Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity

Jianhua Zhou, Christopher F. Parmeter, Subal C. Kumbhakar

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the application of the profile least-squares method to estimate the impact of the determinants of inefficiency in the presence of panel data and unobserved individual specific heterogeneity for the stochastic frontier model. This method has the advantage over previous approaches in that the effect of the determinants of inefficiency on output can be recovered nonparametrically in the presence of heterogeneity at the firm level. We describe the estimator and offer a small set of Monte Carlo exercises that showcases the value of the method for the stochastic frontier model. Application of the method to assess insights generated compared to a pooled cross-section approach using data from the Taiwan banking system is also provided.

Original languageEnglish (US)
Pages (from-to)1142-1152
Number of pages11
JournalEuropean Journal of Operational Research
Volume286
Issue number3
DOIs
StatePublished - Nov 1 2020

Keywords

  • Bandwidth
  • Heteroskedasticity
  • Kernel
  • Partly linear

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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