.18 1.04 1.00 1.04 0.75 0.83 0.89 0.90 0.90 0.84 0.84
03 0.90 0.89 1.19 1.08 1.19 0.98 1.08 1.17 1.11 1.12 1.08 0.99 1.15 1.08 1.23 1.08 0.96 0.96 0.75 0.81 0.90 0.87 0.86 0.77 0.81
04 0.92 0.91 1.21 1.08 1.20 1.03 1.06 1.16 1.15 1.13 1.01 0.98 1.13 1.06 1.22 1.06 0.93 0.94 0.75 0.81 0.89 0.90 0.85 0.80 0.82
05 0.92 0.93 1.23 1.05 1.16 1.04 1.06 1.24 1.11 1.14 1.00 1.03 1.14 1.07 1.24 1.04 0.92 0.94 0.76 0.81 0.89 0.84 0.84 0.81 0.81
06 0.89 0.92 1.22 1.05 1.14 1.01 1.03 1.30 1.09 1.12 1.03 1.03 1.14 1.06 1.23 1.02 0.91 0.94 0.76 0.82 0.90 0.85 0.86 0.81 0.83
07 0.89 0.92 1.22 1.03 1.17 1.03 1.06 1.24 1.10 1.10 1.04 1.06 1.13 1.08 1.20 1.01 0.90 0.94 0.77 0.83 0.91 0.83 0.86 0.82 0.83
08 0.92 0.92 1.26 1.03 1.15 1.04 1.03 1.22 1.13 1.09 1.06 1.07 1.11 1.05 1.18 1.03 0.93 0.94 0.77 0.83 0.92 0.83 0.85 0.82 0.82
09 0.91 0.82 1.25 1.02 1.13 1.03 1.00 1.29 1.10 1.13 1.10 1.05 1.17 1.10 1.22 1.04 0.92 0.99 0.76 0.82 0.91 0.79 0.84 0.80 0.82
160
Appendix 4.3 - Hirschman-Rasmussen Forward Linkage index (Brazil) Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
95 1.10 1.46 0.82 0.93 0.72 1.27 1.24 1.16 1.15 1.31 1.21 1.23 0.81 0.91 0.85 0.76 1.19 0.64 1.02 0.79 1.06 1.03 1.06 0.57 0.71
Source: Author's own elaboration based on WIOD tables. Note: Nec = Not elsewhere classified.
96 1.09 1.46 0.81 0.94 0.71 1.27 1.25 1.13 1.15 1.32 1.22 1.25 0.82 0.92 0.82 0.75 1.19 0.65 1.02 0.80 1.06 1.02 1.06 0.57 0.71
97 1.09 1.49 0.82 0.93 0.71 1.25 1.27 1.16 1.15 1.31 1.20 1.25 0.82 0.92 0.80 0.75 1.19 0.65 1.02 0.80 1.06 1.02 1.06 0.57 0.71
98 1.10 1.46 0.82 0.93 0.69 1.24 1.27 1.18 1.15 1.29 1.21 1.23 0.81 0.91 0.78 0.75 1.21 0.66 1.02 0.81 1.07 1.03 1.07 0.57 0.71
99 1.11 1.45 0.83 0.94 0.68 1.12 1.25 1.19 1.16 1.30 1.22 1.18 0.83 0.90 0.75 0.76 1.23 0.69 1.04 0.83 1.08 1.05 1.08 0.59 0.73
00 1.10 1.47 0.83 0.93 0.68 1.15 1.27 1.19 1.18 1.29 1.22 1.18 0.81 0.85 0.74 0.76 1.25 0.67 1.05 0.83 1.09 1.06 1.09 0.59 0.73
01 1.09 1.46 0.82 0.93 0.69 1.10 1.23 1.18 1.18 1.30 1.22 1.18 0.80 0.92 0.72 0.73 1.33 0.67 1.05 0.84 1.10 1.05 1.10 0.59 0.73
02 1.08 1.42 0.81 0.96 0.70 1.05 1.24 1.20 1.19 1.30 1.23 1.18 0.79 0.86 0.74 0.75 1.34 0.68 1.07 0.84 1.09 1.04 1.09 0.59 0.73
03 1.07 1.43 0.80 0.96 0.69 1.07 1.22 1.22 1.22 1.32 1.25 1.17 0.76 0.92 0.76 0.74 1.31 0.67 1.08 0.84 1.08 1.03 1.08 0.58 0.72
