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Estimation and Inference in Parametric Stochastic Frontier Models: A SAS/IML Procedure for a Bootstrap Method

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  • Tchumtchoua, Sylvie

Abstract

Parametric Stochastic Frontier Models are widely used in productivity analysis and are commonly estimated using FRONTIER, STATA or LIMDEP packages, which only provide point estimates for firm-specific technical efficiency. Confidence intervals for technical efficiencies with superior coverage properties than those offered by the Horrace and Schmidt (1996) method may be computed using the Bootstrap method introduced by Simar and Wilson (2005). To facilitate these calculations, we propose a SAS/IML procedure, which computes these confidence intervals for stochastic frontier models with or without inefficiency effects. We apply the program to estimating supermarket-specific technical efficiency in the U.S. Results indicates that the program works very well and produce narrower confidence intervals than those obtain using Horrace and Schmidt (1996) method.

Suggested Citation

  • Tchumtchoua, Sylvie, 2006. "Estimation and Inference in Parametric Stochastic Frontier Models: A SAS/IML Procedure for a Bootstrap Method," Research Reports 149177, University of Connecticut, Food Marketing Policy Center.
    • Handle: RePEc:ags:uconnr:149177
    DOI: 10.22004/ag.econ.149177
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    References listed on IDEAS

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    1. K. Hadri & C. Guermat & J. Whittaker, 2003. "Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers," Empirical Economics, Springer, vol. 28(1), pages 203-222, January.
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    3. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    4. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
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