Stationary Points for Parametric Stochastic Frontier Models

William C. Horrace, Ian A. Wright

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Stationary point results on the normal–half-normal stochastic frontier model are generalized using the theory of the Dirac delta, and distribution-free conditions are established to ensure a stationary point in the likelihood as the variance of the inefficiency distribution goes to zero. Stability of the stationary point and “wrong skew” results are derived or simulated for common parametric assumptions on the model. We discuss identification and extensions to more general stochastic frontier models.

Original languageEnglish (US)
Pages (from-to)516-526
Number of pages11
JournalJournal of Business and Economic Statistics
Volume38
Issue number3
DOIs
StatePublished - Jul 2 2020

Keywords

  • Dirac delta
  • Generalized function
  • Inefficiency estimation
  • Ordinary least squares
  • Singular distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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