THE IMPACT OF BANKING SECTOR REFORMS AND CREDIT SUPPLY ON AGRICULTURAL SECTOR: EVIDENCE FROM NIGERIA
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1 THE IMPACT OF BANKING SECTOR REFORMS AND CREDIT SUPPLY ON AGRICULTURAL SECTOR: EVIDENCE FROM NIGERIA ABSTRACT Lawrence O. Osa-Afiana Lagos Business School, Pan-Atlantic University, Lagos, Nigeria Ikechukwu Kelikume Lagos Business School, Pan-Atlantic University, Lagos, Nigeria The Nigerian government has embarked on banking reforms over three decades with the aim of, among others, enhancing competitiveness in financial services, promoting investment, and ensuring efficiency in resource allocation. One area that is of interest to the government in reforming the banking sector is the improvement in banking sector lending and credit allocation to the agricultural sector. This study examined the impact of the increased discretionary allocation of credit to the private sector due to the banking sector reforms and the various directed funding programs by the regulatory authority on agricultural output in Nigeria over the period of The study used time series data sourced from World Bank and the Central Bank of Nigeria Statistical Bulletin. The method applied to test the impact of banking sector reforms, agricultural sector credit supply on agricultural sector output in Nigeria was the impulse response functions and the variance decomposition of Vector Error Correction Model (VECM). The results revealed that both the banking sector reforms and credit supply to agricultural sector have positively affected agricultural output in Nigeria. However, the impact of agricultural credit supply on agricultural output proved to be very weak and insignificant. The study suggests that the discretionary allocation of credit, particularly by the monetary authorities or the banking sector, may not necessarily achieve the goal of massive growth in the agricultural sector. There is an urgent need for institutional and infrastructural reform to make the financing of the agricultural sector more productive. JEL Classification: E5, G28, Q1 Keywords: Banking Sector Reforms, Credit Supply, Agricultural Sector, Nigeria Corresponding Author s Address: losa-afiana@lbs.edu.ng INTRODUCTION The period of in Nigeria was characterized by a series of progressive banking sector reforms. The aim of the reforms include liberalizing the interest rates, enhancing competitiveness in financial services, improving efficiency in resource allocation, promoting investment, reducing control on credit and deepening the financial sector, particularly the banking industry (Omoruyi, 1991; Balogun, 2007; Anyanwu, 2010; Udah and Obafemi, 2011). The reforms started with the Structural Adjustment Program that included macroeconomic stabilization measures followed by deregulation of the banking industry that allowed entry of a large number of banks and market determination of exchange and interest rates. As weakness in the banking sector became evident, reform efforts were focused on strengthening the banking system through mandatory progressive increases in bank capital base and the introduction of corporate management & governance standards. These reforms culminated in mandatory industry consolidation in 2005 that reduced the number of banks from 85 to 25 banks by The agricultural sector is a vital sector of the Nigerian economy. Although its share of the Gross Domestic Product (GDP) has progressively declined from 70% in the early 1960s to 48.8% in the 1970s to 22.2% in the 1980s (Mang, 2009; Okezie & Amir, 2011; Ugwu and Kanu, 2012; Akpaeti, 2013). It is the largest employer of labour as it serves as a source of livelihood for two-third of the Nigerian population (Usman, 2006). Successive federal governments have recognized the need to diversify the Nigerian economy from its dependence on the oil sector for revenues and foreign exchange and the agricultural sector has been targeted as a preferred sector in the diversification strategy. In recognition of the important roles of agriculture in driving economic growth and development, the Nigerian government embarked on promoting increased funding to the sector. Even when it abandoned its mandatory agricultural lending limits for banks in the wake of the reform efforts, the Central Bank of Nigeria (CBN) continued with intervention programs to ensure adequate flow of funds from the banking industry to the agricultural sector. These intervention measures have included moral suasion to encourage discretionary bank lending to the sector and direct agricultural finance programs through the agency of the commercial banks. These CBN directed credit programs that were in operation during the period of the banking sector reforms, 682
