Page 1 Abdelhafidh DHRIFI (Correspondence) Abdelhafidh.dhrifi ...

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Faculty of Economic Sciences and Management-Mahdia, Department of Economics, University of MonastirTunisia Abstract: Agriculture is the livelihood of the majority of the world‘s poor and is an important development concern. For that reason, agricultural finance is critical to boost food production and help address food security in the world and also to address the livelihood needs of the poor. The objective of this paper fits into this framework and seeks to study in what extent financial system in African countries contributes to the improvement of agricultural productivity. Estimations are conducted with a panel data of 44 African countries over the period of 1990-2012 using GMM-System estimator. Our findings show that financial system by itself cannot favor agriculture sector in African countries, but at the presence of a good quality of institutions, it contribute positively to improvements of agriculture productivity. The results show also that, in the presence of a certain threshold of quality institutions, African countries can profit of financial development once these threshold conditions are satisfied. This threshold is estimated at a rate of the Law and Order around 58%. Keywords: Financial Development, Agriculture Productivity, Institutional Quality I. Introduction Agricultural productivity is one of the key determinants of high and sustained agricultural growth, and in fact a key determinant of its growth over the longer term. It remains a vital economic driver for developed and developing countries and would play a critical role in eradicating poverty especially in low-income countries. This sector generates a substantial level of revenue while increasing real income (Christiaensen & Demery, 2007). It not only employs an estimated 70 percent of the work-force in low income countries, but it is also a major contributor to Gross Domestic Product (GDP) estimated at approximately 30 percent (The World Bank, 2007). There is an urgent need to make agriculture demand driven, increase value addition in agriculture products and leverage competitive advantage to maximize opportunities in the domestic as well as global market. The farm production level has to grow consistently to maintain food security in the face of ever-growing population. To achieve this goal much interested was given to the role of financial services to agriculture sector. In the twentieth century until the early 80s, giving access to agricultural credit was a part of the Government. Over 70 years, in a context marked by the theories of economic liberalization, the public agricultural funding has been growing criticism that

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Abdelhafidh DHRIFI (Correspondence)

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[email protected]

eventually led to his questioning. Gradually devices agricultural credit will be dismantled as part of liberalization policies in the financial sector. A new approach to promoting access to financial services by the market will emerge in the ‘80s. In this movement, will emerge new financial services organizations, grouped under the terms «decentralized financial systems" or " microfinance". These financial innovations that fit into a market perspective, will develop urban but also in rural areas. Today, the lack of access to financial services remains a major factor blocking modernization of agriculture. To break the deadlock, to build financing arrangements adapted to the specificities of agriculture and consistent with the context of rural financial market, it is necessary to understand the logic and devices on which this new approach is based: that is the subject of this paper. Therefore, this brings new attention to the issue of agricultural finance which is frequently on top of the international development agenda. These concern African countries in highest point. Indeed, a recent literature seems skeptical about the role of financial development in African agriculture productivity and economic development. Past studies have shown that Africa can approach the MDG target is to accelerate productivity agricultural and economic growth. The paper stain to study until what extent the development of the African financial sector can contribute to the improvement of agricultural

Financial Development and Agricultural Productivity: Evidence from African Countries

