Estimation and inference in two-stage, semi-parametric models of production processes. (English) Zbl 1418.62535

Summary: Many papers have regressed non-parametric estimates of productive efficiency on environmental variables in two-stage procedures to account for exogenous factors that might affect firms’ performance. None of these have described a coherent data-generating process (DGP). Moreover, conventional approaches to inference employed in these papers are invalid due to complicated, unknown serial correlation among the estimated efficiencies. We first describe a sensible DGP for such models. We propose single and double bootstrap procedures; both permit valid inference, and the double bootstrap procedure improves statistical efficiency in the second-stage regression. We examine the statistical performance of our estimators using Monte Carlo experiments.


62P20 Applications of statistics to economics
91B38 Production theory, theory of the firm
90B50 Management decision making, including multiple objectives


bootstrap; FRONTIER
Full Text: DOI


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