Stochastic Frontier Model, Skewness, MLE, Constrained Estimators, BIC
Nanyang Technological University
Working Papers Series
Economic Policy | Economics | Public Affairs, Public Policy and Public Administration
In parametric stochastic frontier models, the composed error is specified as the sum of a two-sided noise component and a one-sided inefficiency component, which is usually assumed to be half-normal, implying that the error distribution is skewed in one direction. In practice, however, estimation residuals may display skewness in the wrong direction. Model re-specification or pulling a new sample is often prescribed. Since wrong skewness is considered a finite sample problem, this paper proposes a finite sample adjustment to existing estimators to obtain the desired direction of residual skewness. This provides another empirical approach to dealing with the so-called wrong skewness problem.
Feng, Qu; Horrace, William C.; and Wu, Guiying Laura, "Wrong Skewness and Finite Sample Correction" (2015). Center for Policy Research. 389.
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