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2024 Vol.36, Issue 2 Preview Page

Research Article

Impact of Agricultural Credit on the Productivity and Income of Small-Scale Maize Farmers in Kaduna State, Nigeria
Abdullahi Gambo1
,
Youngjune Kim2*
1Agric Officer, Underwriting Department, Nigerian Agricultural Insurance Corporation, Abuja, 900211, Nigeria
2Assistant Professor, Department of Agricultural and Resource Economics, Kangwon National University, Chuncheon, 24341, Korea
*Corresponding Author
30 June 2024. pp. 77-86
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Abstract

In this study, we investigated the impact of agricultural credit on the productivity and income of smallholder maize farmers in Kaduna State, Nigeria. The objectives of the study are to ascertain the impact of agricultural credit on the income and productivity of small-scale maize farmers and examine the factors that affect their ability to access agricultural credit. A structured questionnaire was used to collect the primary data from 108 beneficiaries and 137 non-beneficiaries of agricultural credit among smallholder maize farmers using a structured questionnaire. Propensity score matching and a logit regression model were used to analyze the data. The most comprehensive score specification was used to generate the average treatment effect on the treated (ATT) estimates for collecting outcome variables. The ATT estimates with an alternative score specification were used as a reliable measure wherein each line corresponds to a separate estimation. Three different matching methods, i.e., nearest neighbor matching, stratification matching, and radius matching, were used to evaluate the robustness of estimation. The results revealed that smallholder maize farmers who were the beneficiaries of agricultural credit exhibited significantly higher mean productivity and income at the 1 and 5% probability levels, respectively than those exhibited by the non-beneficiaries, suggesting that credit positively impacted farmers’ revenue and productivity. We also observed that the farmers’ gender and marital status were not particularly important in determining their access to agricultural credit. Whether single or married, male or female, their prospects of obtaining credit were similar. Age, educational attainment, farming experience, farm size, and cooperative membership were significant factors that affected their ability to access agricultural credit at the 5% probability level, except for the farmers’ income status, which was significant at the 10% probability level. The two most important factors influencing access to agricultural credit were the distance from the source of credit and extension contact, which were significant at a 1% probability level.

Keywords
Logit regression
Nearest neighbor matching
Propensity score matching
Radius matching
Stratification matching
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Information
  • Publisher :Agriculture and Life Sciences Research Institute, Kangwon National University
  • Publisher(Ko) :강원대학교 농업생명과학대학 농업생명과학연구원
  • Journal Title :Journal of Agricultural, Life and Environmental Sciences
  • Journal Title(Ko) :농업생명환경연구
  • Volume : 36
  • No :2
  • Pages :77-86
  • Received Date : 2024-02-14
  • Revised Date : 2024-04-23
  • Accepted Date : 2024-05-07
  • DOI :https://doi.org/10.22698/jales.20240007
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