Non-parametric tests of productive efficiency with errors-in-variables

被引：12

作者：

Kuosmanen, Timo

Post, Thierry

Scholtes, Stefan

机构：

[1] Univ Wageningen & Res Ctr, Environm Econ & Nat Resources Grp, NL-6700 EW Wageningen, Netherlands

[2] Erasmus Univ, Rotterdam Sch Econ, NL-3000 DR Rotterdam, Netherlands

[3] Erasmus Univ, ERIM, NL-3000 DR Rotterdam, Netherlands

[4] Univ Cambridge, Judge Business Sch, Cambridge CB2 1AG, England

来源：

JOURNAL OF ECONOMETRICS | 2007年 / 136卷 / 01期

关键词：

non-parametric production analysis; data envelopment analysis (DEA); errors-in-variables; hypothesis testing; extreme value theory; DATA ENVELOPMENT ANALYSIS; FRONTIER MODELS; ADDITIVE-MODEL; DEA; SENSITIVITY; ROBUSTNESS;

D O I：

10.1016/j.jeconom.2005.08.003

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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-infinity 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. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：131 / 162

页数：32

共 45 条

[21] THE MEASUREMENT OF PRODUCTIVE EFFICIENCY [J].