全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Impact of Formal Financial Market Participation on Farm Size and Expenditure on Variable Farm Inputs: The Case of Maize Farmers in Ghana

DOI: 10.1155/2014/329674

Full-Text   Cite this paper   Add to My Lib

Abstract:

The study examined maize farmers’ participation in the formal financial market and its impact on farm size and expenditure on variable farm inputs. A multistage sampling method was used in selecting 595 maize farmers from the seven districts in Ashanti and Brong Ahafo Regions of Ghana. A structured questionnaire and interview schedule were used to elicit information from the respondents. The impact of formal financial market participation on farm size and expenditure on variable inputs was estimated using Propensity Score Matching (PSM) method. The results of the study showed that formal financial market participation has the potential to significantly increase expenditure on variable inputs by farmers and consequently use of improved technology. Therefore, formal financial market participation should be encouraged through education and promotional activities. 1. Introduction The formal financial sector has been identified as important in improving productivity by making financial services available to producers in the agricultural sector. This is because informal financial services are often considered to be unsatisfactory because of extraordinarily high interest rates on credit, and savings are not sufficiently secure [1]. It is therefore assumed that participation in the formal financial market would lead to larger farm sizes and adoption of improved technology through increased expenditure on variable inputs. In view of this, several policies have been adopted by successive governments of Ghana to improve access to financial services. These policies include liberalisation of the financial sector to increase private sector participation in the provision of financial services. The sector has now expanded from the prereform period of two foreign banks and two state owned banks with virtually no nonbank financial institutions, to include many private financial institutions. The question then is: has the expansion in the formal financial sector increased participation of farmers in the market, and if so what impact does a farmer’s participation in formal financial market have on their input usage and farm size? This paper empirically examines the impact of formal financial market participation on farm size and expenditure on farm inputs by maize farmers in two regions of Ghana (Ashanti and Brong Ahafo). The literature on impact evaluation methods is extensive. Some authors [2–4] present very useful overviews. Khandker et al. [5] have also discussed in detail different methods that are applicable for impact evaluation and the data needed for each type. In

References

[1]  S. R. Khandker and R. R. Faruqee, “The impact of farm credit in Pakistan,” Agricultural Economics, vol. 28, no. 3, pp. 197–213, 2003.
[2]  E. Duflo, R. Glennerster, and M. Kremer, “Using randomization in development economics research,” Handbook of Development Economics, vol. 4, pp. 25–39, 2008.
[3]  M. Ravallion, “Bailing out the world’s poorest,” Challenge, vol. 52, no. 2, pp. 55–80, 2008.
[4]  R. Blundell and M. C. Dias, “Evaluation methods for non-experimental data,” Fiscal Studies, vol. 21, no. 4, pp. 427–468, 2000.
[5]  S. R. Khandker, G. B. Koolwal, and H. A. Samad, Handbook on Impact Evaluation: Quantitative Methods and Practices, The world Bank, Washington, DC, USA, 2010.
[6]  V. Owusu and A. Abdulai, “Non-farm Work and Food Security Among Farm Households in Northern Ghana,” non-farm_northern-ghana, 2009, http://www.pegnet.ifw-kiel.de/activities/research/.
[7]  J. Becerril and A. Abdulai, “The impact of improved maize varieties on poverty in Mexico: a propensity score-matching approach,” World Development, vol. 38, no. 7, pp. 1024–1035, 2010.
[8]  J. M. Mutua and L. N. Oyugi, “Access to financial services and poverty reduction in rural Kenya,” NEPRU Working Paper 108, 2006.
[9]  G. Owuor, “Is micro-finance achieving its goal among smallholder farmers in Africa? Empirical evidence from Kenya using propensity score matching,” in Proceedings of the 25th International Conference of Agricultural Economists, Beijing, China, August 2009.
[10]  Ministry of Food and Agriculture, Agriculture in Ghana Facts and Figures, MoFA Ghana, 2009.
[11]  P. R. Rosenbaum and D. B. Rubin, “The central role of the propensity score in observational studies for causal effects,” Biometrika, vol. 70, no. 1, pp. 41–55, 1983.
[12]  R. H. Dehejia and S. Wahba, “Causal effects in nonexperimental studies: reevaluating the evaluation of training programs,” Journal of the American Statistical Association, vol. 94, no. 448, pp. 1053–1062, 1999.
[13]  S. O. Becker and A. Ichino, “Estimation of average participation effects based on propensity scores,” The Stata Journal, vol. 2, no. 4, pp. 358–377, 2002.
[14]  M. Caliendo and S. Kopeinig, “Some practical guidance for the implementation of propensity score matching,” Journal of Economic Surveys, vol. 22, no. 1, pp. 31–72, 2008.
[15]  J. A. Smith and P. E. Todd, “Does matching overcome LaLonde's critique of nonexperimental estimators?” Journal of Econometrics, vol. 125, no. 1-2, pp. 305–353, 2005.
[16]  J. Heckman, R. LaLonde, and J. Smith, “The economics and econometrics of active labor market programs,” in Handbook of Labor Economics, O. Ashenfelter and D. Card, Eds., vol. 3, pp. 1865–2097, Elsevier, Amsterdam, The Netherlands, 1999.
[17]  B. Sianesi, “An evaluation of the active labour market programmes in Sweden,” The Review of Economics and Statistics, vol. 86, no. 1, pp. 133–155, 2004.
[18]  P. R. Rosenbaum, Observational Studies, Springer, New York, NY, USA, 2002.
[19]  T. A. DiPrete and M. Gang, “Assessing bias in the estimation of causal effects: rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments,” Sociological Methodology, vol. 34, pp. 271–310, 2004.
[20]  World Bank, Finance for All? Policies and Pitfalls in Expanding Access, World Bank, Washington, DC, USA, 2005.
[21]  T. Jappelli, “Who is credit constrained in the U.S. economy,” Quarterly Journal of Economics, vol. 105, pp. 219–234, 1990.
[22]  S. Steiner, Determinants of the Use of Financial Services in Rural Ghana: Implications For Social Protection, Brooks World Poverty Institute, University of Manchester, 2008.
[23]  C. K. Chen and M. Chivakul, “What drives household borrowing and credit constraints? Evidence from bosnia Herzegovnia,” IMF Working Paper 08(202), 2008.
[24]  M. A. Y. Rahji and S. B. Fakayode, “A multinomial logit analysis of agricultural credit rationing by commercial banks in Nigeria,” International Research Journal of Finance and Economics, vol. 1, no. 24, pp. 90–100, 2009.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133