Non-Parametric Tests of Productive Efficiency with Errors-in-Variables
We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, following the approach of Varian. [1985. Nonparametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30(1/2), 445–458]. The test is based on the general Pareto–Koopmans notion of efficiency, and does not require price data. Statistical inference is based on the sampling distribution of the L∞ norm of errors. The test statistic can be computed using a simple enumeration algorithm. The finite sample properties of the test are analyzed by means of a Monte Carlo simulation using real-world data of large EU commercial banks.
|Keywords||data envelopment analysis (DEA), errors-in-variables, extreme value theory, hypothesis testing, non-parametric production analysis|
|Persistent URL||dx.doi.org/10.1016/j.jeconom.2005.08.003, hdl.handle.net/1765/14062|
Kuosmanen, T., Post, G.T., & Scholtes, S.. (2007). Non-Parametric Tests of Productive Efficiency with Errors-in-Variables. Journal of Econometrics, 136(1), 131–162. doi:10.1016/j.jeconom.2005.08.003