FARMERS

UDENSI A.I.1, ANYIRO C.O.2, OREBIYI J.S.3, EZE C.C.4, OHAJIANYA D.O.5, EZEH C.I.6
1Department of Agricultural Economics, Federal University of Technology, Owerri, Nigeria.
2Department of Agricultural Economics and Extension, Abia State University, Umuahia Campus, Umuahia, Abia state, Nigeria.
3Department of Agricultural Economics, Federal University of Technology, Owerri, Nigeria.
4Department of Agricultural Economics, Federal University of Technology, Owerri, Nigeria.
5Department of Agricultural Economics, Federal University of Technology, Owerri, Nigeria.
6Department of Agricultural Economics and Extension, Abia State University, Umuahia Campus, Umuahia, Abia state, Nigeria.

Received : 14-11-2013     Accepted : 09-12-2013     Published : 27-12-2013
Volume : 1     Issue : 2       Pages : 27 - 30
World Res J Trop Agr 1.2 (2013):27-30

Cite - MLA : UDENSI A.I., et al "FARMERS." World Research Journal of Tropical Agriculture 1.2 (2013):27-30.

Cite - APA : UDENSI A.I., ANYIRO C.O., OREBIYI J.S., EZE C.C., OHAJIANYA D.O., EZEH C.I. (2013). FARMERS. World Research Journal of Tropical Agriculture, 1 (2), 27-30.

Cite - Chicago : UDENSI A.I., ANYIRO C.O., OREBIYI J.S., EZE C.C., OHAJIANYA D.O., and EZEH C.I. "FARMERS." World Research Journal of Tropical Agriculture 1, no. 2 (2013):27-30.

Copyright : © 2013, UDENSI A.I., et al, Published by Bioinfo Publications. This is an subscription based article distributed under the terms of the Creative Commons Attribution License, in which, you may not use the material for commercial purposes, you may not distribute the modified material.

Abstract

This study sought to examine farmers’ credit stock determinants from commercial banks and its effect on agricultural production in Nigeria. Time series data, covering the periods of 1977-2007, culled basically from the Central Bank of Nigeria’s Statistical Bulletin, 2009 were used. Adopting a simultaneous equation system, Two-Stage Least Square approach, results showed that commercial banks’ credit accessed by farmers (CR) had significant direct positive effect on the Index of Agricultural Production (IAP) at 1% α-level and also indirectly exerted significant positive effect on IAP by attracting more Foreign Private Investment in agriculture (FPI-Agr) at 1% α-level. It was also observed that all the modeled macroeconomic determinants of the volume of commercial banks’ credit accessed by farmers were significant and positively correlated with CR except for Minimum Rediscount Rate (MRR) which was negatively correlated with CR. Minimum rediscount rate (MRR) was found to be the most important macroeconomic determinant of the volume of commercial banks’ credit accessed by farmers (CR) while interest rate, contrary to major opinions, was the least. This study therefore, suggests that the Nigerian government should strategize on effective means of restructuring her monetary policy options that will increase commercial banks’ loan disbursement ability to farmers by carefully lowering the minimum rediscount rate and maintaining a considerable amount of interest rate that will neither be too high for farmers to borrow nor too low for commercial banks to lend, without, jeopardizing the general price level in the economy and other cardinal macroeconomic objectives of the federal government.

References

[1] Maysami R.C., Howe L.C. and Hamzah M.A. (2004) Journal Pengurusan, 24, 47-77  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[2] Trzeciak-Duval A. (2003) Agricultural Economics, 49(3), 106-112.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[3] Kuwornu J.K.M. (2012) A Co-integration Analysis, 4(2), 13-20.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[4] Nwosu F.O., Oguoma N.N.O., Ben-Chendo N.G., Henri-Ukoha A. (2010) Researcher, 2, 87-90.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[5] Rahji M.A.Y. and Adeoti A.I. (2010) International Research Journal of Finance and Economics, 37, 20-27.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[6] Abhiman D., Manjusha S. and John J. (2009) Research Bank of India Occasional Papers, 30(2).  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[7] Ojo C.O., Bila Y., and Iheanacho A.C. (2012) Agris on-line Pa-pers in Economics and Informatics, 4(2), 15-20  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[8] Olokoyo F.O. (2011) International Journal of Financial Re-search, 2(2), 45-53.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[9] Charles S.M. and Gordon H.S. (1995) Journal of Monetary Eco-nomics, 1(1), 47-73.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[10] Eyo O.E. (2008) World Journal of Agricultural Sciences, 4(6), 781-786.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[11] Henri-Ukoha A., Orebiyi J.S., Obasi P.C., Oguoma N.N., Ohajianya D.O., Ibekwe U.C. and Ukoha I.I. (2011) Journal of Development and Agricultural Economics, 3(2), 69-74.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus  

[12] Koutsoyiannis A. (2003) An Introductory Exposition of Econo-metric Methods, 2nd ed., Palgrave Publishers, New York, 384-393.  
» CrossRef  » Google Scholar  » PubMed  » DOAJ  » CAS  » Scopus