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Derivation of marginal effects of determinants of technical inefficiency

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  • Kumbhakar, Subal C.
  • Sun, Kai

Abstract

In efficiency studies using the stochastic frontier approach, the main focus is to explain inefficiency in terms of some exogenous variables and computation of marginal effects of each of these determinants. Although inefficiency is estimated by its mean conditional on the composed error term (the Jondrow et al., 1982 estimator), the marginal effects are computed from the unconditional mean of inefficiency (Wang, 2002). In this paper we derive the marginal effects based on the Jondrow et al. estimator and use the bootstrap method to compute confidence intervals of the marginal effects.

Suggested Citation

  • Kumbhakar, Subal C. & Sun, Kai, 2013. "Derivation of marginal effects of determinants of technical inefficiency," Economics Letters, Elsevier, vol. 120(2), pages 249-253.
    • Handle: RePEc:eee:ecolet:v:120:y:2013:i:2:p:249-253
    DOI: 10.1016/j.econlet.2013.04.041
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    5. 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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    2. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    3. Baležentis, Tomas & Sun, Kai, 2020. "Measurement of technical inefficiency and total factor productivity growth: A semiparametric stochastic input distance frontier approach and the case of Lithuanian dairy farms," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1174-1188.
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    10. Caetano Luiz Beber & Sebastian Lakner & Ioannis Skevas, 2021. "Organizational forms and technical efficiency of the dairy processing industry in Southern Brazil," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-22, December.
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    12. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    13. Robert Germeshausen & Timo Panke & Heike Wetzel, 2014. "Investigating the Influence of Firm Characteristics on the Ability to Exercise Market Power - A Stochastic Frontier Analysis Approach with an Application to the Iron Ore Market," EWI Working Papers 2014-17, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
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    15. Badunenko, Oleg & Cordero, Jose M. & Kumbhakar, Subal C., 2021. "Are you slacking? Where do you and your country stand in the happiness pursuit?," MPRA Paper 108316, University Library of Munich, Germany.
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    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

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