Quantile estimation of the stochastic frontier model

Samah Jradi, Christopher Parmeter, John Ruggiero

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The stochastic frontier model remains popular within the field of efficiency analysis and yet it remains deeply connected to the notion of a conditional mean. Recent research has attempted to conceive of, and estimate, the stochastic frontier model in a quantile setting. We demonstrate here that the stochastic frontier corresponds explicitly to a specific quantile of the output distribution and provide a computational approach to recover this quantile. An empirical illustration demonstrates comparable performance with more classical methods of estimation of the stochastic frontier model.

Original languageEnglish (US)
Pages (from-to)15-18
Number of pages4
JournalEconomics Letters
Volume182
DOIs
StatePublished - Sep 1 2019

Keywords

  • Efficiency
  • Quantile function
  • Skewed normal
  • True quantile

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

Fingerprint Dive into the research topics of 'Quantile estimation of the stochastic frontier model'. Together they form a unique fingerprint.

  • Cite this