Using the Nerlovian Adjustment Model to Assess the Response of Farmers to Price and Other Related Factors: Evidence from Sierra Leone Rice Cultivation
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Using the Nerlovian Adjustment Model to Assess the Response of Farmers to Price and Other Related Factors: Evidence from Sierra Leone Rice Cultivation

Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V. Gborie

Abstract:

The goal of this study was to increase the awareness of the description and assessments of rice acreage response and to offer mechanisms for agricultural policy scrutiny. The ordinary least square (OLS) technique was utilized to determine the coefficients of acreage response models for the rice varieties. The magnitudes of the coefficients (λ) of both the ROK lagged and NERICA lagged acreages were found positive and highly significant, which indicates that farmers’ adjustment rate was very low. Regarding lagged actual price for both the ROK and NERICE rice varieties, the short-run price elasticitieswere lower than long-run, which is suggesting a long term adjustment of the acreage under the crop.

However, the apparent recommendations for policy transformation are to open farm gate prices and to decrease government’s involvement in agricultural sector especially in the acquisition of agricultural inputs. Impending research have to be centered on how this might be better realized. Necessary conditions should be made available to the private sector by means of minimizing price volatility. In accordance with structural reforms, it is necessary to convey output prices to farmers with minimum distortion. There is need to eradicate price subsidies and control, which generate distortion in the market in addition to huge financial costs.

Keywords: Acreage response, rate of adjustment, rice varieties, Sierra Leone.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1091290

