Previous studies have shown a significant and positive relationship between agricultural output and long run economic development. Nigeria, with current extreme poverty rate of 48% is also characterized with high level of food insecurity. The country however, has about 99 million ha of arable land which supports numerous farming activities. Therefore, there exist an opportunity to increase agricultural output and achieve economic development. Further studies also showed that the percentage of agricultural loans to total loans in Nigeria have been declining over the last 15 years which suggests some form of neglect of the sector. This paper therefore examined the impact of agricultural loans and other relevant variables on agricultural GDP in Nigeria with a view to estimate a regression model that can explain variability in agricultural GDP. All the data used were secondary data collected from the annual statistical bulletin of the Central Bank of Nigeria (2018) and USDA, Economic Research Service (Nov. 2019). Ordinary Least Square regression model was used to estimate regression parameters and to show relationship between the variables. Analyzed results showed that agricultural GDP in Nigeria is statistically dependent on agricultural loan, government expenditure and available farm land. The result was statistically tested to be significant at >=95% level of confidence. Further results also showed that agricultural loan in Nigeria is statistically dependent on agricultural credit guarantee and Non-performing loan ratio. This was also tested to be significant at >=95% level of confidence.The study recommended that the results calls for more allocation of credit for agricultural purposes, more government spending to agriculture and more funding of the agricultural credit guarantee program by the government.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-3690 |
| Date | 01 May 2020 |
| Creators | Arala, Ibrahim Olusegun |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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