04 1.09 1.40 0.81 0.96 0.68 1.06 1.23 1.23 1.25 1.33 1.22 1.15 0.75 0.88 0.77 0.74 1.32 0.67 1.08 0.85 1.10 1.04 1.10 0.58 0.73
05 1.11 1.39 0.82 0.93 0.68 1.11 1.22 1.22 1.23 1.35 1.21 1.18 0.76 0.87 0.80 0.73 1.29 0.67 1.08 0.84 1.10 1.02 1.10 0.57 0.73
06 1.11 1.38 0.83 0.93 0.68 1.13 1.21 1.22 1.19 1.33 1.21 1.18 0.75 0.87 0.80 0.73 1.29 0.67 1.07 0.85 1.10 1.04 1.10 0.58 0.74
07 1.11 1.36 0.83 0.90 0.68 1.16 1.22 1.22 1.17 1.33 1.22 1.19 0.73 0.91 0.78 0.73 1.28 0.68 1.06 0.85 1.11 1.06 1.11 0.58 0.74
08 1.08 1.33 0.83 0.89 0.69 1.22 1.21 1.21 1.19 1.32 1.25 1.19 0.72 0.89 0.78 0.73 1.29 0.68 1.05 0.86 1.10 1.08 1.10 0.59 0.74
09 1.06 1.40 0.80 0.86 0.67 1.28 1.18 1.20 1.18 1.32 1.28 1.30 0.76 0.93 0.81 0.72 1.24 0.69 1.04 0.83 1.07 1.04 1.07 0.56 0.72
161
Appendix 4.4 - Hirschman-Rasmussen Backward Linkage index (South Korea) Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
95 0.82 0.74 1.07 1.19 1.23 0.99 1.06 0.59 1.06 1.09 1.21 1.05 1.31 1.93 1.18 1.19 0.82 0.94 0.83 0.89 0.87 0.80 0.75 0.71 0.70
Source: Author's own elaboration based on WIOD tables. Note: Nec = Not elsewhere classified.
96 0.82 0.74 1.10 1.19 1.23 1.03 1.09 0.59 1.04 1.10 1.20 1.02 1.30 1.85 1.18 1.21 0.81 0.94 0.84 0.88 0.84 0.83 0.77 0.71 0.71
97 0.84 0.73 1.12 1.20 1.26 1.05 1.12 0.58 1.04 1.10 1.19 1.00 1.27 1.65 1.21 1.17 0.81 0.95 0.86 0.89 0.86 0.85 0.80 0.71 0.73
98 0.86 0.70 1.12 1.28 1.32 1.15 1.18 0.60 1.07 1.10 1.18 0.97 1.23 1.54 1.20 1.19 0.82 0.92 0.88 0.85 0.88 0.83 0.75 0.69 0.70
99 0.86 0.74 1.16 1.23 1.24 1.05 1.11 0.60 1.07 1.13 1.17 1.03 1.31 1.43 1.28 1.21 0.82 0.96 0.84 0.86 0.87 0.85 0.75 0.70 0.73
00 0.87 0.72 1.14 1.21 1.23 1.03 1.13 0.61 1.10 1.14 1.12 1.06 1.26 1.38 1.27 1.20 0.83 1.00 0.81 0.89 0.85 0.89 0.78 0.72 0.78
01 0.86 0.71 1.13 1.19 1.23 1.01 1.12 0.60 1.08 1.14 1.13 1.05 1.28 1.37 1.28 1.21 0.81 1.00 0.82 0.88 0.87 0.88 0.80 0.73 0.79
02 0.86 0.76 1.14 1.17 1.20 1.01 1.11 0.59 1.05 1.14 1.15 1.06 1.29 1.32 1.32 1.23 0.78 1.01 0.84 0.89 0.85 0.86 0.81 0.74 0.81
03 0.87 0.79 1.13 1.19 1.20 1.02 1.11 0.59 1.06 1.14 1.15 1.05 1.27 1.23 1.30 1.24 0.76 1.02 0.86 0.90 0.86 0.85 0.83 0.76 0.81
04 0.87 0.81 1.14 1.16 1.19 1.05 1.12 0.61 1.09 1.13 1.12 1.09 1.24 1.18 1.28 1.26 0.78 1.02 0.86 0.90 0.87 0.83 0.83 0.77 0.80
05 0.87 0.81 1.16 1.14 1.18 1.05 1.11 0.61 1.07 1.15 1.10 1.13 1.27 1.14 1.32 1.27 0.78 1.03 0.86 0.89 0.84 0.81 0.83 0.77 0.79
