European Journal of Agriculture and Forestry Research (EJAFR)

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Stochastic Frontier Production Function on the Resource Use Efficiency of Fadama II Crop Farmers in Adamawa State, Nigeria

Abstract

This study assess the resource use efficiency of Fadama II beneficiary crop farmers in Adamawa state, Nigeria . Data were collected on a sample of 160 farmers and were analyzed using stochastic frontier production function. The maximum likelihood estimates (MLE) for the stochastic production function results shows that the coefficients of farm size, inorganic fertilizer, hired labour and expenses on ploughing, significantly affect food crop output of the respondents. The mean technical efficiency was 0.71 (or 71%), the mean allocative efficiency was 0.76 (or 76%) and the mean economic efficiency was 0.54 (or 54%). The study concludes that, the maximum likelihood estimates (MLE) for the stochastic production function of the coefficients of farm size(X1), inorganic fertilizer (X3), hired labour (X5) and expenses on ploughing (X6) were found to be positive and significantly affect food crop output of the respondents with the mean technical efficiency is 0.71 (or 71%). It is however recommended that, Government and other donor agencies should intensify advisory services activities on effective resource allocation, utilization and other ways of increasing farmers’ beneficiary income. Government in partnership with private sector should encourage farmers to increase its technical efficiency in food crop production which could be achieved through improved farmer specific efficiency factors, which include improved farmer education, access to credit, access to improved extension services and less crop diversification. Government to introduce mentorship and pre-job training programmes and to include the youth in policy decisions.

Keywords: Application, Crop Farmers, Efficiency, Fadama II, Resource, Stochastic Frontier Production Function.

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejafr@ea-journals.org
Impact Factor: 6.74
Print ISSN: 2054-6319
Online ISSN: 2054-6327
DOI: https://doi.org/10.37745/ejafr.2013

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