Abdul-Basit Tampuli Abukari, Tuna Alemdar
  AGRISE,Vol 19, No 1 (2019),  47-64  
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Abstract: The study sets out to measure the technical, allocative and cost efficiencies of maize farming in the Northern Region of Ghana for the 2014-2015 farming season. The region has 73% of its population as farmers, with maize being the most cultivated and consumed cereal. Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) are employed in the estimation. Interviews were conducted on 121 farmers selected through a mixed sampling technique. The study also segregated the quantities and prices of nitrogen and phosphorus from compound fertilizers. Under DEA, the study found an average efficiency of 79%, 67% and 53% for technical, allocative and cost efficiencies respectively. For SFA the results respectively are 77%, 27% and 21%. Cost and allocative efficiency estimates were very low especially for SFA. Using fractional regression analysis, it was found that household structure of farmers determined their technical efficiencies. Maize land size, marital status, education, and maize farming experience were found to affect allocative efficiency whiles marital status, household structure and maize farming experience affected cost efficiency. The study also found that labor was excessively used in the production process. Fertilizer application increased maize productivity more than other inputs. Policy recommendations were made following these findings.


causes of inefficienc;, data envelopment analysis; efficiency; fractional regression; ghana; maize; stochastic frontier analysis

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Addai KN, Owusu V, 2014. Technical efficiency of maize farmers across various agro ecological zones of Ghana. Journal of Agriculture and Environmental Sciences, 3, 149-172.

Akramov K, Malek M, 2011. Analyzing Profitability of Maize, Rice, and Soybean Production in Ghana: Results of Pam and DEA Analysis. GSSP Working Paper 28. Accra, Ghana: International Food Policy Research Institute

Alemdar T, Ören MN, 2006. Measuring Technical Efficiency of Wheat Production in Southeastern Anatolia with Parametric and Nonparametric Methods. Pakistan Journal of Biological Sciences, V. 9, N. 6, 1088- 1094, 2006.

Amanor-Boadu V, Zereyesus Y, Ross K, 2015. Agricultural production survey for the Northern Regions of Ghana: 2013–2014 results.

Anang BT, Bäckman S, Sipiläinen T, 2016. Agricultural microcredit and technical efficiency: The case of smallholder rice farmers in Northern Ghana. Journal of Agriculture and Rural Development in the Tropics and Subtropics 117(2): 189-202.

Chapoto A, Sabasi D, Asant-Addo C, 2015. Fertilizer Intensification and Soil Fertility Impact on Maize Yield Response in Northern Ghana. 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California, Agricultural and Applied Economics Association & Western Agricultural Economics Association.

Coelli TJ, Prasada RDS, O‟Donnell CJ, Battese GE, 2005. An Introduction to Efficiency and Productivity Analysis, 2nd Edition, Springer, New York, 366 P.

Cooke E, Hague S, McKay A, 2016. The Ghana Poverty and Inequality report: Using the 6th Ghana Living Standards Survey. Accra: Art Excel Gh.

Danquah M, Iddrisu AM, 2016. Ghana’s long run growth: Policy options for inclusivity and equity. Paper prepared for the African Development Bank, Accra.

Davidson R, MacKinnon JG, 1981. Several Tests for Model Specification in the Presence of Alternative Hypotheses. Econometrica 49(3):781–793

FAO (Food and Agriculture Organization), 2005. Fertilizer Use by Crop in Ghana. International Fertilizer Industry Association (IFA). Land and Water Development Division of FAO.

Ferrier GD, Lovell CAK, 1990. Measuring Cost Efficiency in Banking: Econometric and Linear Programming Evidence. Journal of Econometrics, 46, 229-245.

Gelan A, Muriithi BW, 2012. Measuring and Explaining Technical Efficiency of Dairy Farms: A Case Study of Smallholder Farms in East Africa, Agrekon: Agricultural Economics Research, Policy and Practice in Southern Africa, 51:2, 53-74.