productivity and economic growth. More specifically, the objectives of this paper are to identify the various channels through which financial development influence agricultural productivity and to highlight credit constraint problem in the global development of agriculture in the region. The paper utilizes aggregate annual panel data, on a sample composed of 44 African countries, from 1990-2012 to estimate a model that capture the interrelationship between financial development and agriculture productivity. The remainder of the paper is organized as follows. Section two presents an overview of the literature on the relationship connecting financial development and agriculture productivity. Section three presents Agriculture sector in African countries. Section four presents the empirical model and describes the variables. Model appraisal and validation are handled in section five. While the paper concludes and presents policy implications in section six. II. Financial Development and Agriculture Productivity: the Literature Revue Agricultural finance is a sectoral concept that comprises financial services for agricultural production, processing, and marketing; this includes short, medium, and long-term loans, leasing, savings, payment services, and crop and livestock insurance. In this context, rural and agricultural underdevelopment was analyzed as the result of an inability of poor households saves and invests; credit was then used as a "lever for development" necessary to start the "virtuous circle" of development and private investment. For example, one comprehensive study looked at the investment decisions of government, financial institutions, and farmers and the effects on agricultural investments and output in India (Binswanger, Khandker, and Rosenzweig 1993). The study covered the 1960s and 1970s, a period when India aggressively expanded its financial system into rural areas. The authors concluded that the availability of credit was more important than subsidized interest rates, and the expansion of banking had a larger impact on output through expanding fertilizer use than through increased investments. Bank expansion was greatly aided by government road investments and reduced transaction costs for banks and farmers. Hence, large farms’ access to credit may be most important for aggregate food production. Larger farms are normally considered more creditworthy and have more ready access to credit from commercial and development banks. Subsistence farmers, on the other hand, are more likely to face difficulty in obtaining formal credit and, therefore, may realize

relatively large benefits from small loans, provided they can get access to land, inputs, and markets. According to the economic literature, the relationship between agriculture and financial systems are often marked by a history difficult. For financial institutions, agriculture is a sector that pays poorly because it has long protected by the State, this has resulted in substantial unpaid deletions debt resulting in a deterioration of attitudes in relation to credit. For the side of farmers, financial institutions are often seen as a rapacious industry applying prohibitive interest rates. In the new approach, all financial institutions are engaged in market logic. They must achieve financial autonomy and provide resources for their development. It is therefore logical that move towards the most profitable and most secure areas, and in so doing, they do show great caution in financing agriculture. Yet despite the important contribution of agriculture to the GDP of the poorest developing countries, the supply of financial services to farmers is still limited. A vast array of literature identifies credit constraints as one of the major problems confronting development of agriculture, especially in the adoption of innovation, not only in African countries, but also globally. Credit constraint constitute a major problem hindering the global development of agriculture, this then implies that the adoption of innovation as well as a possible move towards a bio-based economy especially in developing countries remains an uphill task (Feder G. 1993; Fernandez-Cornejo & McBride, 2002). For example, if in 15 countries of the European Union 89.6 percent of the populations on average have access to financial services (United Nations 2006). The comparable figure in the United States was 91 percent. By cons, in the region of Africa, these rates vary from 6.4 percent to a maximum of 47%. These findings are of concern, since access to a properly functioning financial system is likely to be beneficial to farmers, enabling them to improve their agriculture productivity and to contribute to the development of their countries (United Nations, 2006). It is indicated that this lack of access to finance has become an issue related to the development of agriculture sector. Studies have shown that by providing credit to smallholders, adoption of new technology (e.g. hybrid maize) is being encouraged and the ability of smallholders to bear risk has increased (Essa C. Mussa, Franklin Simtowe and Gideon Obare, 2013). All studies found that a credit constraint had a negative impact on the adoption of agricultural innovation, which ultimately might lead to limited

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agricultural growth, development and increased poverty.

share of agriculture in overall public spending was 5% for Africa, against 10% for Asia.

Providing sustainable financial services for agriculture continues to be a challenge in spite of billions of dollars having been spent in subsidies to strengthen financial institutions to serve smallholders. Nagarajan and Meyer (2005) recognize that providing financial services to agriculture sector is part of an interactive system of financial institutions, financial infrastructure, legal and regulatory frameworks, and social and cultural norms. They further state that government has a role to play in establishing a favorable or “enabling” policy environment, infrastructure and information systems, and supervisory structures to facilitate markets, but it should play a more limited role in direct interactions. In fact, there are a number of examples often used in the literature of successful interventions especially in rural and agriculture finance. Such as, BRI in Indonesia, Calpia in El Salvador, and Prodem in Bolivia among a handful of others are described as being successful providers of agriculture credit (in addition to other services) to rural populations.