2 included the Agricultural Credit Guarantee Scheme Fund (ACGSF), Agricultural Credit Support Scheme (ACSS), Commercial Agricultural Credit Scheme (CACS) and the Nigerian Incentive-based Risk-sharing System for Agricultural Lending (NIRSAL). It would appear that the banking reforms and the various CBN agricultural finance initiatives have not resulted in consistent improvements in agricultural production and productivity. For instance, official CBN statistics and World Bank data show that the annual growth rate of Nigeria agricultural output fell from 55.2 percent in 2002 to 7.4 percent in It further dropped to 5.9 percent at the end of 2009 and further declined to 2.9 percent in Following the collapse of oil prices and the massive shortfall in government revenues and attendant adverse economic and social repercussions, the need for accelerated investment in the Agricultural sector has become more urgent. The study is undertaken to assess the impact of the increased discretionary allocation of credit to the private sector as a result of the banking sector reforms and the various directed funding programs by the regulatory authority on agricultural output in Nigeria. The result of this study should inform the design of appropriate strategy to fund the development of the agricultural sector. This paper has been structured into six sections. The first part is this section that introduced the research topic. The second section presents relevant literature. The third section presents the model and methodological issues. The fourth section shows results and discusses the findings while the fifth section presents the conclusion and recommendations. LITERATURE REVIEW Among the rationale for the banking sector reforms is to facilitate rapid economic development by remedying the marginal role of the banking system in the development of the real sector of the Nigerian economy (Abdulahi, 2007). Presumably, as the level of financial intermediation increases as a consequence of the reforms, lending rates will fall, and increased lending to the real will boost economic growth and stimulate employment. The post-consolidation big banks would have larger funding resources and greater capacity for risk-taking and, therefore, are better able to finance critical growth sectors, such as the agricultural sector, of the economy. The link between financial liberalization, financial intermediation, and economic growth in developing countries has been explored in literature. Ang and McKibbin (2007) using data for Malaysia, observed that for small economies, there is a positive relationship between financial development arising from financial liberalization and economic growth. This observation was in accord with the findings of Rousseau and Vuthipadadom (2005) from an analysis of 10 Asian economies over a 50- year period ( ). The study results indicated that while finance was a driving force in promoting investments in these countries, the evidence of financial factors in output was weaker. However, the study did not indicate any differences among the economic sectors in output response to financial liberalization and intermediation. Balogun (2007) examined the performance and pitfall of banking sector reforms about the Nigerian economy. He found that the reforms were characterized by improved incentives but noted that the incentives did not lead to increased credit supply to the real sector of the economy. The outcome of the study further revealed that the reforms tend to be associated with the rise in inflationary pressures. Udah and Obafemi (2011) investigated the impact of financial reforms in both the agricultural and manufacturing sector using VAR. They found that bank credit to the private sector had positively influenced both the manufacturing and agricultural sector in the short run and long run. This result implies that bank credit is a strong financial variable that influences long-run economic growth and development. Onoja, Onu and Ajodo-Ohiemi (2011) explored the contributions of financial sector reforms and credit supply to the agricultural sector by comparing the effects of reforms policies on access to institutional credits in the agricultural sector of the Nigerian economy before and after the reforms. They found that there was an exponential increase in agricultural credit supply in the economy after the commencement reform. The study further found that stock market capitalization, interest rate and the immediate preceding amount of credit guaranteed by ACGSF significantly influenced the volume of credit supplied to the agricultural sector. The outcome of this study implies that there has been an upward trend in agricultural lending after the financial reforms, suggesting that the reforms have a favourable and multiplying effect on agriculture. Akpaeti (2013) investigated the impact of financial sector reforms on agricultural investment in the Nigerian economy using cointegration and vector error correction model. The study revealed that the financial reforms significantly affect agricultural investment in both the short and long-run. Akpaeti, Bassey and Ibok (2014) explored the impact of financial sector reforms on the performance of Nigerian agricultural sector. They found that there existed a short-run and long-run relationship between financial sector reforms variables and major agricultural commodities in Nigeria. The study also revealed a significant difference between agricultural exports commodities such as cocoa and palm oil prior and during financial reforms. Furthermore, the study showed that exports performance during the era of financial reforms 683
