Proceedings of the International Conference on Contemporary Economic Issues 2014
Is there a Natural Resource Curse in Finance-Growth Nexus? The Case of Malaysia Ramez Abubakr Badeeba,*, Hooi Hooi Leanb a School of Social Sciences, Universiti Sains Malaysia, Penang, Malaysia
[email protected] b
School of Social Sciences, Universiti Sains Malaysia, Penang, Malaysia
[email protected]
Abstract This paper examines empirically the finance-growth nexus in Malaysia and identifies the existence of natural resource curse in this nexus. ARDL approach to cointegration and Toda Yamamoto causality test have been applied. The results indicate that there is positive relationship between financial development and economic growth in Malaysia. The results also strongly support the view that economic growth causes financial development. On the other hand, there is a negative impact of natural resource on this relationship which refers to the existence of resource curse in Malaysia. This curse hampers the role of financial development in economic growth. Keywords: Financial Development, Natural Resource Dependence, Economic Growth, Natural Resources Curse, Malaysia.
1. Introduction The finance-growth nexus has been received a considerable attention among economists. Ambiguity surrounding its nature and direction made it one of the most enduring controversial issues in the field of economics. Researches about finance-growth nexus can be traced back to Schumpeter (1911, 1934) who stressed on the role of banks in growth stimulating by identifying entrepreneurs with good growth prospects, and therefore help to reallocate resources to their most productive uses.Along the same line, Mackinnon (1973), Shaw (1973) and Fry (1978)asserted that the financial intermediation (banks) has an important role in economy as determinant of its real economic growth rate, by raising saving and capital accumulation. This idea has been supported with modern analysis, which a large body of empirical evidences now exist to support this “Schumpeterian” logic (Abu Bader and Abu Qarn, 2008b; Beck, 2011; Bittencourt, 2012). Even though, it is well recognized that the financial sector crucial for economic growth, it is fair to say the debate in this respect is ongoing and the issue remains controversial. Different conflicting perspectives have also been presented by other economists about the link, while some of them still believe in relationship between financial development and growth but in bidirectional manner (Singh, 2008; Abu Bader and Abu Qarn, 2008a), some do not, and stressed that there is no relationship between finance and growth (Lucas,1988). Although a vast amount of theoretical and empirical literatures dealing with direct financegrowth nexus, considering this relationship in the context of natural resources-based economies has been fewlyaddressed. Only a few attempts (Nili andRastad, 2007; Beck, 2011; Barajas et al., 2013) have recently discussed the role of oil resource dependence in this 55
Proceedings of the International Conference on Contemporary Economic Issues 2014 relationship. These researches discussed the finance-growth nexus in a panel of countries, ignoring the existence of large variation among these countries in term of degree of dependence on oil and in term of financial development because of differences in institutional and economic structure and differences in type of financial instrument )Beck et al., 2008). This hypothesis, in fact, lies under what is called “natural resource curse” hypothesis, that is, the idea that economic growth underperformance and weak economic sectors in some rich resource countries would be partly explained by the highly dependence on natural resource revenues, especially minerals and oil. This curse does not come from possessing the natural resource which has favourable effects, but from the management of these resources in certain countries and make it a primary source of income by ignoring other income sources (Brunnschweiler and Bulte, 2008). However, delving into potential effects of natural resource dependence on different economic sectors across countries in general and on financial sector in particular has not been widely addressed. Several explanations have been presented for this relationship. These explanations ranging from supply and demand sides hypothesis introduced by Beck (2011) to the thesis introduced by Galyfason and Zoega (2006) and Nili and Ratsatd (2007). The former focuses on the role of “mismanagement and poor policy” channel and Dutch disease scenario in shifting factors of production away from the non-resources traded goods sectors with its effects on financial sectors deepening or size, whereas the latter focuses on the effect of natural resource dependence on financial sector efficiency or its ability to translate the saving into investment and later translate these investment into economic growth. Hence, we believe the potential effects of natural resource on finance-growth is very much an open question and need to be studied in different countries separately to fill the gap in the literature. Thus, in contrast to previous studies, this paper aims to investigate the relationship between financial development and economic growth and its interaction with natural resource dependence in one of the biggest Southeast Asia natural resource economies, Malaysia. Malaysia is a very interesting case study for this subject for two reasons. First, Malaysia has a rich history of financial sector reforms. A series of financial restructuring programs that aimed at improving the financial system had been launched since the 1970s. Immediately after the Asian financial crisis hit the country in 1997, a series of macroeconomic policy responses such as capital controls and reflationary policy have taken place. This was followed by restructuring in the corporate and banking sectors. However, despite these changes in the financial environment, no study has been taken a close look at the effect of these financial sector policies on the financial system, with particular reference to the Malaysian experience. Second, Malaysia is endowed with diversified natural resources that include oil, rubber, tin, and palm. However, it is considered among those countries that have beaten the curse due to its performance on poverty alleviation and GDP respectable numbers. However, one major question arises here. Do the GDP growth numbers mean that Malaysia really escapes from the curse? Jeffery Sachs (2007) says, “One reason for [resource curse] is that large earnings from oil and other natural resources can have adverse effects on other sectors of economies, particularly those sectors that can be motors for sustained economic growth" (p.175). This mean that the resource curse might be exist or threat one of economic sectors that usually play a prominent role in economic growth such as financial sector. Therefore, this paper is an attempt to 56