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[1] Vinciguerra, P., et al., Intra-and Postoperative Variation in Ocular Response Analyzer Parameters in Keratoconic Eyes after Corneal Cross-Linking. J Refract Surg, 2010. 26(9): p. 669-676.
[2] Calabresi, G., Transaction Costs, Resource Allocation and Liability Rules--A Comment. Journal of Law and Economics, 1968. 11(1): p. 67-73.
[3] Sen, A.K., The Resources, Values, and Development. 1997: Harvard University Press.
[4] Binswanger, H. The Policy Response of Agriculture. in Proceedings of the World Bank Annual Conference on Development Economics. 1989.
[5] Kassie, M., B. Shiferaw, and G. Muricho, Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda. World Development, 2011. 39(10): p. 1784-1795.
[6] Salois, M.J., Obesity and Diabetes, the Built Environment, and the ‘Local’Food Economy in the United States, 2007. Economics & Human Biology, 2012. 10(1): p. 35-42.
[7] Leone, S., Unblocking Results Case Study. 2013.
[8] Jaeger, W.K. and B. Mundial, TheEffects of Economic Policies on African Agriculture. Vol. 147. 1992: World Bank Washington, DC.
[9] Widner, J.A., TheOrigins of Agricultural Policy in Ivory Coast 1960–86. The Journal of Development Studies, 1993. 29(4): p. 25-59.
[10] Maconachie, R. and G. Hilson, Artisanal Gold Mining: A New Frontier in Post-Conflict Sierra Leone? The Journal of Development Studies, 2011. 47(4): p. 595-616.
[11] Reddy, A., M. Bantilan, and G. Mohan, Enabling Pulses Revolution in India. Available at SSRN 2240347, 2013.
[12] Mellor, J.W. and B.F. Johnston, TheWorld Food Equation:Interrelations among Development, Employment, and Food Consumption. Journal of Economic Literature, 1984. 22(2): p. 531-574.
[13] Behrman, J.R., Supply Response in Underdeveloped Agriculture; a Case Study of Four Major Annual Crops in Thailand, 1937-1963. 1968.
[14] Rao, J.M., Agricultural Supply Response: A Survey. Agricultural Economics, 1989. 3(1): p. 1-22.
[15] Braulke, M., A Note on the NerloveModel of Agricultural Supply Response. International Economic Review, 1982. 23(1): p. 241-244.
[16] Bond, M.E., Agricultural Responses to Prices in Sub-Saharan African Countries. IMF Staff Papers, 1983. 30(4): p. 703-726.
[17] Strauss, J., Marketed Surpluses of Agricultural Households in Sierra Leone. American Journal of Agricultural Economics, 1984. 66(3): p. 321-331.
[18] Schiff, M. and C.E. Montenegro, Aggregate Agricultural Supply Response in Developing Countries: A Survey of Selected Issues. Economic Development and Cultural Change, 1997. 45(2): p. 393-410.
[19] Thiele, R., Estimating the Aggregate Agricultural Supply Response: A Survey of Techniques and Results for Developing Countries. 2000, Kiel Working Papers.
[20] De Castro, E.R. and E.C. Teixeira, Rural Credit and Agricultural Supply in Brazil. Agricultural Economics, 2012. 43(3): p. 293-302.
[21] Figueiredo, A.M.R., et al., Spatial Analysis of Agricultural Supply Response in the Brazilian Center-West. EconomiaAgraria y RecursosNaturales, 2011. 15.
[22] Zhang, X., Agricultural Extension, Transactions Costs, and Supply Response: Discussion. American Journal of Agricultural Economics, 2012. 94(2): p. 393-394.
[23] Mooney, D.F., B.L. Barham, and C. Lian. Sustainable Biofuels, Marginal Agricultural Lands, and Farm Supply Response: Micro-Evidence for Southwest Wisconsin. in 2013 Annual Meeting, August 4-6, 2013, Washington, DC. 2013: Agricultural and Applied Economics Association.
[24] Arnade, C. and J. Cooper. Price Expectations and Supply Response. in 2013 Annual Meeting, August 4-6, 2013, Washington, DC. 2013: Agricultural and Applied Economics Association.
[25] Lynch, K., et al., Meeting the Urban Challenge? Urban Agriculture and Food Security in Post-Conflict Freetown, Sierra Leone. Applied Geography, 2012.
[26] Shahbaz, M., M. Mutascu, and A.K. Tiwari, Revisiting the Relationship between Electricity Consumption, Capital and Economic Growth: Cointegrationand Causality Analysis in Romania. Journal for Economic Forecasting, 2012. 3: p. 97-120.
[27] Chhetri, N.B. and W.E. Easterling, Adapting to Climate Change: Retrospective Analysis of Climate Technology Interaction in the Rice-Based Farming System of Nepal. Annals of the Association of American Geographers, 2010. 100(5): p. 1156-1176.
[28] Ham, J.C., Estimation of a Labour Supply Model with Censoring due to Unemployment and Underemployment. The Review of Economic Studies, 1982. 49(3): p. 335-354.
[29] Aizenman, J. and Y. Jinjarak, Current Account Patterns and National Real Estate Markets. Journal of Urban Economics, 2009. 66(2): p. 75-89.
[30] Van Rompay, T.J. and A.T. Pruyn, When Visual Product Features Speak the Same Language: Effects of Shape-Typeface Congruence on Brand Perception and Price Expectations*. Journal of Product Innovation Management, 2011. 28(4): p. 599-610.
[31] Hummel, I., et al., Arabidopsis Plants Acclimate to Water Deficit at Low Cost Through Changes of Carbon Usage: An Integrated Perspective Using Growth, Metabolite, Enzyme, and Gene Expression Analysis. Plant Physiology, 2010. 154(1): p. 357-372.