GSS (Ghana Statistical Service), 2012. 2010 Population and Housing Census. Summary Report of Final Results.

GSS (Ghana Statistical Service), 2014. Ghana Living Standards Survey (GLSS6) - Main Report

Hjalmarsson L, Kumbhakar S, Heshmati A, 1996. DEA, DFA and SFA: A Comparison. Journal of Productivity Analysis, 7, Pp. 303–327.

Hoff A, 2007. Second Stage DEA: Comparison of Approaches for Modeling the DEA Score. Eur J Oper Res 181:425–435.

Johansson H, 2005. Technical, Allocative, and Economic Efficiency in Swedish Dairy Farms: The Data Envelopment Analysis versus the Stochastic Frontier Approach. The 11th International Congress of The European Association of Agricultural Economists (EAAE), Copenhagen, Denmark, August 24-27, 2005

Jones AM, Rice N, Bago T, Balia S, 2013. Applied Health Economics, second edition. London: Taylor and Francis.

Liu JS, Lu LY, Lu WM, 2016. Research Fronts and Prevailing Applications in Data Envelopment Analysis. In: Zhu J. (eds) Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 238. Springer, Boston, MA

McDonal J, 2009. Using Least Squares and Tobit in Second Stage DEA Efficiency Analyses. Eur J Oper Res 197(2):792–798.

Papke LE, Wooldridge JM, 1996. Econometric methods for fractional response variables with an application to 401(k) plan participation rates. J Appl Econ 11(6):619-632.;2-1

Pregibon D, 1980. Goodness of Link Tests for Generalized Linear Models. Appl Stat 29(1):15–24

Ragasa C, Chapoto A, 2017. Limits to Green Revolution in rice in Africa: The case of Ghana. Land Use Policy 66: 304-321.

Ramanathan R, 2003. An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement. Sage Publications, New Delhi.

Ramalho EA, Ramalho JJS, Henriques PD, 2010a. Fractional Regression Models for Second Stage DEA Efficiency Analyses. J Product Anal 2010; 34:239–255.

Ramalho EA, Ramalho JJS, Murteira J, 2010b. Alternative Estimating and Testing Empirical Strategies for Fractional Regression Models. J Econ Surv.

Ritter C, Simar L, 1997a. Pitfalls of Normal-Gamma Stochastic Frontier Models. Journal of Productivity Analysis 8:2 (May), 167-82.

Rosen CJ, Bierman PM, Eliason RD, 2008. Soil Test Interpretations and Fertilizer Management for Lawns, Turf, Gardens, and Landscape Plants. University of Minnesota Extension, St Paul, Mn

Shamsudeen A, Paul KN, Samuel AD, 2013. Technical efficiency of maize production in Northern Ghana. African Journal of Agricultural Research, 8, 5251-5259.

Sharma KR, Leung PS, Zaleski HM, 1999. Technical, Allocative and Economic Efficiencies in Swine Production in Hawaii: A Comparison of Parametric and Nonparametric Approaches. Agric Econ 20:23–35.

Simar L, Wilson P, 2007. Estimation and Inference in Two-Stage, Semi-Parametric Models of Production Processes. Journal of Econometrics 136, 31–64.

Silva E, Mendes AB, Santos J, 2013. Efficiency Measures in the Agricultural Sector: The Beginning. In ‘‘Efficiency Measures in the Agricultural Sector: With Applications.’’ Mendes, A.B., Soares Da Silva, E.L.D.G., and Santos J.M.A. (Eds.), ISBN: 978-94-007-5738-7, Pp. 3-12.

Singh S, Coelli T, Fleming E, 2001. Performance of Dairy Plants in the Cooperative and Private Sectors in India. Annals of Public and Cooperative Economics, 72: 453–479.

Wooldridge JM, 2016. Introductory Econometrics: A Modern Approach. Cengage Learning, USA.



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