Proceedings of the International Conference on Contemporary Economic Issues 2014 identify the existence of resource curse in financial sector and its relationship with economic growth in Malaysia. To the best of our knowledge, this is the first study identifying the role of natural resource dependence on finance-growth nexus in Malaysia.Accordingly, the main objective is to shed light on the relationship between financial development and economic growth in somewhat different view by investigating empirically how the natural resource affects this relationship. The rest of this paper is organized as follows: Section 2 discusses the data and methodology, empirical results and discussion are presented in section 3. Finally, section 4 concludes.
2. Data, Model and Methodology 2.1 Data and Measurements Real GDP per capita in 2005 USD price is used as economic growth measurement, whereas financial development measurement, natural resource dependence measurement and control variable are chosen based on the followingjustifications. Financial Development We use domestic credit to private sector as share of GDP 1 to measure the level of financial intermediation. It is considered as one of the best indicators to measure financial development which has been widely used in literature (King and Levine, 1993; Nili and Rastad, 2007). Natural Resource Dependence “Resource dependence” refers to the degree that an economy relies on resource revenues. Following Bhattachrayya and Hodler (2014),we use the natural resource rent which includes energy and minerals as a percentage of GDP as the indicator of natural resource dependence. Control Variables Trade openness is included in the model as control variables because it is an important factor in financial development (Beck, 2011; Yuxiang and Chen, 2011). The ratio of the sum of commodity exports and imports to GDP is estimated as trade openness. The sample period is1970-2011.All data are obtained from World Development Indicator. 2.2 Model The economic literature often suggests the following model for finance-growth nexus: FD f (Y , CV )
whereFD is the financial development indicator, Y is the economic growth indicator, and CV is the control variable that linked to economic growth. Therefore, our estimation equation as follows after transforming the variables into natural logarithm form: ln FDt 0 1 ln GDPCt 2 ln TOt t (1)
1
Domestic credit to private sector refers to financial resources that provided to the private sector, such as through loans, purchases of non-equity securities, and trade credits and other accounts receivable, that establish a claim for repayment.
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Proceedings of the International Conference on Contemporary Economic Issues 2014 wherelnFDis the natural logarithm of domestic credit to private sector as share of GDP, lnGDPC is the natural logarithm of real GDP per capita in 2005 USD, lnTOis the natural logarithm of trade openness to GDP, is the error term. In order to analyze the impact of natural resource dependence, we add the natural resource dependence indicator to equation (1). We capture the impact of dependence of natural resource revenues on finance-growth nexus by adding an interaction term between GDP per capita and natural resource dependence. Therefore, our final estimation equation is the same as Beck (2011) that is: ln FDt 0 1 ln GDPC 2 ln NRt 3 Interact t 4TO t t (2) wherelnNR is the natural logarithm of natural resource rent as share of GDP, and Interact is the interaction term between GDP per capita and natural resource rent. 2.3 Methodology This paper uses autoregressive distributed lag (ARDL) bound testing approach of cointegration by Pesaran et al. (2001). It is reliable and applicable irrespective of whether the underlying regressors are I(0) or I(1) and performs well for small sample size. The ARDL version of the estimation model can be specified as: ln FDt 0 1 ln FDt 1 2 ln GDPCt 1 3 ln NRt 1 4 Interact t 1 o
p
i 1
i 0
5 ln TOt 1 6 ln FDt i 7 ln GDPCt i q
r
s
i 0
i 0
i 0
(3)
8 ln NRt i 9Interact t i 10 ln TOt i t
The F statistic is used for testing the existence of long run relationship among the variables. We test the null hypothesis, H 0 : 1 2 3 4 5 0 , that there is no cointegration among the variables. The F statistics is then compared with the critical value given by Narayan (2005), which is more suitable for small samples. If the computed F-statistic is greater than the upper bound critical value, then we reject the null hypothesis and conclude that there exists steady state equilibrium among the variables. If the computed F-statistic is less than the lower bound critical value then the null hypothesis of no cointegration cannot be rejected. However, if the computed F-statistic lies between the lower and upper bounds critical values, the result is inconclusive. Once cointegration is confirmed, we estimate the long run and short run coefficients of the regressors. Thispaper also adopts Toda and Yamamoto (1995) test for causality, which allows us to derive much more robust conclusion. This test suggests the following augmented VAR framework with p = (k+dmax) lag length. Here k is optimal lag length for the VAR system determined by Akaike’s information criterion (AIC). The performance of dmax=1 is better than any other order of dmax. Thus dmax = 1 is used in this study. We then apply the standard Wald test to the test k VAR coefficients matrix in order to draw the inference about the direction of Granger causality.
