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Estimation of Efficiency with the Stochastic Frontier Cost Function and Heteroscedasticity: A Monte Carlo Study

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  • Kim, Taeyoon
  • Brorsen, B. Wade
  • Kenkel, Philip L.

Abstract

The objective of this article is to address heteroscedasticity in the stochastic frontier cost function using aggregated data and verify it using a Monte Carlo study. We find that when the translog form of a stochastic frontier cost function with aggregated data is estimated, all explanatory variables can inversely affect the variation of error terms. Our Monte Carlo study shows that heteroscedasticity is only significant in the random effect and the unexplained error term not in the inefficiency error term. Also, it does not cause biases, which is quite opposite of previous research. These are because our model is approximately defined by first order Taylor series around zero inefficiency area. But, disregarding heteroscedasticity causes the average inefficiency to be overestimated when the variation of inefficiency term dominates the other error terms.

Suggested Citation

  • Kim, Taeyoon & Brorsen, B. Wade & Kenkel, Philip L., 2008. "Estimation of Efficiency with the Stochastic Frontier Cost Function and Heteroscedasticity: A Monte Carlo Study," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6408, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6408
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    References listed on IDEAS

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    1. 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 105-111, January.
    2. Greene, William H., 1980. "On the estimation of a flexible frontier production model," Journal of Econometrics, Elsevier, vol. 13(1), pages 101-115, May.
    3. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    4. Dickins, William T, 1990. "Error Components in Grouped Data: Is It Ever Worth Weighting?," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 328-333, May.
    5. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
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    Keywords

    Resource /Energy Economics and Policy;

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