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Modeling the Impact of Agricultural Credit Finance and Socio-economic Characteristics of Farmers on Rice Production: Multiple Linear Regression with Categorical Predictor Variables Approach

Yisa Yakubu


In this paper, the impact of farmers’ access to agricultural credit finance and their socio-economic characteristics on the quantity of rice produced at the end of the 2013/2014 cropping season for rice farmers from some sampled rice-producing communities in Niger state was modeled using Least squares regression approach with categorical input variables. The contributions of each of the dummy predictors to the fitness of the model and hence, its role in the explanatory power of the model, were examined. It was observed that the amount of credit finance received by farmers plays a significant role in the explanatory power of the fitted model while none of the farmers’ socio-economic characteristics significantly improves the goodness-of-fit of the model.


Agricultural credit finance, Multiple Regression, Categorical Predictors, Modeling, Rice production.

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