LASSO for Stochastic Frontier Models with Many Efficient Firms

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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)
Pages (from-to)1132-1142
Number of pages11
JournalJournal of Business and Economic Statistics
Issue number4
StatePublished - 2023


  • 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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