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Proceedings of the International Conference on Contemporary Economic Issues 2014 ln FDt 1 B11,1 ln GDPC t 2 B21.1 ln NRt 3 B31.1 interact t 4 B41.1 ln TO B . t 5 51 1 B11,k B21.k B31.k B41.k B . 51 k B11,p B21.p B 31.p B41.p B51.p
B12.1 B13.1
B14.1 B15.1
B22.1 B23.1
B24.1
B25.1
B32.1 B33.1
B34.1
B35.1
B42.1
B44.1
B43.1
B52.1 B53.1
B54.1
B12.k B13.k
B14.k
B22.k B23.k
B24.k
B32.k B33.k
B34.k
B42.k B43.k
B44.k
B45.1 B55.1
B25.k B35.k B45.k B55.k
B15.k
B52.k B53.k
B54.k
B12.p B13.p
B14.p
B22.p B23.p
B24.p
B32p
B33p
B34.p
B35.p
B42.p
B43.p
B44.p
B45.p
B52.p
B53.p
B54.p
B55.p
B15.p B25.p
ln FDt ln GDPCt ln NRt ... interact t ln TO t ln FDt k ln GDPCt k ln NRt k interact t-k ln TO t k ln FDt p 1t ln GDPCt p 2t ln NR t p 3t interact t-p 4t ln TOt p 5t
3. Empirical Findings and Discussion All variables are integrated in order one2. Hence, ARDL approach can be applied to analyze the long-run relationship among the variables. The ARDL approach is sensitive to the number of lags used. Given the limited number of observations, lags up to two years are imposed on the first difference of each variable and AIC criterion is used to select the optimal lag length for each variable. The AIC suggests ARDL (1,0,1,0,0). The result of ARDL bound test of cointegration is tabulated in Table 1. Table 1 Result from ARDL (1,0,1,0,0) Cointegration Test F-statistic 3.8373* Critical Values 1% level 5 % level 10% level Lower Bound 4.045 2.962 2.483 Upper Bound 5.898 4.338 3.708 Note: * denotes the significance at 10% significance level. Critical values bounds are from Narayan (2005) with unrestricted intercept and no trend.
Table 1 shows that the calculated F statistic is higher than the upper bound critical value at 10% level of significance. This result provides evidence for the existence of long-run relationship among economic growth, financial development, natural resource dependence and trade openness in Malaysia. Table 2 Long Run and Short Run Analysis Panel A. Long Run Coefficients Variable Constant
LnGDPC
t-statistic -1.5809 1.7315
7.2659* -0.9131*
1.746 -1.739
0.07453
1.1047
Coefficient
t-statistic
LnFL
LnNR
Interact LnTO Panel B. Short Run Coefficients Variable ln GO
2
Coefficient -16.531 2.6162*
Result is available upon request.
