A fully nonparametric stochastic frontier model for panel data
(2005) , 23 pages
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- Authors
- Abstract
- In this paper we estimate the frontier and time variant technical efficiency fully nonparametrically by exploiting recent advances in kernel regression estimation of categorical data. Specifically, we model firm (unordered) and time (ordered) categorical variables directly into the conditional mean. This approach allows us to smooth the firm and time specific effects, which formally entered the model linearly. Our setup allows for more flexible and accurate estimates of the frontier and time variant technical efficiency. Further, the estimators are consistent and achieve the standard nonparametric rate of convergence. We apply these techniques to a data set examining labor efficiencies of 17 railway companies over a period of 14 years. Not only are our results for the elasticites more economically intuitive than theparametric and semiparametric procedures, we obtain different rankings in terms of labor efficiencies.
- Affiliations
State University of New York at Binghamton Department of economic
Citations
Henderson, D. J., & Simar, L. (2005). A fully nonparametric stochastic frontier model for panel data (STAT Discussion Paper 0525). https://hdl.handle.net/2078.5/32606