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Interpreting and testing the scaling property in models where inefficiency depends on firm characteristics

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Author Info
Peter Schmidt
Antonio Alvarez
Christine Amsler

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Abstract

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 ≥ 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,δ) to reflect its dependence on z and some parameters δ. Various models in the existing literature specify the distribution of u(z,δ). We are interested in models that satisfy the scaling property, which says that u(z,δ) can be written as a scaling function h(z, δ) 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,δ). 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 δ 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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Publisher Info
Paper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 520.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:feam04:520

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Related research
Keywords: stochastic frontier; scaling property; technical inefficiency;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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  1. Tiziana Laureti, 2008. "Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier," International Advances in Economic Research, Springer, vol. 14(1), pages 76-89, February. [Downloadable!] (restricted)
  2. Meike Wollni & Bernhard Brümmer, 2009. "Productive efficiency of specialty and conventional coffee farmers in Costa Rica: Accounting for technological heterogeneity and self-selection," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 13, Courant Research Centre PEG. [Downloadable!]
  3. Liu, Yanyan, 2006. "Model Selection in Stochastic Frontier Analysis: Maize Production in Kenya," 2006 Annual meeting, July 23-26, Long Beach, CA 21281, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). [Downloadable!]
  4. Yanyan Liu & Robert Myers, 2009. "Model selection in stochastic frontier analysis with an application to maize production in Kenya," Journal of Productivity Analysis, Springer, vol. 31(1), pages 33-46, February. [Downloadable!] (restricted)
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