Article Title: Determinants of Choice of Finance by Coffee Farmers in Machakos County, Kenya
Volume Number: 1
Issue: 1
Year: 2015
Article Type: Original Article
Author Names: P. Songa¹, John Cheluget¹, S. Sandhya², J. Satpathy³*
Page Number: 68-79
PDF: [Download]
DOI: https://doi.org/10.64368/ejmi.vol.1.issue1.5
Affiliations:
¹The Management University of Africa, Kenya
²NITTE – School of Management, Bengaluru, India
³Neuro Integral Scientific Institute, Colombia
* Correspondence: Dr. J Satpathy, Department of Neuromanagement, Neuro Integral Scientific Institute, Colombia, Email Address: jyotisatpathy@gmail.com
Keywords: Coffee Board of Kenya; Coffee Marketing Board; Collateral, Interest Rate
Abstract: Coffee farming in Kenya has faced numerous challenges over time, ranging from land ownership to access to information, cultural beliefs, and collateral challenges to the acquisition of bank credit. This study aims to establish the determinants of the choice of finance by coffee farmers in Machakos County, Kenya. The study adopted a descriptive approach that utilized both quantitative and qualitative research methodologies. The study used questionnaires to collect data from a sample of ninety-six (96) respondents. Multiple regression analysis was undertaken to test the relationship between the independent variables (collateral, interest rates, bureaucracy, and accessibility to financial institutions) and the dependent variable (choice of finance). The findings indicate that R is 0.726, R² is 0.527, and adjusted R² is 0.5905. ANOVA of the data showed that F calculated is greater than F critical (26.361>2.49), indicating that the overall model was reliable in predicting the relationship between the independent variable (collateral, interest rates, bureaucracy, and accessibility to financial institutions) and the dependent variable (choice of finance). The study concludes that there was a statistically significant association between collateral, interest rates, bureaucracy, and accessibility to financial institutions and selection of funding, as the p-values 0.039, 0.001, 0.015, 0.011, and 0.018 are less than 0.05 at 5% level of significance. The study recommends that government and financial institutions, as well as other lending institutions, should consider coming up with policies and procedures geared towards catering to the specific credit needs of farmers.
References:
1. Angula MN. Determinants of sustainable coffee marketing channel choice and supply response among organic and UTZ certified smallholder farmers: evidence from Uganda. Doctoral dissertation, Michigan State University. 2010.
2. Giovannucci D, Potts J, Killian B, Wunderlich C, Soto G, Schuller S, Vagneron I. Seeking sustainability: COSA preliminary analysis of sustainability initiatives in the coffee sector. Committee on Sustainability Assessment. 2008.
3. Njabani AW. The role of women self help groups in socio–economic development of Chuka/Igamba Ng’ombe Constituency, Tharaka–Nithi County. Journal of Social Sciences. 2015; pages 50–72.
4. Zeller M, Sharma M, Henry C, Lapenu C. An operational method for assessing the poverty outreach performance of development policies and projects: results of case studies in Africa, Asia, and Latin America. World Development. 2006;34(3):446–464.
5. Anteneh A, Muradian R, Ruben R. Factors affecting coffee farmers market outlet choice: the case of Sidama Zone, Ethiopia. 2011.
6. Gemech F, Struthers J. Coffee price volatility in Ethiopia: effects of market reform programmes. Journal of International Development. 2007;19(8):1131–1142.
7. CBK. Coffee Board of Kenya — History of Coffee. Retrieved February 08, 2016, from http://www.coffeeboardkenya.co.ke/index.php/kenyan-coffee/history-of-coffee
8. Gathura MN. Factors affecting small-scale coffee production in Githunguri District, Kenya. International Journal of Academic Research in Business and Social Sciences. 2013;3(9):132–149.
9. Njoroge S, Mbogo S. Pilot short and medium term finance to small-scale coffee farmers in Kenya. International Journal of Academic Research in Business and Social Sciences. 2010;1(20):11–15.
10. Berliant TM. A foundation of location theory: consumer preferences and demand. Journal of Economic Theory. 2008;44(2):336–343.
11. Mankiw NG. Principles of Economics. 4th ed. South Western: Thomson; 2007.
12. Cullis J, Jones P. Public Finance and Public Choice. 3rd ed. New York: Oxford University Press; 2009.
13. Barberis N, Thaler R. A survey of behavioral finance. In: Handbook of the Economics of Finance. 2003;1:1053–1128.
14. Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979.
15. Tversky A, Kahneman D. Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty. 1992;5(4):297–323.
16. Sheffrin SM. Economics: Principles in Action. Upper Saddle River, NJ: Pearson Prentice Hall; 2003.
17. Onysko S, Sholudko O, Sodoma R. Credit risk monitoring of creditor banks of agro-industrial complex. Accounting and Finance. 2015;(3):108–115.
18. Berger AN, Udell GF. A more complete conceptual framework for SME finance. Journal of Banking and Finance. 2006;30(11):2945–2966.
19. Swinnen JF (Ed.). Global supply chains, standards and the poor: how the globalization of food systems and standards affects rural development and poverty. CABI. 2007. Thaler R. Mental accounting and consumer choice. Journal of Marketing Science. 1985;4(3):50–62.
20. Hayes CM. What every farmer should know about secured transactions. Pennsylvania: Pennsylvania State University; 2004.
21. Nyanamba SO, Nyangweso GN, Omari SM. Factors that determine the capital structure among micro-enterprises: a case study of micro-enterprises in Kisii Town, Kenya. American International Journal of Contemporary Research. 2013;3(7):139–147.
22. Adofu I, Abula M, Audu S. An assessment of the effects of interest rate deregulation in enhancing agricultural productivity in Nigeria. Current Research Journal of Economic Theory. 2010;2(2):82–86.
23. Bernard B, Sare YA, Musah A. The effects of interest rate on micro, small and medium enterprises financing decision in Wa Municipality of Ghana. International Journal of Business, Humanities and Technology. 2014;4(4):81–90.
24. Wachira MI, Kihiu EN. Impact of financial literacy on access to financial services in Kenya. International Journal of Business and Social Science. 2012;3(9):42–50.
25. Njongoro JN. The effect of mortgage interest rate on the growth of mortgage financing in Kenya. Nairobi: University of Nairobi Library; 2013.
26. Weyant J. Integrated assessment of climate changes: state of the literature. Journal of Benefit-Cost Analysis. 2014;5(3):377–409.
27. Guirkinger C. Understanding the coexistence of formal and informal credit markets in Piura, Peru. World Development. 2008;36(8):1436–1452.
28. Wang J, Huang J, Rozelle S. Evolution of tubewell ownership and production in the North China Plain. Australian Journal of Agricultural and Resource Economics. 2005;49(2):177–195.
29. Cheruiyot NC. Financing coffee: a Kenyan experience. Nairobi: Agriculture, Fisheries and Food Authority (AFFA); 2015.
30. Wangari RW. Factor that contribute to the declining trend of coffee production in Kenya: the case in Nyeri County. Unpublished thesis, University of Nairobi. 2014.
31. Girante MJ. Three essays on the production effects of decoupled payments: do decoupled payments matter for acres and yields? Raleigh, North Carolina: UMI Microform; 2008.