06 0.88 0.80 1.16 1.12 1.18 1.06 1.10 0.62 1.08 1.14 1.09 1.11 1.25 1.11 1.33 1.27 0.81 1.03 0.86 0.90 0.82 0.85 0.86 0.78 0.80
07 0.89 0.80 1.16 1.10 1.20 1.05 1.10 0.64 1.08 1.13 1.07 1.13 1.23 1.07 1.31 1.26 0.83 1.05 0.86 0.91 0.84 0.87 0.84 0.77 0.81
08 0.91 0.82 1.19 1.08 1.22 1.05 1.14 0.64 1.10 1.13 1.05 1.18 1.19 1.05 1.27 1.19 0.85 1.06 0.85 0.92 0.86 0.89 0.83 0.76 0.80
09 0.91 0.80 1.24 1.10 1.27 1.10 1.09 0.66 1.05 1.12 1.05 1.21 1.22 1.05 1.35 1.21 0.87 1.03 0.83 0.89 0.80 0.84 0.80 0.74 0.78
162
Appendix 4.5 - Hirschman-Rasmussen Forward Linkage index (South Korea) Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
95 0.97 1.65 0.79 0.72 0.76 1.28 1.37 1.21 1.21 1.20 1.26 1.37 0.92 0.80 0.75 0.78 1.35 0.59 0.79 0.88 0.84 1.20 1.24 0.51 0.56
Source: Author's own elaboration based on WIOD tables. Note: Nec = Not elsewhere classified.
96 1.05 1.56 0.89 0.72 0.78 1.29 1.40 1.14 1.23 1.19 1.26 1.36 0.92 0.80 0.77 0.76 1.31 0.58 0.81 0.85 0.82 1.19 1.25 0.52 0.55
97 1.10 1.60 0.91 0.72 0.76 1.31 1.40 1.12 1.21 1.17 1.27 1.32 0.92 0.74 0.79 0.78 1.28 0.59 0.82 0.86 0.81 1.19 1.25 0.53 0.56
98 1.21 2.28 0.90 0.64 0.73 1.25 1.38 1.15 1.21 1.10 1.21 1.17 0.86 0.73 0.72 0.73 1.26 0.59 0.82 0.85 0.78 1.17 1.20 0.51 0.55
99 1.15 1.66 0.90 0.72 0.73 1.30 1.39 1.12 1.26 1.18 1.24 1.35 0.90 0.76 0.79 0.77 1.26 0.59 0.83 0.84 0.79 1.16 1.23 0.52 0.55
00 1.15 1.66 0.89 0.75 0.71 1.32 1.41 1.07 1.28 1.19 1.26 1.39 0.89 0.76 0.77 0.77 1.25 0.59 0.83 0.84 0.77 1.15 1.22 0.53 0.56
01 1.14 1.67 0.90 0.75 0.71 1.32 1.40 1.08 1.28 1.18 1.25 1.39 0.87 0.78 0.77 0.77 1.24 0.58 0.84 0.83 0.83 1.13 1.21 0.52 0.56
02 1.13 1.62 0.91 0.78 0.72 1.34 1.40 1.04 1.27 1.18 1.24 1.39 0.87 0.79 0.79 0.82 1.22 0.56 0.84 0.83 0.85 1.11 1.21 0.52 0.56
03 1.15 1.61 0.93 0.78 0.75 1.34 1.39 1.02 1.25 1.18 1.23 1.36 0.89 0.78 0.80 0.83 1.23 0.56 0.85 0.83 0.88 1.10 1.20 0.52 0.56
04 1.15 1.57 0.93 0.79 0.74 1.36 1.37 1.06 1.21 1.16 1.22 1.36 0.90 0.77 0.79 0.86 1.26 0.55 0.85 0.84 0.89 1.09 1.19 0.52 0.56
05 1.13 1.66 0.92 0.80 0.74 1.36 1.35 1.10 1.19 1.18 1.19 1.39 0.90 0.77 0.81 0.87 1.25 0.53 0.84 0.82 0.90 1.06 1.15 0.51 0.55
06 1.13 1.62 0.93 0.83 0.76 1.37 1.36 1.08 1.19 1.19 1.19 1.35 0.91 0.77 0.82 0.89 1.25 0.53 0.84 0.83 0.89 1.07 1.15 0.51 0.54
07 1.13 1.62 0.93 0.84 0.78 1.36 1.38 1.06 1.16 1.18 1.19 1.35 0.91 0.78 0.80 0.90 1.26 0.53 0.84 0.83 0.88 1.09 1.15 0.51 0.54
