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One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels

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  • Wang, Hung-jen
  • Schmidt, Peter

Abstract

Consider a stochastic frontier model with one-sided inefficiency u, and suppose that the scale of u depends on some variables (firm characteristics) z. A one-step model specifies both the stochastic frontier and the way in which u depends on z, and can be estimated in a single step, for example by maximum likelihood. This is in contrast to a two-step procedure, where the first step is to estimate a standard stochastic frontier model, and the second step is to estimate the relationship between (estimated) u and z. In this paper we propose a class of one-step models based on the scaling property that u equals a function of z times a one-sided error u * whose distribution does not depend on z. We explain theoretically why two-step procedures are biased, and we present Monte Carlo evidence showing that the bias can be very severe. This evidence argues strongly for one-step models whenever one is interested in the effects of firm characteristics on efficiency levels.

Suggested Citation

  • Wang, Hung-jen & Schmidt, Peter, 2001. "One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels," MPRA Paper 31075, University Library of Munich, Germany, revised Mar 2002.
  • Handle: RePEc:pra:mprapa:31075
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    References listed on IDEAS

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    1. Christian Ritter & Léopold Simar, 1997. "Pitfalls of Normal-Gamma Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 8(2), pages 167-182, May.
    2. 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.
    3. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
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    5. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    6. 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.
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    More about this item

    Keywords

    technical efficiency; stochastic frontiers;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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