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Yield response of rice in Nigeria: A co-integration analysis

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Yield response of rice in Nigeria: A co-integration analysis
American Journal of Agriculture and Forestry
2014; 2(2): 15-24
Published online January 20, 2014 (http://www.sciencepublishinggroup.com/j/ajaf) doi: 10.11648/j.ajaf.20140202.11

Yield response of rice in Nigeria: A co-integration analysis
David Boansi
Department of Economic and Technological Change, Center for Development Research (ZEF), University of Bonn, Germany

Email address: boansidavid@rocketmail.com (D. Boansi)

To cite this article:
David Boansi. Yield Response of Rice in Nigeria: A Co-Integration Analysis. American Journal of Agriculture and Forestry.
Vol. 2, No. 2, 2014, pp. 15-24. doi: 10.11648/j.ajaf.20140202.11

Abstract: To help bridge information gap in supply response studies for Nigeria and inform policy decision on how the demand-supply gap for rice in Nigeria could be bridged, the current study through the use of Johansen’s Full Information
Maximum Likelihood test estimated a yield response model for Nigeria using national level data for the period 1966-2008.
The results suggest that, increasing yield levels for paddy rice in Nigeria and ensuring stability requires interplay of biophysical, socio-economic and structural forces. By estimates for the current study, bridging of the demand-supply gap can be realized through initiation of measures to address inefficiencies in the supply chain to ensure appropriate transmission of price increment, promotion of local rice consumption to ensure ready market for farmers in times of increasing output, addressing soil fertility challenges through efficient use of fertilizer and regular management of fertility of rice fields, and increasing farmers access to credit to help them meet cost of relevant inputs of production. The latter suggestion could to a greater extent incite appropriate response of farmers to both price and non-price incentives in the country. Diagnostic tests conducted indicate that the residual series is normally distributed, non-serially correlated and



References: [16] Fashola, O.O., Imolehin, E.D., and Wakatsuki, T. (2007). Abubakar, S. (2013). Why Nigeria imports N1bn rice daily. (1996). Evolving the Nigerian Agricultural Research Strategy Plan: Agro-Ecological Inputs Pakistan with “Endogenous” Technology. The Pakistan Development Review 33:4 Part II (Winter 1994) pp Amanor-Boadu, V. (2012). Rice price trends in Ghana (2006-2011) Anderson, K. and Nelgen, S. (2012). Updated national and global agricultural trade and welfare reduction indexes, 1995 [12] Daramola, B. (2005). Government policies and competitiveness of Nigerian rice economy Republic of Benin, November 07-09, 2005 [13] Defoer, T., Wopereis, M.C.S., Jones, M.P Erenstein, O., and Guei, R.G. (2004). Challenges and technical opportunities for rice-based production systems for Proceedings of FAO Rice Conference, Rome, Italy, 12-13 February, 2004. [14] Engle, R.F. and Granger, C.W.J. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 55:251-276 [15] FAOSTAT (2013) June14, 2013 K.R. (2006). Spatial patterns of labile forms of phosphorus in a subtropical wetland [21] Johansen, S. and Juselius K. (1990). Maximum likelihood estimation and inference on co-integration with application

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