08 1.13 1.48 0.96 0.84 0.84 1.37 1.37 1.04 1.14 1.15 1.19 1.34 0.89 0.75 0.75 0.91 1.30 0.54 0.85 0.85 0.92 1.12 1.17 0.52 0.56
09 1.19 2.13 0.92 0.83 0.85 1.34 1.31 1.05 1.09 1.14 1.17 1.31 0.88 0.75 0.76 0.96 1.25 0.50 0.80 0.80 0.83 1.05 1.10 0.48 0.51
163
Appendix 4.6 - Backward and Forward Linkages Decomposition (Brazil, %)
Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
1995-2002 2003-2009 Backward Linkage Backward Linkage Forward Linkage Forward Linkage Prim Manuf Serv Prim Manuf Serv Prim Manuf Serv Prim Manuf Serv 23.72 45.86 30.42 11.78 72.17 16.05 23.31 44.57 32.12 12.99 72.51 14.50 10.13 37.97 51.90 5.91 74.61 19.48 10.31 33.13 56.56 7.54 70.98 21.47 36.25 34.36 29.39 10.27 48.74 41.00 36.74 31.50 31.76 12.55 50.50 36.94 5.46 61.22 33.33 2.24 74.43 23.33 7.76 54.98 37.26 3.54 72.52 23.93 6.36 60.43 33.21 0.38 95.34 4.28 7.10 56.88 36.01 0.43 95.68 3.89 16.55 55.56 27.89 2.54 85.59 11.87 18.88 50.62 30.50 3.07 85.53 11.40 7.53 50.79 41.68 2.18 43.49 54.33 11.17 48.60 40.23 3.23 45.66 51.12 46.40 28.21 25.39 6.47 54.48 39.05 46.44 25.18 28.38 8.78 52.02 39.20 9.62 51.60 38.78 11.97 67.10 20.94 10.00 48.00 42.00 14.89 66.56 18.55 4.97 58.38 36.65 3.81 67.71 28.47 5.92 55.11 38.97 4.63 64.34 31.03 13.43 44.27 42.31 2.00 83.73 14.27 10.93 43.23 45.84 3.70 81.10 15.21 8.63 57.11 34.26 4.10 84.46 11.44 9.96 50.44 39.60 4.98 84.50 10.52 3.83 64.62 31.55 7.73 74.57 17.70 4.47 59.66 35.87 10.29 72.65 17.05 3.99 57.92 38.09 2.83 66.38 30.78 4.40 53.76 41.84 4.16 63.19 32.66 2.65 62.45 34.90 1.61 65.89 32.50 3.11 60.27 36.62 2.04 69.09 28.87 4.73 65.71 29.55 2.00 43.20 54.81 5.84 60.57 33.59 2.58 41.49 55.93 6.47 21.32 72.20 4.25 41.19 54.56 10.46 20.72 68.83 5.65 43.74 50.60 6.38 62.80 30.83 2.78 34.85 62.38 6.23 59.87 33.90 5.80 28.11 66.09 4.33 26.13 69.54 6.42 58.16 35.43 5.03 25.60 69.37 8.22 59.72 32.05 11.57 44.98 43.45 5.03 34.29 60.68 11.20 40.71 48.09 7.45 35.54 57.01 5.78 34.82 59.40 4.87 36.99 58.15 6.69 33.54 59.78 6.90 37.67 55.43 2.27 22.04 75.69 3.51 35.62 60.86 2.47 19.14 78.40 5.06 38.39 56.55 5.78 34.82 59.40 4.87 36.99 58.15 6.69 33.54 59.78 6.90 37.67 55.43 4.60 26.70 68.71 4.46 37.51 58.03 4.82 25.48 69.70 6.34 38.76 54.90 4.90 38.61 56.49 4.85 36.75 58.40 5.34 36.06 58.60 6.88 37.42 55.70
Source: Author's own elaboration based on WIOD tables Note: Nec = Not elsewhere classified.
