A zero inefficiency stochastic frontier model
Traditional stochastic frontier models impose inefficient behavior on all firms in the sample of interest. If the data under investigation represent a mixture of both fully efficient and inefficient firms then off-the-shelf frontier models are statistically inadequate. We introduce the zero inefficiency stochastic frontier model which can accommodate the presence of both efficient and inefficient firms in the sample. We derive the corresponding log-likelihood function, conditional mean of inefficiency, to estimate observation-specific inefficiency and discuss testing for the presence of fully efficient firms. We provide both simulated evidence as well as an empirical example which demonstrates the applicability of the proposed method.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
- Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June.
- Thomas Bauer & Silja Göhlmann & Mathias Sinning, 2007.
"Gender differences in smoking behavior,"
John Wiley & Sons, Ltd., vol. 16(9), pages 895-909.
- Bauer, Thomas & Göhlmann, Silja & Sinning, Mathias, 2006. "Gender Differences in Smoking Behaviour," CEPR Discussion Papers 5848, C.E.P.R. Discussion Papers.
- Bauer, Thomas K. & Göhlmann, Silja & Sinning, Mathias, 2006. "Gender Differences in Smoking Behavior," RWI Discussion Papers 44, RWI - Leibniz-Institut für Wirtschaftsforschung.
- Bauer, Thomas K. & Göhlmann, Silja & Sinning, Mathias, 2006. "Gender Differences in Smoking Behavior," IZA Discussion Papers 2259, Institute for the Study of Labor (IZA).
- Thomas Bauer & Silja Göhlmann & Mathias Sinning, 2006. "Gender Differences in Smoking Behavior," Health, Econometrics and Data Group (HEDG) Working Papers 06/07, HEDG, c/o Department of Economics, University of York.
- Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
- Kaparakis, Emmanuel I & Miller, Stephen M & Noulas, Athanasios G, 1994. "Short-Run Cost Inefficiency of Commercial Banks: A Flexible Stochastic Frontier Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(4), pages 875-893, November.
- William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
- Gurmu, Shiferaw & Trivedi, Pravin K, 1996. "Excess Zeros in Count Models for Recreational Trips," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 469-477, October.
- Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
- 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.
- Lee, Lung-Fei, 1993. "Asymptotic Distribution of the Maximum Likelihood Estimator for a Stochastic Frontier Function Model with a Singular Information Matrix," Econometric Theory, Cambridge University Press, vol. 9(03), pages 413-430, June.
- Lee, L.F., 1992. "Asymptotic Distribution of the Maximum Likelihood Estimator for Stochastic Frontier Function Model with a Singular Information Matrix," Papers 92-01, Michigan - Center for Research on Economic & Social Theory.
- Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
- Donald W.K. Andrews, 1999. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Cowles Foundation Discussion Papers 1229, Cowles Foundation for Research in Economics, Yale University.
- Yong Chen & Kung-Yee Liang, 2010. "On the asymptotic behaviour of the pseudolikelihood ratio test statistic with boundary problems," Biometrika, Biometrika Trust, vol. 97(3), pages 603-620.
- Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
- 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.
- 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.
- Bos, J.W.B. & Economidou, C. & Koetter, M., 2010. "Technology clubs, R&D and growth patterns: Evidence from EU manufacturing," European Economic Review, Elsevier, vol. 54(1), pages 60-79, January.
- Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
- Harris, Mark N. & Zhao, Xueyan, 2007. "A zero-inflated ordered probit model, with an application to modelling tobacco consumption," Journal of Econometrics, Elsevier, vol. 141(2), pages 1073-1099, December. Full references (including those not matched with items on IDEAS)