One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels |
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Authors: | Wang Hung-jen Schmidt Peter |
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Institution: | (1) Academia Sinica, Institute of Economics, Taipei, 115, Taiwan;(2) Department of Economics, Michigan State University, East Lansing, MI 48824, USA |
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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. |
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Keywords: | technical efficiency stochastic frontiers |
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