164
Appendix 4.6 - Backward and Forward Linkages Decomposition (South Korea, %)
Subsectors Agriculture Mining Food and Beverages Textiles Leather and Footwear Wood and Products of Wood Paper , Printing and Publishing Petroleum and Nuclear Fuel Chemicals Rubber and Plastics Other Non-Metallic Mineral Basic Metals and Fabricated Metal Machinery Electrical and Optical Equipment Transport Equipment Manufacturing, Nec Utilities Construction Sales Traditional Services Transport Services Financial Services Business Services Public Admin Health and Education
1995-2002 2003-2009 Backward Linkage Backward Linkage Forward Linkage Forward Linkage Prim Manuf Serv Prim Manuf Serv Prim Manuf Serv Prim Manuf Serv 16.97 58.46 24.58 9.20 69.15 21.65 15.74 57.14 27.12 8.06 62.82 29.11 1.14 48.61 50.25 0.56 87.98 11.46 0.93 46.80 52.27 0.51 87.16 12.34 35.67 43.06 21.27 11.87 45.89 42.23 32.46 42.17 25.37 9.23 40.24 50.54 3.38 66.93 29.68 1.16 86.58 12.26 2.27 65.25 32.48 1.99 81.13 16.88 7.40 69.00 23.60 0.29 88.85 10.86 6.32 65.14 28.54 0.43 80.81 18.76 15.49 53.20 31.30 3.03 83.36 13.61 12.06 57.48 30.46 2.99 84.90 12.11 0.99 69.22 29.79 1.19 66.06 32.75 0.93 66.15 32.92 1.32 63.52 35.17 3.36 62.26 34.38 2.68 60.84 36.48 3.16 57.86 38.98 2.38 64.81 32.81 1.65 74.31 24.04 3.15 81.23 15.62 1.41 74.54 24.06 2.27 80.86 16.87 2.17 75.23 22.60 2.16 83.33 14.51 1.99 74.55 23.46 1.73 85.98 12.28 11.56 54.80 33.64 0.39 89.95 9.65 9.00 53.76 37.24 0.31 91.96 7.73 0.69 81.83 17.48 0.38 93.46 6.16 0.59 80.65 18.76 0.26 94.71 5.03 0.63 75.04 24.33 1.22 85.26 13.53 0.53 77.55 21.93 0.78 86.45 12.77 1.08 66.76 32.16 0.34 89.57 10.09 0.79 72.61 26.60 0.22 89.58 10.20 0.60 78.95 20.46 0.77 82.10 17.13 0.49 82.83 16.68 0.44 84.71 14.86 2.34 68.27 29.39 0.74 58.79 40.47 1.64 72.09 26.27 0.43 68.38 31.19 1.81 53.15 45.04 1.39 58.45 40.16 1.75 42.70 55.55 1.19 55.82 42.99 2.49 68.52 28.98 0.88 21.07 78.05 1.83 71.30 26.87 0.82 22.71 76.46 1.51 32.13 66.36 1.73 65.37 32.91 1.52 32.17 66.31 1.72 62.66 35.62 6.70 47.16 46.14 1.41 35.97 62.62 7.79 40.48 51.73 1.36 39.88 58.76 1.07 56.20 42.74 1.76 59.62 38.61 1.10 55.67 43.23 1.57 63.65 34.78 1.11 19.82 79.08 2.23 46.91 50.86 0.86 13.75 85.39 1.39 36.22 62.39 4.43 36.80 58.76 1.57 57.18 41.25 3.45 35.51 61.05 1.18 56.90 41.92 1.75 55.50 42.76 2.72 37.24 60.05 1.68 51.83 46.49 2.74 37.60 59.65 1.59 47.93 50.48 2.10 41.02 56.88 1.51 44.74 53.75 1.61 41.13 57.26
Source: Author's own elaboration based on WIOD tables Note: Nec = Not elsewhere classified.
