One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels

Hung-Jen Wang () and Peter Schmidt

MPRA Paper from University Library of Munich, Germany

Abstract: Consider a stochastic frontier model with one-sided inefficiency u, and suppose that the scale of u depends on some variables (firm characteristics) z. A one-step model specifies both the stochastic frontier and the way in which u depends on z, and can be estimated in a single step, for example by maximum likelihood. This is in contrast to a two-step procedure, where the first step is to estimate a standard stochastic frontier model, and the second step is to estimate the relationship between (estimated) u and z. In this paper we propose a class of one-step models based on the scaling property that u equals a function of z times a one-sided error u * whose distribution does not depend on z. We explain theoretically why two-step procedures are biased, and we present Monte Carlo evidence showing that the bias can be very severe. This evidence argues strongly for one-step models whenever one is interested in the effects of firm characteristics on efficiency levels.

Keywords: technical efficiency; stochastic frontiers (search for similar items in EconPapers)
JEL-codes: C51 C52 D24 (search for similar items in EconPapers)
Date: 2001-10, Revised 2002-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (482)

Published in Journal of Productivity Analysis 18.2(2002): pp. 129-144

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Related works:
Journal Article: One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:31075

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