3 was better compared to the pre-financial reforms era. Ammani (2012) investigated the relationship between agricultural production and credit supply in Nigeria using a simple regression model ad found that formal credit supply was positive and significant in influencing productivity in the agricultural sector. Kolawole (2013) investigated the relationship between agricultural value added, interest rate, exchange rate, credit to the agricultural sector and inflation in Nigeria using error correction model. The outcome of the study revealed that causality cannot be established. This result implies that there was a weak and insignificant causation between agricultural value added, credit supply to the Agric sector and inflation in Nigeria. These literature signal the fact that the impact of the banking sector reforms on Nigerian agricultural output, particularly through the agricultural credit is still controversial. Previous studies did not unravel the extent (if at all) of the impact made by agricultural credit on the agricultural output. This study is thus, poised to fill the gap by assessing the combined impact of the increased credit supply to the agriculture sector as a result of the banking sector reforms. METHODOLOGY Sources of Data The data employed in this study was secondary data, which was obtained from Central Bank of Nigeria (CBN) Statistical Bulletin and World Bank. The data used is between the periods of Following previous studies on financial reforms (Balogun, 2007; Udah and Obafemi, 2011), this study thus, captures banking reforms using the percentage ratio of broad money (M2) to the gross domestic product (GDP) [M2/GDP][%] and credit to private sector (CPS). It also proxy credit supply with sectoral credit to Agriculture (SCA); while the agricultural sector was represented by the annual growth rate of agricultural output (AAGR). Model Specification In bid to examining the impact of banking reforms and credit supply on the agricultural sector, the model of this study is expressed as follows: ( ( ( ( The econometric model is thus transformed and expressed as follows: ( ( ( Where: AAGR = Annual Growth Rate of Agricultural Growth M2GDP = Percentage Ratio of Broad Money to Gross Domestic Product CPS = Private Sector Credit SCA = Loans and Advances to the Agricultural Sector The a priori expectation is > 0 ANALYTICAL TECHNIQUES Unit root test This test was employed to determine the presence of unit root, that is, to ascertain if the variables are stationary. This test was conducted under two specifications of the Augmented Dickey Fuller (ADF) test (i) intercept (ii) trend and intercept. Cointegration Test This test was conducted to determine the presence of a long-run relationship. In achieving this, the Trace and Maximum Eigenvalue statistics of the Maximum Likelihood method (ML) developed by Johansen (1988; 1991) were employed. The null hypothesis for the trace test denotes the presence of at most r cointegrating vectors. For the Max Eigenvalue test, the null of r = 0 was tested against the alternative that r = 1; r = 1 was tested against the alternative that r =2 and so on (Akpaeti, Bassey, and Okon, 2014). The Schwarz Information Criterion (SIC), sequential modified LR test statistic (LR), Final Prediction Error (FPE), and the Hannan-Quinn Information Criteria (HQ) were used to select the optimal lag length for the cointegration test. 684
4 Vector Autoregression Model (VAR) Proceedings of the Asia Pacific Conference on Business and Social Sciences 2015, Kuala Lumpur This study employs VAR (VECM) to examine the short-run properties of the model. However, this study did not express interest in the coefficients of VAR because they do not convey much economic meaning in the context of this study. Hence, the study focuses more on the use of the impulse response and the variance decomposition of the VAR (VECM). The impulse response function explains the response of an endogenous variable to one of the innovations. It traces the effects on present and future values of the endogenous variable of one standard deviation shock to one of the innovations. The variance decomposition, on the other hand, separates the variation in an endogenous variable into component shocks to the VAR. Hence, variance decomposition gives information on the relative importance of each random innovation in affecting the variables in the VAR. It is pertinent to mention that if cointegration