165
CONCLUSIONS This thesis investigated the role of the manufacturing sector in economic growth
through a comparative analysis between Brazil and South Korea. The study adopted
theoretical, historical and empirical approaches to understand the particularities of each
productive structure that conditioned their distinct economic dynamic. The first chapter presented the theoretical core of this thesis. An effort to combine different heterodox strands
on economic development highlighting the importance of the manufacturing sector to economic growth was made. Through contributions from Keynesian-Kaldorian, Structuralist
and Neo-Schumpeterian theories, this chapter argued that the manufacturing sector presents some growth-enhancing properties not found in other sectors.
Both Anglo-Saxon and Latin American Structuralism strands stressed that economic
development is narrowly linked to a radical transformation in favour of the manufacturing sector to overcome underdevelopment. Structuralist strands state that a dynamic process of industrialisation is a necessary condition for increasing employment, productivity and income
per capita and, consequently, reducing poverty. According to this approach, the process of economic development involves a shift of production from low productivity to high productivity sectors where increasing returns to scale prevail.
Complementarily, the Kaldorian literature detailed that the manufacturing sector is
imbued with special properties not shared by other sectors that trigger a process of cumulative
causation. Thus, from a Kaldorian perspective, the understanding of the development process and growth rate differences between countries requires a sectoral approach. The Kaldorian section also explored the role of manufacturing for productivity growth, stating that the rate of
productivity growth in the manufacturing sector depends on its rate of output growth due to static and dynamic returns to scale. Furthermore, this economic approach emphasises the central role of manufacturing for the balance of payments equilibrium.
The importance of manufacturing was also approached in the first chapter through the
debate about de-industrialisation that identifies three main causes for this process, namely statistical illusions, ‘servicification’ and productive fragmentation. This section showed that a non-negligible part of the extent of de-industrialisation reflects changes in statistical
classification rather than a real decrease in the relative importance of manufacturing.
Furthermore, despite the recent rise of services, manufacturing remains the driver of 166
economic growth, as many services essentially are spin-offs from manufacturing production.
Additionally, the increasing trend of productive fragmentation over the world not only reduced the manufacturing share in the GDP of many economies but also affected negatively these countries through a deterioration of the so-called “industrial commons” that resulted in a loss of high-value-added activities and the capacity to create technological innovation.
The first chapter also examined the Neo-Schumpeterian route to development,
exploring relations between innovation, economic dynamism and catching-up in a sectoralspecific approach. The convergence between Neo-Schumpeterian literature and Structuralist
economics showed the role of manufacturing as a main locus of technological change. From
an economic development perspective, developed and developing economies could be divided
according to their capacity to innovate and imitate. In this approach, the diffusion of
technological progress to developing economies results from a process of technology absorption through imitation of products and process from developed economies. Along the economic development trajectory, countries first imitate and then innovate according to their own needs. In this process, the cumulative causation is generated by the accumulation of knowledge on productivity growth.
From the aforementioned theoretical framework that considers a thriving
manufacturing sector a necessary condition for a successful trajectory of economic growth,
the second chapter analysed the industrial development undertaken by Brazil and South Korea and identified domestic and external factors that determined their distinct routes of economic dynamism. This study showed that during the industrialist era (1950-1980) both countries
presented a significant economic dynamism based on an active developmental state. In South
Korea, the strategy of economic development comprised policies for technology acquisition, incentives for R&D activities and the promotion of cartels for specific purposes, such as
standardisation, specialisation and exports. Additionally, the South Korean domestic private capital, represented by the Chaebols, played a decisive role in the development of the national
industry with a clear outward orientation. In Brazil, by contrast, industrialisation was mainly driven by state-owned enterprises and multinational companies, following a pattern of industrial growth grounded in its large domestic market.
Nevertheless, during the 1970s, both economies were strongly impacted by two oil
price shocks in 1973 and 1979, and the Volcker interest rate hikes in 1979. The outbreak of
the debt crisis in 1982 and the abrupt cut-off of the international liquidity exposed the 167
vulnerability of the Brazilian economy, given its large current account deficit and external
debt. This turbulent economic environment resulted in a serious domestic crisis and caused a
deep disarticulation of the state to provide active policies for national industry as before.
