Estimation and inference in two-stage,semi-parametric models of production processes |
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Authors: | Léopold Simar Paul W Wilson |
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Institution: | 1. Institut de Statistique, Université Catholique de Louvain, Voie du Roman Pays 20, Louvain-la-Neuve, Belgium;2. Department of Economics, University of Texas, Austin, TX 78712, USA |
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Abstract: | 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. |
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Keywords: | C1 C44 C61 |
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