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On the Estimation of Technical and Allocative Inefficiency Using Stochastic Frontier Functions: The Case of U.S. Class 1 Railroads

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  • Kumbhakar, Subal C

Abstract

In this paper, the author considers specification and estimation of technical and allocative inefficiency in a cost-minimizing framework using panel data. Some distinguishing features of the model are (1) the functional form of the production technology is flexible enough to allow elasticity to vary across firms; (2) allocative inefficiency, coming from managerial errors ou t of inertia , ignorance, etc., are separated from random errors in optimization; (3) the panel nature of the data allows the estimation of input and firm specific allocative inefficiency together with technical inefficiency; and (4) subdivision of the sample period allows one to make efficiency comparisons of each firm over the subperiods and to check the stability of the parameter estimates. Copyright 1988 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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  • Kumbhakar, Subal C, 1988. "On the Estimation of Technical and Allocative Inefficiency Using Stochastic Frontier Functions: The Case of U.S. Class 1 Railroads," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(4), pages 727-743, November.
    • Handle: RePEc:ier:iecrev:v:29:y:1988:i:4:p:727-43
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    Cited by:

    1. Fawson, Chris & Shumway, C. Richard, 1990. "Endogenous Regional Agricultural Production Technologies," 1990 Annual meeting, August 5-8, Vancouver, Canada 270879, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    3. Maira Caño- Guiral, 1995. "Competitividad y eficiencia técnica. Un modelo de datos panel para la industria láctea uruguaya," Documentos de Trabajo (working papers) 0795, Department of Economics - dECON.
    4. Griffiths, William E. & O'Donnell, Christopher J., 2005. "Estimating variable returns to scale production frontiers with alternative stochastic assumptions," Journal of Econometrics, Elsevier, vol. 126(2), pages 385-409, June.
    5. Al-Hadi, Azrina Abdullah & Bitzan, John & Peoples, James, 2019. "Input allocation efficiency in the United States railroad industry: Changing work rules and managerial flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 281-296.
    6. Jiro Nemoto & Mika Goto, 2006. "Measurement of technical and allocative efficiencies using a CES cost frontier: a benchmarking study of Japanese transmission-distribution electricity," Empirical Economics, Springer, vol. 31(1), pages 31-48, March.
    7. Rouven E. Haschka & Helmut Herwartz & Clara Silva Coelho & Yabibal M. Walle, 2023. "The impact of local financial development and corruption control on firm efficiency in Vietnam: evidence from a geoadditive stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 60(2), pages 203-226, October.
    8. Dhawan, Rajeev & Jochumzen, Peter, 1999. "Stochastic Frontier Production Function With Errors-In-Variables," Working Papers 1999:007, Lund University, Department of Economics.

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