A penalization approach for estimating inefficiency in stochastic frontier panel models

Firmin Doko Tchatoka, Magnus Söderberg and Mohammad Abbas Hakeem ()
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Mohammad Abbas Hakeem: The University of Adelaide
Authors registered in the RePEc Author Service: Mark Weder

School of Economics and Public Policy Working Papers from University of Adelaide, School of Economics and Public Policy

Abstract: Efficiency analysis is crucial for evaluating the performance of entities that provide essential and other homogenized services. The Jondow et al.’s (1982) estimator is widely used but has been criticized for biasing inefficiency toward its mean, distorting the distribution, and misrepresenting the conditional distribution of inefficiency, particularly in cross-sectional settings. Zeebari et al. (2023) propose a regularization approach that aligns sample and theoretical moments but it is primarily suited to cross-sectional data. This paper introduces a penalized mode estimator for unit inefficiency in panel data, accounting for heteroskedasticity in both inefficiency and idiosyncratic errors. A closed-form expression for this estimator is derived, and Monte Carlo simulations demonstrate its superior performance compared to existing methods. An empirical study of electricity providers in Australia, Canada, and New Zealand further underscores its advantages.

Keywords: Inefficiency; JLMS estimator; Heteroskedasticity; Restricted mode estimator (search for similar items in EconPapers)
Date: 2025-02
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