For most productions, yields per hectare are among the lowest in the world. The three most important factors of production (selected seeds, fertilizers and agricultural machinery) are little used by producers. In Africa, cultures follow the seasons. When it rains, farmers crops and in the dry season they simply crops the rainy season until the next rainy season to leave the field.

III. Agriculture Sector in African Countries Agriculture was and will always remain one of the most important parts of the sustainability of any economy. It is an essential factor. And in Africa as a region where it could be of great benefit to the people in terms of combating poverty and providing employment to the people at large. Agriculture supports the livelihoods of 80 percent of the African population, provides employment for about 60 percent of the economically active population, and for about 70 percent of the poorest people on the continent. More than 65 percent of the population works in this sector which is causing more than a quarter of the GDP of most countries. Agricultural products account for about 20 percent of international trade in Africa and are one of the main sources of raw materials for industry. The global financial and food crises have brought agriculture into sharp focus, demonstrating that poverty and food insecurity goes hand in hand. Agricultural growth is a proven driver of poverty reduction. When agriculture stimulates growth in Africa, the growth is twice as effective in reducing poverty as growth based in other sectors.

According to estimates of the World Food Program of the United Nations, more than 30 million Africans are currently in need of international food assistance. Researchers of the African reported that the population grew faster than food production on the continent since 1993, which explains the 20% increase in the number of people suffering from hunger - from 176 million to 210 million. Commercial exports are not doing better, the share of Africa in world trade has declined in nine of its ten main agricultural export products.

Despite its importance, the agricultural sector has been neglected for decades. Most often, farmers do not have access to the assets they need to make the best use of agriculture, eg seed improved, fertilizers or adequate water supply. Priority was given to other sectors and thus the share of agricultural expenditure in total expenditure declined from 6.3% in 1990-1991 to 4.6% at the end of the decade. In 1998, the average

Due to irregular in large parts of Africa rains, it is urgent to increase the area of irrigated land. According to the United Nations Food and Agriculture, only 5% of arable land is irrigated in Africa, against 38% in Asia. While much of Africa has abundant supplies of water, "the region uses less than 3% of its water resources, the lowest percentage in the developing world". This is a very traditional system that can only work when the population is relatively small and that the seasons are constant and follow their pace without a problem. Once one of these factors is missing, it is a recipe for disaster.

Access to capital and credit for smallholders has been a perennial problem and the subject of analysis in these last few decades. Small farmers in Africa, work in risky environments that are expensive for financial institutions to serve. Most have little or no usable collateral and little experience with financial services. A history of public intervention in credit markets has created expectations that defaults on agricultural loans will carry little penalty to the borrower. All of these challenges for outreach of financial institutions to small farmers are relevant for young farmers, and are compounded by the fact that young farmers have little experience.



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IV. Econometric Specification, Definition Variables and Estimation Techniques

of

IV.1. Model Specification Based on theoretical analysis on agriculture and to assess the impact of the financial development, we adopted a standard model building on previous studies. The model explains agriculture productivity by a core set of control variables, overall Employment in Agriculture (% of total employment), Agricultural Irrigated Land (% of total agricultural land), Arable Land (% of land area) and Fertilizer Consumption (kilograms per hectare of arable land). These variables are expected to influence positively the agriculture productivity. We add growth of GDP per capita, to capture the contribution of economic development. It is incorporated in the model to reflect the level of development of the economic system. We therefore expect a positive coefficient of this variable. We introduce also the number of people who accessed the telephone lines per 100 inhabitants to measure the quality of infrastructure (infrastructure). The baseline model is then augmented with the financial development measured by domestic credit to private sector to GDP and institutional quality which is measured by Law and Order-also called Rule of Law. We notes that the empirical results suggest, however, that the past agriculture productivity rate is suited in the explanation of the current agriculture productivity. The following presentation of the structure of the model of regression is based on a dynamic specification.