is detected between series, there exists a long-term equilibrium relationship hence; it becomes appropriate to use VECM (VAR error correction model) in place of VAR. In the absence of cointegration, VAR becomes more relevant. The VAR model specification in the context of the variables of study is express as follows: ( ( ( ( Where: are the stochastic error term called impulses or innovations or shocks in VAR. RESULTS AND DISCUSSION The Effects of Banking Sector Reforms and Credit Supply on Agricultural output Table 1 depicts the outcome of the unit root test. Augmented Dicker Fuller (ADF) unit root test was employed in carrying out the unit root test. The results revealed that all the variables possessed unit-roots at one percent level of significance and become stationary at first differences. Since all the variables became stationary after first differences, it is, therefore, pertinent to test whether the non-stationary variables were co-integrated. Thus, the study applied the Johansen Cointegration Trace test and Johansen Cointegration Maximum Eigenvalue test to ascertain whether a long-run relationship exists between the variables. TABLE 1. RESULT OF ADF UNIT ROOT TEST Variables Level First Difference Decision Rule Intercept Trend + Intercept Trend + Intercept Intercept AAGR *** *** I(1) M2GDP *** *** I(1) Log(CPS) *** *** I(1) Log(SCA) *** *** I(1) 1% Critical Values 5% % Source: Author s computation using EViews 7 *** indicates significance at 1% Table 2 shows the optimum lag structure for the VAR upon which the cointegration analysis is carried out. The result suggests that information criteria, such as sequential modified LR test statistic (LR), Final 685
5 Prediction Error (FPE), Schwarz Information Criteria (SC) and the Hannan-Quinn Information Criteria (HQ), signal the optimum lag length to be 1 at 5 percent level of significance. Hence, the cointegration test was carried out using Johansen cointegration test with lag 1. TABLE 2. DETERMINATION OF OPTIMUM LAG CRITERIA Lag Log L LR FPE AIC SC HQ NA * 0.199* * 9.997* * Source: Authors Computation using EViews 7. *indicates lag order selected by the criterion at 5 percent level of significance. Tables 3 and 4 show the outcomes of the cointegrating test employing both the Trace and the Maximum Eigenvalue tests. The results indicated the presence of one (1) cointegrating vector in each of the tests. Hence, there is evidence of the existence of a long-run relationship among banking sector reforms, credit supply, agricultural outputs and other policy variables in Nigeria. Consequently, it is more appropriate to apply the vector error correction model (VECM) to track the long-run relationship between the variables. TABLE 3. JOHANSEN COINTEGRATION TRACE TEST Null Hypothesis Alternative Test Statistics Critical Value 0.05 P-Value Hypothesis r = 0 r = < ** r = 1 r = < r = 2 r = < r = 3 r = < Source: Authors computation and Eview7 output. r implies the number of co-integrating vector. ** indicates significant at 5% level. TABLE 4. JOHANSEN COINTEGRATION MAXIMUM EIGENVALUE TEST Null Hypothesis Alternative Test Statistics Critical Value 0.05 P-Value Hypothesis r = 0 r = ** r = 1 r = r = 2 r = r = 3 r = Source: Authors computation and Eview7 output. r implies the number of co-integrating vector. ** indicates significant at 5% level. Figure 1 depicts the graph of AR inverse root of the VEC. The result shows that all the polynomial roots fall within the unit circle except for one, touching the circle at the positive side of the x-axis. This outcome implies that the VEC model is stable or stationary and, as a result, the impulse response functions are reliable and can be used for policy formulation. 686
6 1.5 FIGURE 1. GRAPH OF AR INVERSE ROOT Inverse Roots of AR Characteristic Polynomial Source: Authors computation and Eview7 output Figure 2 depicts impulse response that explains the reaction of an endogenous variable to one of the innovations. It helps to trace the effects of a shock to one endogenous variable on to the other variables. It can be seen that from the impulse response graph in panel (a) that banking sector reforms, captured by M2GDP positively affected the agricultural output proxy by AAGR. This result tends to lend credence to previously related studies (Onoja et al., 2011; Akpaeti et al., 2014). The credit to private sector (LOG(CPS)) in panel (a) indicates that it did not have a positive effect on the agricultural sector at the initial stage of the reforms. The possible explanation for this is that the bulk of the private sector credit growth in the wake of the reforms in Nigeria was short term, which is not useful for growth- producing capital investments. Furthermore, the smallholder farmers tend to have low productivity as they lack the scale and knowledge to make and manage productive investments. However, the impulse response further shows that LOG(CPS) was able to find its path to equilibrium after