Consequently, economic growth was seriously affected during the 1980s, giving rise to the
commonly used term “the lost decade”. South Korea dealt with the crisis in a much less traumatic way, since its strategy of industrialisation was relatively less dependent on foreign
debt and the Japanese banks played a decisive role ‘recycling’ the country’s liabilities. Therefore, distinct from the Brazilian economy, South Korea not only recovered rapidly from
the debt crisis, but also strengthened the manufacturing sector and the production of cuttingedge technological products.
From the 1980s onwards, Brazil embarked on a ‘fundamentalist’ neoliberal agenda
which sought to reverse almost every aspect of the growth strategy previously followed by the country. Neoliberal policies were strongly marked by an extreme move towards market
friendly policies which weakened the domestic manufacturing sector. In South Korea, the neoliberal policies implemented were remarkably different. South Korean economic reforms were much more pragmatic, seeking to transform the initial catching-up efforts into a dynamic
and sustainable process of capital expansion and development. After the 1980s, despite the neoliberal discourse, the country’s experience was characterised by the maintenance of a strong state control over socioeconomic transformations and by pragmatism in the management
of
intermediate
and
instrumental
objectives,
such
internationalisation and the administration of the fiscal and monetary policy.
as
economic
In Brazil, the pro-market policy orientation resulted in an economic dynamic of
successive ‘stop-and-go’ cycles derived from a fragile productive structure and lack of
effective demand. From the 1980s onwards, the country’s growth rate collapsed both in terms of GDP and manufacturing value-added growth. Moreover, from an intra-sectoral viewpoint,
the manufacturing sector showed a technology composition that stagnated over the decades.
In contrast, South Korea presented a much more sustainable economic growth. The economy grew, on average, more than 6% per year and the manufacturing sector expanded significantly. In terms of intra-sectoral value-added composition, the share of high-tech industries rose sharply, reaching around 61% of the manufacturing share in 2010.
The deleterious effects of premature de-industrialisation in Brazil vis-à-vis South
Korea’s thriving manufacturing expansion clearly had an impact on the evolution of labour 168
productivity and income catching-up. Data shows that the remarkable neglect of manufacturing since economic reforms lies at the heart of country’s productivity stagnation. In contrast to the period from 1950 to 1980, when in both countries manufacturing and
productivity expanded considerably, from 1980 to 2010 due to the manufacturing collapse, Brazilian productivity remained mostly stagnant. Even during the commodities prices boom from 2002 to 2008, Brazilian economy productivity growth was extremely poor. In terms of income catching-up, while South Korea moved ahead after the advent of neoliberal reforms, Brazil drastically fell behind.
Taking into account the ‘Kaldorian-Structuralist’ approach, it is not by coincidence
that the persistent difficulty to overcome the middle-income trap appears to be closely related
to the absence of a dynamic manufacturing sector. Regarding their export trajectories, the
dichotomy between these economies is also very clear. On the one hand, South Korea pursued an outward strategy of economic growth expanding exports of manufacturing products, particularly of high-tech products. On the other hand, Brazil has been historically dependent
on its domestic market and Ricardian comparative advantages, i.e. natural resources endowments. As a matter of fact, even in a context of a dynamic domestic market, the
Brazilian economic policy has been unable to articulate a dynamic manufacturing sector to compete internationally.
The structural dichotomy between Brazil and South Korea in terms of productive
structure was detailed through input-output analyses in the third and fourth chapters, which constituted the empirical part of this thesis. The third chapter complemented the previous
historical analysis, detailing the structural transition and dichotomy between Brazil and South Korea. Based on the methodology of Imbs and Wacziarg, data showed that Brazil was affected by a process of premature specialisation at both the inter- and the intra-sectoral
levels. Intra-sectoral data of manufacturing revealed that during the specialisation stage, South Korea increased sharply the share of medium- and high-tech sectors in the economy while Brazil, although more diversified, remained dependent on less dynamic sectors. This
dichotomy propelled different processes of cumulative causation and, consequently, impacted on the countries’ growth rates distinctly.