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Proceedings of the International Conference on Contemporary Economic Issues 2014 Constant
0.031 -0.789
0.144 -0.955
0.063
0.037
Interact
-0.048
-0.232
LnTO ECt 1
-0.070
-0.957
-0.373***
-4.517
Panel C. Diagnostic Test Test χ2 serial χ2 ARCH
F-Statistic 0.008 0.005
Prob-Value 0.929 0.942
LnF
LnGDPC LnNR
χ2 Ramsey
0.525 Note: ***.* denotes the significance at 1% and 10% level respectively.
0.474
Table 2 panel A shows that financial development indicator and economic growth are positively related in the long run and statistically significant. In addition, the natural resource has a positive direct impact on financial development. This might be a result of the significant flows from natural resource revenues into economy through financial sector channel. Increase of natural resource revenues encourages the government in spending on new investments activities which in turn stimulate the demand for financial services. The most interesting finding is the negative sign of interaction term. The finding implies that the significant relationship between financial development and economic growth become weaker with the increasing of natural resource dependence. This result is consistent with the Nili and Rastad (2007), Beck (2011) and Barajas et al. (2013) who found that natural resource dependence weakens the finance-growth nexus. While the direct effect of natural resource on financial development is significantly positive, the indirect effect through economic growth is negative. It seems that natural resource dependence has a negative indirect impact on the financial development through hampering its effectiveness in translating savings into productive investments which in turn weaken the nexus between financial development and economic growth. Table 2 Panel B shows the short run results. The coefficient of the lagged error correction term suggests that a deviation from the long-run equilibrium following a short-run shock is corrected by about 37% per year. The model passes all diagnostic tests and well specified. Since all variables are cointegrated, we can perform Toda-Yamamoto causality test to find the direction of causality between financial development and economic growth. Table 3 reports the relationship between financial development and economic growth in Malaysia goes from economic growth to financial development. The financial intermediation in Malaysia does not play its role in fostering economic growth, but it is benefited from the success achieved in economic growth that provides the means to implement well developed financial structures. These results are in line with Ang and Mckibbin (2007). In developing countries, financial intermediation affects economic growth mainly through mobilizing savings and allocating funds to productive investment projects that will generate good returns. Based on our findings, the financial intermediaries in Malaysia do not seem to be efficient in creating high productive investments as in most natural resource dependence economies. The high share of natural resource rent to GDP make the economy exposed to 60
Proceedings of the International Conference on Contemporary Economic Issues 2014 volatility in international price of natural resource. This volatility increases the uncertainty in investment climate in Malaysia which encourage the financial intermediaries to defer longer term capital investment decisions or engage in short term, lower risk activities at the expense of more productive investments. Furthermore, one of the main natural resource curse channels in natural resource dependence economies is mismanagement economic policy and neglecting human development. The easy access of resources rent may relive government of working on developing its human capital which may negatively reflected on the performance of various economic sectors i.e. financial sector. Table 3 Results of Toda Yamamoto Causality Test Dependent Variable
ln GDPC ln FD
Independent variables ln GDPC -
-4.104** Note: ** denotes the significance at 5% significance level.
ln FD
OILR
-0.006 -
4. Conclusion This paper examines the relationship between financial development and economic growth in Malaysia and identifying the role of natural resource dependence in this relationship. The results reveal positive relationship between financial development and economic growth in the long run. We find evidence about the negative impact of natural resource dependence on the relationship between financial development and economic growth. The increasing the natural resource dependence weaken finance-growth nexus in Malaysia. We also find unidirectional causality from economic growth to financial development which means financial development does not play its role in fostering economic growth. This might be a reason of natural resource curse. The result offers mix of policy implications. On one hand, Malaysia government should be aware of the indirect risk for natural resource dependence to financial sector. Financial development which is achieved by increasing the economic growth, decreases with the highly dependence on natural resource rent. Therefore, the government should diversify its economic activities and reduce its dependence on natural resource such as oil. In particular, financial sector which can be offer greater opportunities over the short and long term future. Moreover, natural wealth can be used as a foundation for transitioning to production processes which lead to more diversified economy. On the other hand, the financial sector in Malaysia does not play its proposed role in fostering economic growth, but in contrary it is benefited from success achieved by general economic performance. Hence, financial sector improvement efforts must be continuous to increase the contribution of this sector in economic growth. 5. References Abu-Bader, S.& Abu-Qarn, A. S.(2008a) Financial development and economic growth: The Egyptian experience. Journal of Policy Modeling 30, 887-898. Abu-Bader, S & Abu-Qarn, A. S.(2008b) Financial development and economic growth: empirical evidence from six MENA countries. Review of Development Economics 12, 803-817. 61
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