ESTIMATION OF SORGHUM SUPPLY ELASTICITY IN SOUTH AFRICA
This study aims to estimate sorghum supply elasticity in South Africa. The study used time series data spanning from 1998 to 2016, obtained from the abstracts of agricultural statistics. The Variance Error Correction Model was employed; the study used two dependent variables, these being area and yield response functions. The results have shown that the area response function was found to be a robust model as most of the variables were significant, responsive and elastic. Maize price, as a competing crop for sorghum, negatively influenced the area allocation; however, the remaining variables
had a positive impact on area allocation in the long-run. The yield response function was found not to be robust and hence not adopted. It was therefore concluded that the area response function is more robust than the yield response function, hence sorghum production has shown more response to area
allocation than yield. The findings further indicated that the error correction term for area and for the yield response function was –1.55 and –1.30, respectively. This indicated that the two models were able to revert to equilibrium. Based on the findings, the study recommends that amongst other methods to enhance sorghum output, producers could use improved varieties or hybrids, as this action would result in allocation of more land to sorghum production, following price change.
sorghum; supply; elasticity; error correction model; South Africa
Alhaji, M., Conteh, H., Yan, X., Gborie, A. V. (2014). Using the Nerlovian adjustment model to assess the response of farmers to price and other related factors: Evidence from Sierra Leone rice cultivation. Int. J. Soc. Behav. Edu. Econ. Bus. Indust. Eng., 8(3), 1–7.
Anwarul Huq, A. S. M., Arshad, F. M. (2010). Supply response of potato in Bangladesh: A vector error correction approach. J. Appl. Sci., 10(11), 895–902.
Belete, A. (1995). Economic analysis of supply response among summer wheat growers in Lesotho. UNISWA J. Agric., 4, 55–80.
Belete, A., Fraser, C. G., Trollip, I. R. F. (1995). Econometric estimation of a supply function: An empirical example from agriculture. A guide to supply response analysis, working paper No. 1, 6–27.
DAFF (Department of Agriculture, Forestry and Fisheries) (2010). Sorghum production guideline. Annual report 2009–2010 (pp. 13–28). Retrieved Feb 13th 2017: www. nda.agric.za/SorghumProductionguideline2010DAFF (Department of Agriculture, Forestry and Fisheries) (2015). A profile of the South African grain sorghum
market value chain. Annual report 2014–2015 (pp. 6–27). Retrieved April 13th 2017 from: www.nda.agric.za/GrainSorghumMarketValueChainProfile2015
Gujarati, D. N., Porter, D. C. (2009). Basic Econometrics. Fifth edition. The McGraw-Hill Series Economics, 557–758. New York, USA.
Hallam, D., Zanoli, R. (1993). Error correction models and agricultural supply response. Eur. Rev. Agric. Econ., 20,151–166.
Johansen, S. (1988). Statistical analysis of cointegration vectors. J. Econ. Dyn. Control, 12, 231–254.
McKay, A., Morrissey, O., Vaillant, C. (1998). Aggregate export and food crop supply response in Tanzania. Centre for research in economic development and international trade, University of Nottingham. Credit research paper No. 98(4), 4–34.
Mose, L. O., Burger, K., Kuvyenhoven, A. (2017). Aggregate supply response to price incentives: The case of smallholder maize production in Kenya. African crop science conference proceedings, 8 (pp. 1271–1275).
Munyati, V., Mugabe, D., Chipunza, N., Mafuse, N., Chagwiza, G., Musara, J. (2013). An econometric approach to ascertain sorghum supply response in Zimbabwe. Afr. J. Agr. Res., 8(47), 6034–6038.
Mutua, M. M. (2015). An estimation of sugarcane supply response among out-growers in Mumias sugar company. Masters’ thesis. University of Nairobi, Kenya (pp. 38–60).
National Agricultural Marketing Council (2007). Report on the investigation into the South African sorghum industry: Annual report 2006–2007 (pp. 25–47).
Nerlove, M. 1958. The dynamics of supply: Estimation of farmers’ response to Price. Am. J. Agric. Econ., 41(2), 452–455.
Nmadu, J. N. (2010). Revision of the Nerlovian partial adjustment framework and its application to sorghum production in Nigeria. Afr. J. Agric. Res., 5(5), 25–31. Retrieved Feb 15th 2017 from: http://www.academicjournals.org/AJAR
Paltasingh, K. R., Goyari, P. (2013). Supply response in rainfed agriculture of Odisha, Eastern India: A vector error correction approach. Agric. Econ. Rev., 14(2), 89–104.
Shoko, R. R. (2014). Estimating the supply response of maize in South Africa. Masters’ thesis, University of Limpopo, South Africa (pp. 51–66).
Sihlobo, W., Kabuya, T. (2015). Grain market overview. Grain SA. Retrieved April 12th 2017 from: http://www.grainsa.co.za/grain-market-overview-3
StataCorp. (2011). Stata time series reference manual release 12. Stata Press, 418–754.
Townsend, R., Thirtle, C. (1997). Dynamic acreage response: An error correction model for Maize and Tobacco in Zimbabwe. Occasional Paper Series No. 7 198059, International Association of Agricultural Economists. Retrieved from: https://ideas.repec.org/p/ags/iaaeo7/198059.html
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