The third chapter also applied the structural decomposition analysis (SDA) to
understand factors such as demand, trade and technological change that contributed to the formation of these divergent productive structures. Results showed that, during the height of
169
neoliberal reforms from 1995 to 2003, the Brazilian manufacturing output exhibited a poor performance with the majority of components registering negative variations. By contrast, the
South Korean manufacturing output increased sharply, mainly due to exports and positive variations in other components. Furthermore, this expansion was composed mostly of
medium- and high-tech industries. In the subsequent period, from 2003 to 2008, besides the
significant output growth, South Korea registered an expressive increase of imports, mainly
due to the ‘flying geese’ movement of regional productive fragmentation marked especially by the rise of China as the world’s factory.
In Brazil, domestic demand from 2003 to 2008 composed the key variable of
economic growth, propelled by the credit-led consumption of the period. The boom in commodity prices also played a central role in boosting the economy in that period.
Nevertheless, once again manufacturing performed worse when compared to services, which showed the most dynamic output growth. Evidence of the productive disarticulation of the
Brazilian industry was reinforced by the negative variation of the component related to
imports. Under high and volatile interest and exchange rates, periods of demand expansion (such as during the 2000s) experienced substitution of national inputs for imported ones as the
easiest way to attend demand. This fact not only revealed the dependence of the Brazilian domestic industry in relation to the international supply but also the wreaking of important intra-sectoral linkages.
The final chapter dealt with the productive structure of the Brazilian and South Korean
economies in terms of leading sectors and sectoral interdependences. In this sense,
Hirschman’s theory was applied to explain the importance of industrial linkages for economic growth. According to this thinking, an underdeveloped economy is marked by the absence of
inter- and intra-sectoral linkages that affect cumulative effects in demand and supply. In this
context, the chapter initially measured output multipliers and Hirschman-Rasmussen indices. Output multipliers indicated that the South Korean subsectors are more interrelated than the
Brazilian ones. From 1995 to 2002, South Korea presented higher output multipliers for the
majority of subsectors, particularly in manufacturing. In the subsequent period, from 2003 to 2009, South Korea expanded its output multiplier showing only four sectors with lower multipliers than Brazil. Thus, an increase in the South Korean final demand has a more dynamic effect on the domestic economy than in Brazil.
170
In terms of Hirschman-Rasmussen backward and forward linkages, as a general
picture, in both countries manufacturing presented high backward indices, while services and the primary sector presented high forward linkages. The exception was the ‘Petroleum’ subsector, which in Brazil showed one of the highest backward linkages while in South Korea
presented a very low one. Although Hirschman had anticipated the central role of manufacturing, this analysis showed particularly that the majority of medium- and high-tech subsectors is very dependent on the inter- and intra-sectoral supply and, consequently, has the
highest potential to stimulate the production in other sectors. Furthermore, the main difference
between Brazilian and South Korean linkages refers to the level of their linkages. From a comparative perspective, South Korea presented an economy with higher backward and forward linkages than Brazil.
In a complementary way, seeking to refine the analysis of the productive structure, the
Hirschman-Rasmussen indices were normalised according to the sector size in each economy. The different productive structures of Brazil and South Korea became more evident. Results
of pure normalised backward linkages showed that South Korea not only presented more
manufacturing sectors but also more high-tech subsectors with the highest linkages. These findings illustrate that in South Korea, dynamic manufacturing sectors have been used to
stimulate the production of inputs of other sectors and to create an environment of cumulative productive causation. Despite a general increase of services in both economies, the Brazilian
productive structure indicated a significant dependence on services subsectors to stimulate the economy and an increasing dependence on the primary sector as well. In regard to the forward
linkage, in both countries, except for ‘Chemicals’, subsectors that produced goods with a
lower degree of processing in relation to other subsectors exhibited relatively higher forward linkages.
In face of the increasing role of services in these indices and their ascendant trend of
intermediate consumption in manufacturing value-added, the fourth chapter also examined the interdependence between services and manufacturing. Both forward and backward linkages for each sector were decomposed between manufacturing, services and the primary sector through a new input-output method. First, the forward linkage decomposition showed that (i)
the sectoral share of each linkage did not vary significantly between the periods analysed, and
(ii) in both countries, despite a considerable share of services in GDP, their role in terms of forward linkage composition is still more limited than those of manufacturing. Second, the backward linkage decomposition showed that (i) all sectors are using more services over both
171
periods, a trend more evident in South Korea than in Brazil, and (ii) while the South Korean
backward linkage of manufacturing has a lower share of services than the backward linkage of services has of manufacturing, the opposite holds true for Brazil.
172
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