Wrong Skewness and Finite Sample Correction

Author(s)/Creator(s)

Qu Feng, Nanyang Technological University, SingaporeFollow
William C. Horrace, Syracuse UniversityFollow
Guiying Laura Wu, Nanyang Technological University, SingaporeFollow

Description/Abstract

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.

Document Type

Working Paper

Date

10-2015

Keywords

Stochastic Frontier Model, Skewness, MLE, Constrained Estimators, BIC

Language

English

Funder(s)

Nanyang Technological University

Series

Working Papers Series

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

ISSN

1252-3066

Additional Information

working paper no. 154

Recommended Citation

Feng, Qu; Horrace, William C.; and Wu, Guiying Laura, "Wrong Skewness and Finite Sample Correction" (2015). Center for Policy Research. 389.
https://surface.syr.edu/cpr/389

Source

Local input

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.