Interpreting and testing the scaling property in models where inefficiency depends on firm characteristics
In this paper, we are interested in a stochastic frontier model in which observable characteristics of the firms affect their levels of technical inefficiency. Let u â‰¥ 0 be the one-sided error reflecting technical inefficiency, and let z be a set of variables that affect u. We write u as u(z,Î´) to reflect its dependence on z and some parameters Î´. Various models in the existing literature specify the distribution of u(z,Î´). We are interested in models that satisfy the scaling property, which says that u(z,Î´) can be written as a scaling function h(z, Î´) times a random variable u* that does not depend on z. This property implies that changes in z affect the scale but not the shape of u(z,Î´). This paper reviews the existing literature and identifies models that do and do not have the scaling property. It also discusses practical advantages of the scaling property. The scaling property is argued to be intuitively appealing; it allows estimation by nonlinear least squares; it allows a distribution-free interpretation of the parameters Î´ that show how z affects inefficiency; and it underlies the model of Battese and Coelli, Journal of Productivity Analysis, 1992, which is currently the only model to allow correlation over time when inefficiency depends on firm characteristics. The paper shows how to test the hypothesis of scaling, and other interesting hypotheses, in the context of the model of Wang, Journal of Productivity Analysis, 2002. Finally, two empirical examples are given.
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- Han, Chirok & Orea, Luis & Schmidt, Peter, 2005.
"Estimation of a panel data model with parametric temporal variation in individual effects,"
Journal of Econometrics,
Elsevier, vol. 126(2), pages 241-267, June.
- Han, Chirok & Orea, Luis & Schmidt, Peter, 2002. "Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects," Efficiency Series Papers 2002/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
- Peter Schmidt & Chirok Han & Luis Orea, 2004. "Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects," Econometric Society 2004 Far Eastern Meetings 519, Econometric Society.
- Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
- Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
- Tom Doan, "undated". "TAR: RATS procedure to estimate a threshold autoregression, tests for threshold effect," Statistical Software Components RTS00209, Boston College Department of Economics.
- Tom Doan, "undated". "RATS programs to replicate Hansen's threshold estimation and testing results," Statistical Software Components RTZ00091, Boston College Department of Economics.
- Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
- Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
- Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
- 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.
- 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.
- Wang, Hung-Jen, 2003. "A Stochastic Frontier Analysis of Financing Constraints on Investment: The Case of Financial Liberalization in Taiwan," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 406-419, July.
- Cuesta, Rafael A. & Orea, Luis, 2002. "Mergers and technical efficiency in Spanish savings banks: A stochastic distance function approach," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2231-2247.
- Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
- Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
- 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.
- Wang, Hung-Jen, 2002. "Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model," MPRA Paper 31076, University Library of Munich, Germany.
- Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
- 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.
- 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.
- 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. Full references (including those not matched with items on IDEAS)
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