Expected Efficiency Ranks from Parametric Stochastic Frontier Models

Author(s)/Creator(s)

William C. Horrace, Syracuse UniversityFollow
Seth Richards-Shubik, Carnegie Mellon University

Description/Abstract

In the stochastic frontier model we extend the multivariate probability statements of Horrace (2005) to calculate the conditional probability that a firm is any particular efficiency rank in the sample. From this we construct the conditional expected efficiency rank for each firm. Compared to the traditional ranked efficiency point estimates, firm-level conditional expected ranks are more informative about the degree of uncertainty of the ranking. The conditional expect ranks may be useful for empiricists. A Monte Carlo study and an empirical example are provided.

Document Type

Working Paper

Date

2-2013

Keywords

Efficiency estimation, Order statistics, Multivariate inference, Multiplicity

Language

English

Series

Working Papers Series

Disciplines

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

ISSN

1525-3066

Additional Information

Working paper no.153

Recommended Citation

Horrace, William C. and Richards-Shubik, Seth, "Expected Efficiency Ranks from Parametric Stochastic Frontier Models" (2013). Center for Policy Research. 394.
https://surface.syr.edu/cpr/394

Source

Local input

Creative Commons License

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