[32] Zhao, H., Dynamic Relationship between Exchange Rate and Stock Price: Evidence from China. Research in International Business and Finance, 2010. 24(2): p. 103-112.
[33] Schreinemachers, P. and T. Berger, AnAgent-Based Simulation Model of Human–Environment Interactions in Agricultural Systems. Environmental Modelling & Software, 2011. 26(7): p. 845-859.
[34] Hendricks, N.P., et al., The Environmental Effects of Crop Price Increases: Nitrogen Losses in the US Corn Belt. 2013.
[35] Lusardi, A. and O.S. Mitchell, Financial Literacy and Planning: Implications for Retirement Wellbeing. 2011, National Bureau of Economic Research.
[36] Mitra, S. and J.M. Boussard, A Simple Model of Endogenous Agricultural Commodity Price Fluctuations with Storage. Agricultural Economics, 2012. 43(1): p. 1-15.
[37] Arthur, W., et al., Asset Pricing under Endogenous Expectations in an Artificial Stock Market. Available at SSRN 2252, 1996.
[38] McGuinness, T. and K. Cowling, Advertising and the Aggregate Demand for Cigarettes. European Economic Review, 1975. 6(3): p. 311-328.
[39] Phitthayaphinant, P., B. Somboonsuke, and T. Eksomtramage, Supply Response Function of Oil Palm in Thailand. Journal of Agricultural Technology, 2013. 9(4): p. 727-747.
[40] Harris, R.D. and A. Nguyen, Long Memory Conditional Volatility and Asset Allocation. International Journal of Forecasting, 2013. 29(2): p. 258-273.
[41] Fenichel, E.P. and X. Wang, The Mechanism and Phenomena of Adaptive Human Behavior During an Epidemic and the Role of Information, in Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases. 2013, Springer. p. 153-168.
[42] Lambert, D.M., W. Xu, and R.J. Florax, Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models. International Regional Science Review, 2012.
[43] Stolz, S. and M. Wedow, Banks’ Regulatory Capital Buffer and the Business Cycle: Evidence for Germany. Journal of Financial Stability, 2011. 7(2): p. 98-110.
[44] Pao, H.-T. and C.-M. Tsai, Modeling and Forecasting the CO2Emissions, Energy Consumption, and Economic Growth in Brazil. Energy, 2011. 36(5): p. 2450-2458.
[45] Potgieter, A., et al., Early-Season Crop Area Estimates for Winter Crops in NE Australia Using MODIS Satellite Imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 2010. 65(4): p. 380-387.
[46] Hanssens, D.M. and M.G. Dekimpe, 26 Short-Term and Long-Term Effects of Marketing Strategy. Handbook of Marketing Strategy, 2012: p. 457.
[47] Helms, A.C., Keeping up with the Joneses: Neighborhood effects in Housing Renovation. Regional Science and Urban Economics, 2012. 42(1): p. 303-313.
[48] Helfand, S.M. and E.S. Levine, Farm Size and the Determinants of Productive Efficiency in the Brazilian Center-West. Agricultural Economics, 2004. 31(2-3): p. 241-249.
[49] Visschers, V.H., C. Keller, and M. Siegrist, Climate Change Benefits and Energy Supply Benefits as Determinants of Acceptance of Nuclear Power Stations: Investigating an Explanatory Model. Energy Policy, 2011. 39(6): p. 3621-3629.
[50] Mátyás, L., Proper Econometric Specification of the Gravity Model. The world economy, 1997. 20(3): p. 363-368.
[51] Lam, P.-L. and A. Shiu, Economic Growth, Telecommunications Development and Productivity Growth of the Telecommunications Sector: Evidence around the World. Telecommunications Policy, 2010. 34(4): p. 185-199.
[52] Ramalho, E.A., J.J. Ramalho, and J.M. Murteira, Alternative Estimating and Testing Empirical Strategies for Fractional Regression Models. Journal of Economic Surveys, 2011. 25(1): p. 19-68.
[53] Barros, P., TheBlack Box of Health Care Expenditure Growth Determinants. 2010.
[54] Dinpashoh, Y., et al., Trends in Reference Crop Evapotranspiration over Iran. Journal of Hydrology, 2011. 399(3): p. 422-433.
[55] Jones, C.T., AnotherLook at US Passenger Vehicle Use and the'Rebound'Effect from Improved Fuel Efficiency. The Energy Journal, 2010(4): p. 99-110.
[56] Jarque, C.M., Jarque-Bera Test, in International Encyclopedia of Statistical Science. 2011, Springer. p. 701-702.
[57] Ziramba, E., Price and Income Elasticities of Crude Oil Import Demand in South Africa: A Cointegration Analysis. Energy Policy, 2010. 38(12): p. 7844-7849.
[58] Yu, H., E. Luedeling, and J. Xu, Winter and Spring Warming Result in Delayed Spring Phenology on the Tibetan Plateau. Proceedings of the National Academy of Sciences, 2010. 107(51): p. 22151-22156.
[59] Lawlor, D.A., et al., Association between General and Central Adiposity in Childhood, and Change in These, with Cardiovascular Risk Factors in Adolescence: Prospective Cohort Study. BMJ: British Medical Journal, 2010. 341.
[60] Ozturk, I. and A. Acaravci, The Causal Relationship between Energy Consumption and GDP in Albania, Bulgaria, Hungary and Romania: Evidence from ARDL Bound Testing Approach. Applied Energy, 2010. 87(6): p. 1938-1943.
[61] Alves, D.C. and R. De Losso da SilveiraBueno, Short-Run, Long-Run and Cross Elasticities of Gasoline Demand in Brazil. Energy Economics, 2003. 25(2): p. 191-199.