APit   0   1 X it   2 INSTit   3 FDit  it  it Where

1

APit is the indicator of agriculture

productivity for a country i at a period t;

X it is a set

of potential agriculture productivity determinants (cited above), FDit is an indicator of financial development and

i

is the country specific effect

and it is the error term. With

i

and

it

are independently distributed,

E     E it   0 , E   *it   0 To test the importance of institutional quality in determining the relationships between financial development and agriculture productivity, we adopted the following model:

APit   0  1 X it   2 INSTit   3 FDit   4 INSTit * FDit  it  it  2 Where INSTit represent the institutional quality indicator. We add on our model INST*FD to capture the interaction term between the institutional quality and the level of financial development. We are particularly interested in the effect of the interaction term because we suspect that institutional quality may complement or substitute other conditions. IV.2. Definitions of Variables We compiled data for a sample of 44 African countries over the period 1990-2012. The sample sizes and the period of study are limited by the availability of data on control variables. Agriculture Productivity (AP): it is measured by agriculture value added (% of GDP). By definition, agricultural productivity is the primary source of economic growth and poverty reduction in most agriculture-based economies. The expansion of smallholder farming can lead to a faster rate of growth, by raising the incomes of rural cultivators and reducing food expenditure, and thus reduces income inequality (Mellor 1999; Magingxa and Kamara 2003; Diao and al. 2010; Resnick 2004; Bahram and Chitemi 2008; Anríquez G. and K. Stamoulis, 2007; and World Bank, 2008). As observed by Ravallion (2000), a rise in average household income by 2 percent leads to a fall in the poverty rates by about 4 percent on average. The World Development Report (2008) also observed that GDP growth originating in agriculture is about four times more effective in reducing poverty than GDP growth of other sectors (World Bank, 2008). Financial Development (FD): it is measured by the ratio of domestic credit provided by banking sector relative to GDP. This indicator is generally used in empirical studies. Institutional Quality (INST): here, we opt for the widely used indicator of Law and Order-also called Rule of Law-compiled by International Country Risk Guide (ICRG), which assesses the strength and impartiality of the legal system, and the popular observance of the law. This indicator ranges from 0 to 6, with a higher figure indicating a better quality and enforcement of the legal system (Laeven, 2002). Technological Innovation (TI): it is measured by agricultural machinery (tractors per 100 sq km of arable land). Technology can help reduce the higher transportation and communication costs found in rural areas. In a world where communication technology and information tend to define common



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place in many region of the world, Africa continue to perpetuate extensive technologies lack of access to appropriate information, training, modern production resources. Number of subscribers to telephone lines per 100 inhabitants: is an indicator measuring the level of infrastructure. It is introduced into the model to capture the role of infrastructure agriculture productivity. It represents the degree of development in the field of information technology and communication, which is a sector that could have a positive influence on the agriculture sector. It is measured by the average of the number of telephone mainlines per 1000 people. Poor infrastructure can impede agricultural activities in Africa. The key challenges are to improve poor conditions of the market facilities and transportation systems, including road and rail. IV.3. Estimation Techniques To test the effect of financial development on agriculture productivity in Africa the estimation technique used is the System Generalized Method-ofMoment (GMM) estimator developed by Blundell and Bond (1998). The estimator combines two sets of

equations. The first set includes first-differenced equations where the right-hand-side variables are instrumented by the levels of the series lagged one period or more. The second set consists of the equations in levels with the right-hand side variables being instrumented by lagged first of higher-order differences. The GMM estimator will be used because it has a number of advantages. For instance, Beck et al. (2000) argue that the GMM panel estimator is good in exploiting the time-series variation in the data, accounting for unobserved individual specific effects, and therefore providing better control for endogeneity of all the explanatory variables. We use the GMM estimator to investigate the financial developmentagriculture productivity nexus in African countries. V. Main Results and Discussion The regression results that we have made over the period 1990-2012 are presented in the table presented below. All regressions are run with GMM. The test of second-order serial correlation justifies the acceptation of the null hypothesis, and the Sargan test of over identification suggests that we cannot reject the hypothesis of the validity of instruments.



