Impact of Agricultural Credit Guarantee Scheme Fund on Agricultural Output in Nigeria

The study examined the impact of Agricultural Credit Guaranteed Scheme Fund (ACGSF) on agricultural productivity in Nigeria covering the period 1986Q1 to 2024Q4. The objectives of the study were to determine the impact of Agricultural Credit Grant Scheme Fund (ACGSF) granted to categorized farm production on agricultural output, assess the nature of the relationship between Agricultural Credit Grant Scheme Fund (ACGSF) and agricultural output, trace the direction of causality between Agricultural Credit Grant Scheme Fund (ACGSF) and agricultural output and ascertain the optimal ACGSF loan to crop production required to boost agricultural output in Nigeria. Data for the study were sourced from the Central Bank of Nigeria (CBN) Statistical bulletin 2024 and were interpolated using Eview Econometric package. Augmented Dickey-Fuller (ADF) unit root test and Autoregressive and Distributed Lag (ARDL) bounds test of co-integration were carried out and the Autoregressive Distributed Lag ARDL model was applied to extract the data set The findings showed that the variables were integrated of order zero and one and had a long run relationship. The result of the short run ARDL indicated that loans granted to Mixed Production in the third quarter had positive significant effect on agricultural output while those granted to crop production had negative but insignificant effect. It was shown by the finding that. oans granted to and fishery production had positive insignificant effect on agricultural output in Nigeria. The result of the ARDL Bound test showed that the variables had a long run relationship among the variables used in the model. There was an evidence of a unidirectional causality flowing from agricultural output to loan granted to Mixed Farming Productivity (MIP) by the result of the Granger Causality. The result of the Non-Linear Threshold Quadratic model showed that the maximum loan to be granted to the crop production in order to guarantee maximum agricultural productivity was N710,266.055. The study recommended the need to give priority to loans the mixed farming production than fishery or crop production; monitor and evaluate the loans granted to farmers from the first quarter to the third quarter; diversify loans given to farmers; and grant each farmer at least a sum of N710,266.055 in order to attain a maximum agricultural productivity in Nigeria.

Authors

Institutions

Publication Details

Journal
Journal of World Economic Research
Published
2025-12-29
DOI
https://doi.org/10.11648/j.jwer.20251402.17
Primary Topic
Microfinance and Financial Inclusion
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Agricultural Credit Guarantee Scheme Fund on Agricultural Output in Nigeria

Patrick Nwabueze Ubru, Fredrick C. Asogwa, Nicholas Attamah
Journal of World Economic Research
Microfinance and Financial Inclusion
article

Impact of Agricultural Credit Guarantee Scheme Fund on Agricultural Output in Nigeria

Patrick Nwabueze Ubru, Fredrick C. Asogwa, Nicholas Attamah
article en

Abstract

The study examined the impact of Agricultural Credit Guaranteed Scheme Fund (ACGSF) on agricultural productivity in Nigeria covering the period 1986Q1 to 2024Q4. The objectives of the study were to determine the impact of Agricultural Credit Grant Scheme Fund (ACGSF) granted to categorized farm production on agricultural output, assess the nature of the relationship between Agricultural Credit Grant Scheme Fund (ACGSF) and agricultural output, trace the direction of causality between Agricultural Credit Grant Scheme Fund (ACGSF) and agricultural output and ascertain the optimal ACGSF loan to crop production required to boost agricultural output in Nigeria. Data for the study were sourced from the Central Bank of Nigeria (CBN) Statistical bulletin 2024 and were interpolated using Eview Econometric package. Augmented Dickey-Fuller (ADF) unit root test and Autoregressive and Distributed Lag (ARDL) bounds test of co-integration were carried out and the Autoregressive Distributed Lag ARDL model was applied to extract the data set The findings showed that the variables were integrated of order zero and one and had a long run relationship. The result of the short run ARDL indicated that loans granted to Mixed Production in the third quarter had positive significant effect on agricultural output while those granted to crop production had negative but insignificant effect. It was shown by the finding that. oans granted to and fishery production had positive insignificant effect on agricultural output in Nigeria. The result of the ARDL Bound test showed that the variables had a long run relationship among the variables used in the model. There was an evidence of a unidirectional causality flowing from agricultural output to loan granted to Mixed Farming Productivity (MIP) by the result of the Granger Causality. The result of the Non-Linear Threshold Quadratic model showed that the maximum loan to be granted to the crop production in order to guarantee maximum agricultural productivity was N710,266.055. The study recommended the need to give priority to loans the mixed farming production than fishery or crop production; monitor and evaluate the loans granted to farmers from the first quarter to the third quarter; diversify loans given to farmers; and grant each farmer at least a sum of N710,266.055 in order to attain a maximum agricultural productivity in Nigeria.

Journal of World Economic ResearchVol. 14(2)
University of Nigeria (NG), Enugu State University of Science and Technology (NG)
Zero hunger
Openalex Percentile: Top 16%
Microfinance and Financial Inclusion
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.