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Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model

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  • Wang, Hung-Jen

Abstract

We consider a model that provides flexible parameterizations of the exogenous influences on inefficiency. In particular, we demonstrate the model's unique property of accommodating non-monotonic efficiency effect. With this non-monotonicity, production efficiency no longer increases or decreases monotonically with the exogenous influence; instead, the relationship can shifts within the sample. Our empirical example shows that variables can indeed have non-monotonic effects on efficiency. Furthermore, ignoring non-monotonicity is shown to yield an inferior estimation of the model, which sometimes results in opposite predictions concerning the data.

Suggested Citation

  • Wang, Hung-Jen, 2002. "Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model," MPRA Paper 31076, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:31076
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    References listed on IDEAS

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    1. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(02), August.
    2. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    3. 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.
    4. Meeusen, Wim & van den Broeck, J, 1977. "Technical Efficiency and Dimension of the Firm: Some Results on the Use of Frontier Production Functions," Empirical Economics, Springer, vol. 2(2), pages 109-122.
    5. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    6. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    7. 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.
    8. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    9. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    10. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    stochastic frontiers; heteroscedasticity; non-monotonic effects;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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