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Table 1: Robustness analysis of the relationship between financial development and agriculture productivity Variables

(1)

(2)

(3)

GDPG

0.171

0.166

0.169

(2.04)**

(2.06)**

(2.19)**

0.027

0.027

0.027

(3.48)***

(2.39)**

(2.56)***

0.173

0.174

0.171

(7.53)***

(7.18)***

(7.92)***

0.424

0.418

0.475

(2.60)**

(2.63)**

(2.56)**

0.043

0.0436

0.0431

(2.81)***

(2.73)***

(2.27)***

0.095

0.091

0.089

(1.51)

(1.58)

(1.64)*

-0.022

-0.022

-0.022

(-1.89)**

(-1.82)**

(1.95)**

--

0.032

0.031

(2.81)**

(2.97)**

--

0.038

Techn. Innovation

Agr. Irrig Land

Arable Land

Employ, in Agr

Fert Consomption

Fin. Devp

INST. Qual

Fin. Devp*INST. Qual

--

a

(2.37)** 4.74

4.79

6.19

(5.623)***

(6.425)***

(7.164)***

Nombers of obs.

1012

1012

1012

Number of countries

44

44

44

Sargan Hansen Test

0.74

0.77

0. 81

AR2

0.48

0.52

0.54

Constant

Notes: * significant at 10% ** Significant at 5%; *** Significant at 1%.

2

and

 3 , of the equation (1) represent the marginal

impacts respectively of the institutional quality and financial development. On the contrary,  4 in equation (2) represents the marginal impact of financial development conditional on the level of

institutional quality. We note that in the first model (without the introduction of institutional quality) the coefficient of financial development measured by domestic credit to private sector to GDP enter with a significantly negative coefficient proving that financial system cannot contribute to the



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improvement of agricultural productivity in African countries. This results can be explained by the fact that financial sector in African countries still unable to provide the necessary financial services especially to rural farmers. This can be explained several reasons: first, the demand for facilitation of deposit is low due to macroeconomic instability or gaps in the regulation and supervision of financial institutions. Second, the lack of a strong legal system in the region prevents lenders to obtain reimbursement of their loans. The third reason may be due to space factor. In the same context, and to fully appreciate the role that can play financial system on agriculture sector in the region of Africa, we re-estimate the same model taking into account the role of institutional quality in determining the financial development-agriculture productivity relationships. The results presented in model (2) shows that there is a significant and positive impact of institutional quality on agriculture productivity. In fact, a 1% increase in this indicator leads to an increase in agriculture productivity by 3%. The evaluation of model (3) of the same table suggests that the institutional quality changes sign of impact on the agriculture productivity to a certain level because the interactive term with the indicator of the financial development is shown statistically significant. The coefficients on the interaction term between the institutional quality and the financial development come out positive and significant. This result suggests that the non significant association between a financial system and agriculture productivity as shown in model (1) and model (2) could be positively significant as institutions grow stronger and even reverse. To obtain the level of threshold of institutional quality, we have to calculate from (model 3, Table 1)

3

the function:

4

being equal to

zero. Then the threshold of institutional quality is equal to (

3 4

) According to table 1, this

threshold is approximate at a rate of the Law and Order around 58%. On variables of control, the results show that the GDP per capita appears to have a positive and significant effect on the agriculture productivity rate and that it is consistent with the expected result, which confirms the existence of a strong positive relationship between the GDP per capita and agriculture productivity rates. This suggests that high

