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Estimating Farm Efficiency in the Presence of Double Heteroscedasticity Using Panel Data

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Abstract

The accuracy of technical efficiency measures is important given the interest in such measures in policy discussions. In recent years the use of stochastic frontiers has become popular for estimating technical inefficiency, but estimated inefficiencies are sensitive to specification errors. One source of such errors is heteroscedasticity. This paper addresses this issue by extending the Hadri (1999) correction for heteroscedasticity to stochastic production frontiers and to panel data. It is argued that heteroscedasticity within an estimation can have a significant effect on results, and that correcting for heteroscedasticity yields more accurate measures of technical inefficiency. Using panel data on cereal farms, it is found that the usual technical efficiency measures used in stochastic production frontiers are significantly sensitive to the extended correction for heteroscedasticity.

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Bibliographic Info

Article provided by Universidad del CEMA in its journal Journal of Applied Economics.

Volume (Year): VI (2003)
Issue (Month): (November)
Pages: 255-268

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Handle: RePEc:cem:jaecon:v:6:y:2003:n:2:p:255-268

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Keywords: stochastic frontier production; heteroscedasticity; technical efficiency; panel data;

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References

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  1. Hadri, K. & Whittaker, J., 1995. "Efficiency, environmental Contaminants and Farm Size: Testing for Links Using Stochastic Production Frontiers," Discussion Papers 9505, Exeter University, Department of Economics.
  2. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-11, January.
  3. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  4. Karim Abadir & Kaddour Hadri, . "Bias Nonmonotonicity in Stochastic Difference Equations," Discussion Papers 96/15, Department of Economics, University of York.
  5. Karim Abadir & Kaddour Hadri & Elias Tzavalis, . "The Influence of VAR Dimensions on Estimator Biases," Discussion Papers 96/14, Department of Economics, University of York.
  6. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  7. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc.
  8. Kaddour Hadri, 1997. "A frontier approach to disequilibrium models," Applied Economics Letters, Taylor & Francis Journals, vol. 4(11), pages 699-701.
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Cited by:
  1. Shinji Yane & Sanford Berg, 2013. "Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2337-2348, June.
  2. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
  3. Saldias, Rodrigo & von Cramon-Taubadel, Stephan, 2012. "Access to credit and the determinants of technical inefficiency among specialized small farmers in Chile," DARE Discussion Papers 1211, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
  4. Kumbhakar, Subal C. & Lien, Gudbrand D. & Hardaker, J. Brian, 2011. "Technical efficiency in competing panel data models: A study of Norwegian grain farming," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114673, European Association of Agricultural Economists.

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