Maximum simulated likelihood estimation of the seemingly unrelated stochastic frontier regressions

Hung-pin Lai

Empirical Economics, 2021, vol. 60, issue 6, No 11, 2943-2968

Abstract: Abstract In this paper, we use the maximum simulated likelihood (MSL) approach to estimate multiple stochastic frontier (SF) models with random effects and correlated composite errors. We show that the separate estimation of the single equation ignores the correlation between the composite errors and causes significant efficiency loss in estimation. In addition to using Monte Carlo simulation to investigate the finite sample performance of the simulated estimator, we demonstrate the usefulness of our approach in estimating the technical efficiency of Taiwan’s international hotels based on their accommodation and restaurant divisions.

Keywords: Maximum likelihood estimation; Copula; Seemingly unrelated stochastic frontier regressions; Random effects (search for similar items in EconPapers)
JEL-codes: C3 C5 R3 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00181-020-01962-9

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