LASSO for Stochastic Frontier Models with Many Efficient Firms

Research output: Contribution to journalArticlepeer-review

Abstract

We apply the adaptive LASSO to select a set of maximally efficient firms in the panel fixed-effect stochastic frontier model. The adaptively weighted L 1 penalty with sign restrictions allows simultaneous selection of a group of maximally efficient firms and estimation of firm-level inefficiency parameters with a faster rate of convergence than least squares dummy variable estimators. Our estimator possesses the oracle property. We propose a tuning parameter selection criterion and an efficient optimization algorithm based on coordinate descent. We apply the method to estimate a group of efficient police officers who are best at detecting contraband in motor vehicle stops (i.e., search efficiency) in Syracuse, NY.

Original languageEnglish (US)
JournalJournal of Business and Economic Statistics
DOIs
StateAccepted/In press - 2022

Keywords

  • Adaptive LASSO
  • Fixed-effect stochastic frontier model
  • L1 regularization
  • Panel data
  • Sign restriction
  • Zero inefficiency

ASJC Scopus subject areas

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

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