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Does Farm Size and Specialization Matter for ProductiveEfficiency? Results from Kansas

Published online by Cambridge University Press:  26 January 2015

Amin W. Mugera  and
Michael R. Langemeier
Amin W. Mugera
Affiliation:
Institute of Agriculture and School of Agriculture and Resource Economics, Faculty of Agriculture and Natural Sciences, The University of Western Australia, Perth, Australia
Michael R. Langemeier
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, Kansas
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Abstract

In this article, we used bootstrap data envelopment analysis techniques toexamine technical and scale efficiency scores for a balanced panel of 564farms in Kansas for the period 1993–2007. The production technology isestimated under three different assumptions of returns to scale and theresults are compared. Technical and scale efficiency is disaggregated byfarm size and specialization. Our results suggest that farms are both scaleand technically inefficient. On average, technical efficiency hasdeteriorated over the sample period. Technical efficiency varies directly byfarm size and the differences are significant. Differences across farmspecializations are not significant.

Keywords

bootstrap, data envelopment analysis, efficiency, farmsD24Q12
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 4 , November 2011 , pp. 515 - 528
Copyright
Copyright © Southern Agricultural Economics Association 2011

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References

Bravo-Ureta, B., Solís, D., Moreira, V., Maripani, J., Thiam, A., and Rivas, T. “Technical Efficiency in Farming: A Meta-regression Analysis.” Journal of Productivity Analysis 27(2007):57–72.10.1007/s11123-006-0025-3Google Scholar
Byrnes, R, Färe, R., Grosskopf, S., and Kraft, S. “Technical Efficiency and Size: The Case of Illinois Grain Farms.” European Review of Agriculture Economics 14(1987):367—81.Google Scholar
Chavas, J.V., and Aliber, M. “An Analysis of Economics Efficiency in Agriculture: A Nonparametric Approach.” Journal of Agricultural Research Economics. 18(1993):1–16.Google Scholar
Daraio, C, and Simar, L. Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications. New York: Springer, 2007.Google Scholar
Featherstone, A.M., Langemeier, M.R., and Ismet, M. “A Nonparametric Analysis of Efficiency for a Sample of Kansas Beef Cow Farms.” Journal of Agricultural Economics 29(1997):175–84.Google Scholar
Henderson, D.J., and Zelenyuk, V. “Testing for (Efficiency) Catching-up.” Southern Economic Journal 73(2007):1003–19.Google Scholar
Hughes, A., and Yaisawarng, S. “Sensitivity and Dimensionality Tests of DEA Efficiency Scores.” European Journal of Operational Research 154(2004):410–22.10.1016/S0377-2217(03)00178-4Google Scholar
Kalaitzandonakes, N.G., Wu, S., and Ma, J. “The Relationship between Technical Efficiency and Firm Size Revisited.” Canadian Journal of Agricultural Economics 40(1992):427–42.10.1111/j.1744-7976.1992.tb03705.xGoogle Scholar
Key, N., McBride, W., and Mosheim, R. “Decomposition of Total Factor Productivity Change in the U.S. Hog Industry.” Journal of Agricultural and Applied Economics 40(2008):137–49.S1074070800028029Google Scholar
Langemeier, M. “Kansas Farm Management SAS Data Bank Documentation.” Staff Paper No. 11-01. Department of Agricultural Economics, Kansas State University, August 2010.AMBIGUOUS (934511 citations)Google Scholar
Olson, K., and Vu, L. “Economic Efficiency in Farm Households: Trends, Explanatory Factors, and Estimation Methods.” Agricultural Economics 40(2009):587–99.10.1111/j.1574-0862.2009.00400.xGoogle Scholar
Paul, CM., Nehring, R., Banker, D., and Somwaru, A. “Scale Economies and Efficiency in U.S. Agriculture: Are Traditional Farms History?” Journal of Productivity Analysis 22(2004):185–205.10.1007/s11123-004-7573-1Google Scholar
Serra, T., Zilberman, D., and Gil, J.M. “Farms' Technical Inefficiencies in the Presence of Government Programs.” The Australian Journal of Agricultural and Resource Economics 52(2008):57–76.10.1111/j.1467-8489.2008.00412.xGoogle Scholar
Silverman, R.W. Density Estimation for Statistical and Data Analysis. London: Chapman and Hall, 1986.Google Scholar
Simar, L., and Wilson, P. “Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models.” Management Science 44(1998):49–61.10.1287/mnsc.44.1.49Google Scholar
Simar, L., and Wilson, P. “Statistical Inference in Nonparametric Frontier Models: The State of the Art.” Journal of Productivity Analysis 13(2000):49—78.Google Scholar
Simar, L., and Zelenyuk, V. “On Testing Equality of Distributions of Technical Efficiency Scores.” Economic Review (Federal Reserve Bank of Atlanta) 25(2006):497–522.Google Scholar
Wand, M.P., and Jones, M.C. Kernel Smoothing. New York: Chapman and Hall, 1995.Google Scholar
Weersink, A., Turvey, C.G., and Godah, A. “Decomposition Measures of Technical Efficiency for Ontario Dairy Farms.” Canadian Journal of Agricultural Economics 38(1990):439–56.Google Scholar
Wilson, P.W. “FEAR: A Package for Frontier Efficiency Analysis with R.” Socio-Economic Planning Sciences 42(2008):247–54.10.1016/j.seps.2007.02.001Google Scholar
Wu, S., Devadoss, S., and Lu, Y. “Estimation and Decomposition of Technical Efficiency for Sugarbeet Farms.” Applied Economics 35(2003):471–84.10.1080/00036840210161819Google Scholar