The “wrong skewness” problem in stochastic frontier models: a new approach
Christian Hafner (),
H. Manner and
Leopold Simar ()
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H. Manner: University of Cologne
No 2015014, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
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 generaliz- ing 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.
Keywords: Stochastic frontier model; production efficiency; skewness; testing symmetry preferences (search for similar items in EconPapers)
JEL-codes: C13 C18 D24 (search for similar items in EconPapers)
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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:cor:louvco:2015014
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