the third year of the reforms and subsequently display positive effects on the agricultural sector. The sectoral credit to agriculture [LOG(SCA)] in panel (a) at the initial stage of the reforms positively impacted the agricultural sector. However, it began to have an adverse effect on the agricultural output in the third period (the same period when credit to private sector started to produce a positive effect on agricultural output). However, it finds it a path to equilibrium again and subsequently produces a positive effect on the agricultural output. Panel (d) shows the impulse response of sectoral credit to agriculture [LOG(SCA)] to shock in other endogenous variables. The outcome implies that the banking reforms, captured by both M2GDP and LOG(CPS), have a positive effect on the sectoral credit to agriculture that in turn produces a positive effect on agricultural outputs. A possible explanation for this is that a good proportion of the credit to the private sector flow to the agricultural sector. 687
7 FIGURE 2. IMPULSE RESPONSE FUNCTIONS Response of AAGR to Cholesky One S.D. Innovations Response of M2GDP to Cholesky One S.D. Innovations (a) 3 (b) AAGR LOG(CPS) M2GDP LOG(SCA) AAGR LOG(CPS) M2GDP LOG(SCA) Response of LOG(CPS) to Cholesky One S.D. Innovations Response of LOG(SCA) to Cholesky One S.D. Innovations (c).3.2 (d) AAGR M2GDP AAGR LOG(CPS) LOG(SCA) LOG(CPS) Source: Authors computation and Eview7 output M2GDP LOG(SCA) Figure 3 depicts the trend(s) of the various endogenous variables. Panel (a), which represents the rate of agricultural output; tend to decline rapidly at the initial stage of the reforms as the credit to private sector (Panel c) and sectoral credit to agricultural sector (Panel d) rises. However, it began to rise dramatically and responds positively to private sector credit and credit to the agricultural sector as shown in panel c and panel d respectively. Panel b, which depicts banking reforms, indicates that there was a rapid increase in liquidity in 2005 as a result of the reforms. 688
8 FIGURE 3. TRENDS OF ENDOGENOUS VARIABLES (a) (b) AAGR M2GDP 10 8 (c) (d) LOG(CPS) Source: Authors computation and Eview7 output LOG(SCA) : Table 5 shows variance decomposition outcome. The variance decomposition provides information about the relative importance of each random innovation in affecting the variables in the VAR. It shows the magnitude of information each variable contributes to the other variables in the autoregression. Furthermore, it determines how much of the forecast error variance of each of the variables can be explained by exogenous shocks to the other variables. This study employed a twenty-five (25) forecasting time horizon and observed the relevance of the variables over time. It is pertinent to mention that only the variance decomposition of AAGR is shown. The result in Table 5 provides the portion of the forecast error variance of each variable that is attributed to its innovation and innovations in another variable. The own shocks of AAGR constitute a significant source of variation in its forecast error in the time horizon, ranging from 100% to 80.93%. Twentyfive (25) years later, variation in AAGR is accounted for by M2GDP (16.82%), LOG(CPS) (1.63%), and LOG(SCA) (0.59%) shock. This result implies that the predominant source of variation in AAGR is M2GDP while LOG(SCA) accounts for the least variation. This outcome also indicates that the banking sector reforms have had a significant impact on the Nigerian agricultural outputs. However, the supply of credit to the agriculture [LOG(SCA)], though had a positive effect, but do not have a significant impact on agricultural outputs. A possible explanation for this is that the quantum of credit flow to the agricultural sector is too small to make an appreciable impact. In addition, the low impact of credit supply may be as a result of the diversion of cheap agricultural credit into more profitable business ventures. 689
9 TABLE 5. VARIANCE DECOMPOSITION OF AAGR Period S.E. AAGR M2GDP LOG(CPS) LOG(SCA) Source: Authors Computation using EViews 7 CONCLUSION AND RECOMMENDATIONS The study examined the impact of the banking reforms and credit supply on the agricultural sector in Nigeria. The scope of the study covers the era of the Structural Adjustment Programme (SAP) and extends through to the financial sector reform years of 2013 when the Central Bank of Nigeria in collaboration with the Federal Ministry of Agriculture and Rural Development (FMARD) launched the 200 billion Naira Agricultural Credit Guarantee scheme (ACGS). Since the lunching of the Agricultural Credit Scheme, the Central Bank of Nigeria through the commercial banks in the country have disbursed funds to small and medium scale farmers but not much has been achieved by way of productivity in the agricultural sector. Using time series data sourced from World Bank and the Central bank of Nigerian Statistical Bulletin, and