The wrong skewness problem in stochastic frontier models: A new approach
Hans Manner,
Christian Hafner and
Leopold Simar
VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy from Verein für Socialpolitik / German Economic Association
Abstract:
Stochastic frontier models are widely used to measure, e.g., technical efficiencies of firms. The classical stochastic frontier model often suffers from the empirical artefact that the residuals of the production function may have a positive skewness, whereas a negative one is expected under the model, which leads to estimated full efficiencies of all firms. We propose a new approach to the problem by generalizing the distribution used for the inefficiency variable. This generalized stochastic frontier model allows the sample data to have the wrong skewness while estimating well-defined and non-degenerate efficiency measures. We discuss the statistical properties of the model and we discuss a test for the symmetry of the error term (no inefficiency). We provide a simulation study to show that our model delivers estimators of efficiency with smaller bias than those of the classical model even if the population skewness has the correct sign. Finally, we apply the model to data of the U.S. textile industry for 1958-2005, and show that for a number of years our model suggests technical efficiencies well below the frontier, while the classical one estimates no inefficiency in those years.
JEL-codes: C13 C18 D24 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-ecm and nep-eff
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Citations: View citations in EconPapers (1)
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Related works:
Journal Article: The “wrong skewness” problem in stochastic frontier models: A new approach (2018) 
Working Paper: The "wrong skewness" problem in stochastic frontier models: A new approach (2018)
Working Paper: The “wrong skewness” problem in stochastic frontier models: a new approach (2015) 
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc15:112812
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