Parametric measurement of time-varying technical inefficiency: results from competing models.

Abstract

Abstract This paper provides an empirical comparison of time-varying technical inefficiency measures obtained from the econometric estimation of different specifications of the stochastic production frontier model. Specifically, ten different frontier model specifications, which are most widely used in empirical applications, are estimated using a balanced panel data set from the Greek olive-oil sector, consisting of 100 farms observed during 1987-93 period. The empirical results indicate that both the magnitude and individual ranking of technical efficiency estimates differs considerably across models. (ProQuest: ... denotes formulae omitted.) Introduction The use of panel data, repeated observations on each production unit, considerably enrich the econometric analysis of stochastic production frontier models and have several potential advantages over simple cross-section data. First, it offers a more efficient econometric estimation of the production frontier model.1 Second, it provides consistent estimators of firm inefficiency, as long as the time dimension of the data set is sufficiently large.2 Third, it removes the necessity to make specific distributional assumptions regarding the one-sided error term associated with technical inefficiencies in the sample.3 Fourth, it does not require inefficiency to be independent of the regressors included in the production frontier.4 Fifth, it permits the simultaneous identification of both technical change and time-varying technical inefficiency, establishing thus a clear link between technical change, technical efficiency and productivity.5 Since the very first detailed discussion of efficiency measurement within the context of panel data (i.e., Pitt and Lee, 1981; Schmidt and Sickles, 1984), several alternative models have been progressively developed extending the existing methodological framework to account for different theoretical issues in empirical frontier modeling. In empirical applications there has been no clear preference for one of the several alternative model specifications since no one has an absolute advantage over the others. Moreover, the choice among them is further complicated by the fact that, in general, they are not nested to each other which implies that there are no statistical criteria to discriminate among them.6 Hence, the choice for the appropriate model of pooling is based on a priori grounds related with the particular objectives of each empirical application or with data availability as well as the underlying hypotheses for each production frontier model. However, empirical evidence suggests that the economic optima, including efficiency, are sensitive to the choice of the estimation technique. It is evident, therefore, that all these necessitate considering the comparative performance of these models in real world applications. In the empirical literature on frontier modeling with panel data, the issues of model specification and selection of estimation technique have not been explored in detail. The objective of this paper is to contribute in the existing literature providing a more comprehensive comparison of the most widely applied model specifications used to measure output-oriented time-varying technical inefficiency with panel data. The paper explores the sensitivity of obtained technical inefficiency estimates to the choice of the model of pooling, while maintaining an identical data set and retaining the same assumptions about the underlying production technology. In particular ten of the most widely applied frontier models are estimated and compared using a balanced panel data set from the Greek agricultural sector consisting of 100 olive-growing farms observed over the 1987-93 period. The rest of the paper is organized as follows: In the next section a brief review of studies on the effect of the choice for the model of pooling on efficiency measurement is presented. Section 3 provides a brief review of alternative model specifications used to measure time-varying technical inefficiency with panel data. …