adopting the VECM methodology, it was found that the banking sector reforms and credit supply to agriculture have positively affected the growth rate of agricultural output in Nigeria. However, the impact of agricultural credit supply, as shown by the variance decomposition, is very low and insignificant. The results of the study suggest that on account of the weak linkage between the rate of agricultural output and aggregate credit supply to the sector, care should be taken in formulating the financial strategy for the transformation agenda of the agricultural sector. This is so, to enhance optimal productivity gains in the agricultural sector. The discretionary allocation of credit, particularly by the monetary authorities or the banking sector, may not necessarily achieve the goal of massive growth in the agricultural sector. Urgent solution is needed to address the lingering problem of infrastructure, institutions and various supply bottlenecks to guarantee smooth transforming of the agricultural sector in Nigeria through effective credit financing. 690
10 APPENDIX Proceedings of the Asia Pacific Conference on Business and Social Sciences 2015, Kuala Lumpur TABLE 1. DATA SOURCE obs AAGR M2GDP LOG(CPS) LOG(SCA) Source: CBN Statistical Bulletin, 2014 and World Bank REFERENCES Abdullah, IB 2007, Banking Sector Reforms and Bank Consolidation in Nigeria: Challenges and Prospects, Business Journal of Management and Social Sciences, Vol. 6, No 1, pp Akpaeti, AJ 2013, Does Financial Sector Reforms Affect Agricultural Investments in Nigeria? A Cointegration and VAR Approach, International Journal of Food and Agricultural Economics, Vol. 1, No. 2, pp Akpaeti, AJ, Bassey, NE, & Ibok, OW, 2014, The Impact of Financial Sector Reforms on the Nigerian Agricultural Export Performance, American Journal of Experimental Agriculture, Vol. 4, No. 9, pp Akpaeti, AJ, Bassey, NE, & Okon, UE, 2014, Trend evaluation of agricultural export crops in Nigeria, International Journal of Food and Agricultural Economics (IJFAEC), Vol. 2, No. 1, pp Ammani, AA 2012, An investigation into the relationship between agricultural production and formal credit supply in Nigeria, International Journal of Agriculture and Forestry, Vol. 2, No. 1, pp Ang, JB & Mckibbin, WJ 2007, Financial Liberalization, Financial Sector Development and Growth: Evidence from Malaysia, Journal of Development Economics, Vol. 84, No. 1, pp Anyanwu, CM 2010, An Overview of Current Banking Sector Reforms and the Real Sector of the Nigerian Economy, CBN Economic and Financial Review, Balogun, E.D 2007, Banking sector reforms and the Nigerian economy: performance, pitfalls and future policy options Johansen, S 1988, Statistical analysis of cointegration vector, Journal of Economic dynamics and Control, Vol. 12, pp
11 Johansen, S 1991, Estimation and hypothesis of cointegration vectors in Gaussian vector autoregressive model models, Econometrica, Vol. 59, pp Kalu, CU & Mgbemena, OO 2015, Banking Sector Reforms in Nigeria s Fourth Republic: A Review of Evidence, Journal of Economics and Sustainable Development, Vol. 6, No. 6, pp Kolawole, BO 2013, Institutional reforms, interest rate policy and the financing of the agricultural sector in Nigeria, European Scientific Journal, Vol. 9. No.12, pp Mang, H.G 2009, Politics and economics of FADAMA irrigation and product sales in the mining areas of the Jos Plateau in Nigeria, Draft Paper for WOW Working Group on the Politics of Land, Authority and National Resources. Okezie, CA & Amir, BH 2011, Economic crossroads: The experience of Nigeria and lessons from Malaysia, Journal of Development and Agricultural Economics, Vol. 3, No. 8, pp Omoruyi, SE 1991, The Financial Sector in Africa: Overview and Reforms in Economic Adjustment Programmes, CBN Economic and Financial Review, Vol. 29, No.2, pp Onoja, AO, Onu, ME & Ajodo-Ohiemi, S 2011, Contributions of Financial Sector Reforms and Credit Supply to Nigerian Agricultural Sector ( ), Journal of Applied Statistics, Vol. 2, No. 2, pp Rousseau, PL & Vuthipadadom, D 2005, Finance, Investments and Growth: Time-series evidence from 10 Asian economies, Journal of Macroeconomics, Vol. 27, No. 1, pp Udah, EB & Obafemi, FN 2011, The Impact of Financial Reforms on Agricultural and Manufacturing Sectors in Nigeria: An Empirical Investigation, Journal of Sustainable Development in Africa, Vol. 13, No. 8, pp Ugwu, DS & Kanu, IO 2012, Effects of agricultural reforms on the agricultural sector in Nigeria, Journal of African Studies and Development, Vol. 4, No. 2, pp Usman, NE 2006, Agriculture: Vital to Nigerian economic development. Paper Presented at the Forum of Economic Stakeholders on Growing the Nigerian Economy, Thisday Newspaper, 25 July Internet/Website Source: Data on annual growth rate of agricultural output from WorldBank For more detail please see: lue%20wbapi_data_value-first&sort=asc 692
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