Abstract
Employing cross-sectional data from 360 rice farmers selected from three states in South West Nigeria, the study analyzes the impact of credit demand on the productivity of rice farmers. An Endogenous Switching Regression Model (ESRM) that accounts for both heterogeneity and sample selection biases were used to estimate the impact of credit demand on rice productivity in South West Nigeria. In addition, a Tobit regression model was employed to measure the level of participation of rice farmers in the credit market. The result of the first stage (probit model) of the ESRM revealed that household assets, access to service, climate variables, regional variables, and transaction cost are statistically significant in influencing farmers’ credit demand decision. The results of the second stage of the ESRM indicate factors such as household assets and access to service were statistically significant in explaining variations in rice productivity among participants and non-participants in the credit market. Furthermore, the results of the Tobit model showed that the farmers’ location income from rice farming experience, interest rate, and distance to the source of credit are statistically significant determinants of the amount of credit received. These findings suggest that facilitating farmers’ access to credit will improve rice productivity. Therefore, it is imperative for government and development partner to work together in order to improve the conditions for suitable agricultural credit access to rice farmers, especially a review of interest rates. A necessary addition should be developed to the assistance already being provided under Nigeria Incentive-Based Risk Sharing System for Agricultural Lending (NIRSAL) in the form of loan guarantees and other risk-sharing incentives, such as a regulatory environment that supports the modern contractual obligations that are characteristic of well-functioning agricultural financing. This would not only contribute to the intensification of rice production in Nigeria to meet its increasing rice demand, but also improve rice farmers’ productivity and their households’ incomes.
Highlights
Background of the StudyMany policy incentives have been put in place for Nigeria’s financial system
Analyzing the impact of credit demand on rice productivity includes an examination of participation in the credit market and the factors that influence the decision of rice farmers to borrow from the credit sources
An improved version of an endogenous switching regression model that accounts for both heterogeneity and sample selection biases was used to investigate the impact of credit demand on rice productivity in Southwestern Nigeria
Summary
Many policy incentives have been put in place for Nigeria’s financial system This is in a bid to ensure that farmers have access to credit to finance their agricultural activities. Credit plays an important role in increasing agricultural productivity at both the pre-planting and harvesting stages (Akpokodje, Lançon, & Erensten, 2001); timely access and availability of credit as posited by Saboor, Hussein, & Munir (2009) are critical to farmers’ acquisition of the inputs and machinery required to carry out farm activities. The empirical technique advances the existing literature on the impact of credit demand on rice productivity by using a switching regression that segregates smallholder farmers in line with their participation in the credit market while simultaneously controlling for biases resulting from sample selectivity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