levels of economic development are associated with higher levels of agriculture productivity. As for the coefficient on the variable infrastructure, it also appears to be positive and significant impact on agriculture sector, confirming the results of previous studies. For the case of the elasticity’s associated with employment in agriculture, agricultural irrigated land, they appears to affect positively and significantly the agriculture productivity in Africa. We notice that employee’s agriculture plays a significant role in agriculture performance. A 1% change in employee’s agriculture raises agriculture productivity by about 2.3%. The results show that agricultural irrigated land and the arable land has a positive and significant impact on agriculture productivity. As regards the fertilizer consumption, it appears to have no significant impact on agriculture performance. This justifies the lack of use fertilizer consumption by farmers. On the impact of technological innovation on agriculture productivity rate, the equation shows that the variable has positive and statistically significant impact on agriculture sector. An increase of technological innovation by 1% leads to increase in agriculture productivity rate by 2.7 %. Hence, infrastructural quality, as captured by telephone line per 1000 people, play significant role in improving agriculture productivity. This allows us to say that it is necessary to invest considerably in infrastructure because, as account given the low population density in African countries, the infrastructure that connects farmers to markets is costly and investment in road infrastructures, institutions and the public sector are essential. Table 2: List of the sample countries Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cap Verde, Central African Republic, Democratic Republic of the Congo, Djibouti, Egypt, Equatorial Guinea, Ethiopia, Gabon, Ghana, Guinea-Bissau, Ivory Coast, Kenya, Libya, Madagascar, Malawi, Mali, Morocco, Mozambique, Namibia, Nigeria, Niger, Republic of the Congo, Rwanda, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Tanzania, Tchad, The Gambia, Togo, Tunisia, Uganda, Zambia and Zimbabwe.



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As a whole, we can say that financial development is only one condition for improving agriculture productivity, and the successful provision of finance requires better quality of institutions, supportive policies and infrastructure. We thank that the key success of agriculture performance are to: (1) increase the area of irrigated farmland in Africa and improve land management and farming techniques to conserve and improve soil quality, (2) to investment in rural infrastructure, including roads and railways, storage sites and processing, markets, communication systems and reliable supply for farmers, (3) to strengthen research and development, particularly with regard to technology and farming methods and advanced quickly and truly benefit farmers , suppliers and buyers of progress. IV. Conclusion and Policy Implications In this essay, we have studied the financial development-agriculture productivity nexus. Estimations are conducted with a panel data of 44 African countries over the period of 1990-2012 using GMM-System estimator. The empirical results show that financial system by itself cannot favor agriculture sector in African countries, but at the presence of a good quality of institutions, it contribute positively to agriculture performance. Our finding shows also that, in the presence of a certain threshold of quality institution, African countries can profit of financial development once these threshold conditions are satisfied. This threshold is estimated at a rate of the Law and Order around 58%.

financial services, improving the fit between the financial and the agricultural sectors and coordination of the agricultural sector and developed public policy. Hence, it is essential to identify needs that may face farmers in a context where access to formal finance is very selective and little incentive. Adapt type of financing related to agriculture requires to identify the needs of farmers according to their lifestyle (Wampfler and Lapenu, 2002). The requirements are: (i) needs Short-term: the farmer needs goods such as inputs, fungicides, vegetable crops and culture less than 12 months labor employed, rental and sharecropping, fattening, storage and processing of production. (ii) Requirements Medium-term: the equipping for intensification, marketing, storage (buildings), purchase of animals, land purchase. (iii) The need for long-term are: the creation of the largest plantations of perennial crops. As a whole, we can conclude that making the African region’s agriculture competitive depends on getting policies right, strengthening institutions, and increasing and improving investments in the sector. Among other things, the region requires macroeconomic policy reforms, land policy reforms that enable smallholders to obtain access to land, scaled-up public investments in agriculture, greater private investment through public-private partnerships, and institutional reforms to make markets work better and create self-sustaining rural financial systems. References

These findings may lead to some economic implications: macroeconomic policies should encourage the development of financial systems. However, for financial development may affect positively agriculture sector, it should allow better access to these financial services (deposits, loans, etc.). We thank that it is essential to create an environment favourable to agriculture growth, financial system requires a number of economic and institutional conditions prerequisites. The case of African countries, which suffer from high levels of corruption, heavy bureaucracy and a high level of collision between the political and the financial system, we show the importance of the institutional factor in the success financial system. This is why it is rational to believe that efforts to improve the quality of institutions and political environment are also crucial to the success of the financial system to grant loans to farmers.

[1]

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