Filling the Niche—A Synthesis of Financial Inclusion among Smallholder Farmers in Africa, the Case for Kenya
- 1 African Center of Excellence in Sustainable Agriculture and Agribusiness, Egerton University, Nakuru, Kenya
Abstract
This paper makes a synthesis of empirical studies carried out in parts of Africa, and in Kenya to derive lessons on financial inclusion among smallholder farmers in rural and peri-urban areas . The derived lessons point at a steadily growing expansion of financial services to rural /peri-urban poor traditionally characterised by high idiosyncratic risks and huge information asymmetry. This category of households seems to have made the African continent sustain itself in the midst of financial crisis in 2008/09 when the rest of the world including the Asian tigers and the American capitalists faced serious setbacks in their financial sector growth. During this period, Africa experienced steady growth that started in 2000 at below 3% and peaked at about 4.8% by 2009-20 15 . The contribution of the transformation of the financial sector experienced in Kenya is one of the reasons for this growth. The paper elucidates the key determinants of access to the reformed financial services by the rural poor , access to targeted training on financial services beyond the formal education, participation of female-headed households in collective frameworks and creditworthiness as exhibited by multiple borrowing points. The impact of such inclusion is exhibited by significant changes in purchasing power of households through income and diversified investment in farm assets. In all these successes, ICT through mobile money transfer played a significant role, as exhibited in studies across the region. Despite the successes, the key challenges include high fungibility of targeted funding, showing a need to provide an array of financial services to the poor including credit for consumption, school fees, medical cover and emergency loans found among the savings and credit cooperatives. Also, the inequality and raising the poorest of the poor is still a challenge, one reason being the instrumental role of ICT through mobile money transfer system which some of the poorest farmers have no access to. M obile banking services such as M-Shwari product is something that extension personnel could take as part of their advice to small farmers in accessing short-term loans and as means of savings funds between USD 1 - 100. These kinds of funds are useful in particular in bridging financial gaps along the agribusiness value chains. The funds can be borrowed to transport produce to the market, and make payments in time to enable farmers to capitalise on their input purchases. On participation of smallholder farmers in mobile banking type , and in particular saving and immediate credit service is still limited . Th is is an area for immediate uptake by all stakeholders including policymakers and the financial sector .
- AfDB (2019). Africa’s 2019 Economic Outlook. Africa.com. https://www.africa.com/afdb-report-africas-2019-economic-outlook
- Ali, A., & Abdulai, A. (2010). The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan. Journal of Agricultural Economics, 61, 175-192. https://doi.org/10.1111/j.1477-9552.2009.00227.x
- Becker, S. O., & Ichino, A. (2002). Estimation of Average Participation Effects Based on Propensity Scores. The Stata Journal, 2, 358-377. https://doi.org/10.1177/1536867X0200200403
- Caliendo, M., & Kopeinig, S. (2005). Some Practical Guidance for the Implementation of Propensity Score Matching. Discussion Paper No. 1588, DIW Berlin Department of Public Economics. Konigin-Luise-Str. 5, 14195. Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor. https://doi.org/10.2139/ssrn.721907
- Dehejia, R. H., & Wahba, S. (1999). Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs. Journal of the American Statistical Association, 94, 1053-1062. https://doi.org/10.1080/01621459.1999.10473858
- Dehejia, R. H., & Wehba, S. (2002). Propensity Score-Matching Methods for Non-Experimental Causal Studies. The Review of Economics and Statistics, 84, 151-161. https://doi.org/10.1162/003465302317331982
- Diagne, A., Bastin, G., & Coron, J.-M. (2012). Lyapunov Exponential Stability of 1-D Linear Hyperbolic Systems of Balance Laws. Automatica, 48, 109-114. https://doi.org/10.1016/j.automatica.2011.09.030
- Gine, X., & Karlan, S. D. (2006). Group versus Individual Liability. A Field Experiment in the Philippines. Discussion Paper, World Institute for Development Economics. https://doi.org/10.1596/1813-9450-4008
- Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47, 5-86. https://doi.org/10.1257/jel.47.1.5
- Kirui, O. K., Okello, J. J., Nyikal, R. A., & Njiraini, G. W. (2013). Impact of Mobile Phone-Based Money Transfer Services in Agriculture: Evidence from Kenya. Quarterly Journal of International Agriculture, 52, 141-162.
- Ouma, A. S. (2002). Financial Sector Dualism: Determining Attributes for Small and Micro Enterprises in Urban Kenya. A Theoretical and Empirical Approach Based on Case Studies in Nairobi and Kisumu. Published PhD Thesis, University of Cologne.
- Rosenbaum, P., & Rubin, D. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70, 41-50.