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 L8 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.v2007o
This paper tests the farm level profit maximization hypothesis using a nonparametric production anal...
It is well-known that Type I or Type II error control in parametric statistical inference is related...
AbstractThe purpose of the paper is to point to usability of data envelopment analysis (DEA) for tec...
We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, fol...
We develop a nonparametric test of productive efficiency that accounts for thepossibility of errors-...
textabstractThis paper develops a novel statistic for firm efficiency called efficiency depth that a...
This paper discusses statistical procedures for testing various restrictions in the context of nonpa...
textabstractWe consider the issues of noise-to-signal estimation, finite sample performance and hypo...
We propose procedures for testing statistically the significance of violations of nonparametric test...
This paper develops a new nonparametric model for efficiency estimation. In contrast to Data Envelop...
We consider how one might test observed choice data for consistency with optimizing models in the pr...
A rich literature on the analysis of efficiency in production has developed since pi- oneering work ...
This paper tests the farm level profit maximization hypothesis using a nonparametric production anal...
This paper demonstrates that standard central limit theorem (CLT) results do not hold for means of n...
This paper discusses various statistics for testing hypotheses regarding returns to scale in the con...
This paper tests the farm level profit maximization hypothesis using a nonparametric production anal...
It is well-known that Type I or Type II error control in parametric statistical inference is related...
AbstractThe purpose of the paper is to point to usability of data envelopment analysis (DEA) for tec...
We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, fol...
We develop a nonparametric test of productive efficiency that accounts for thepossibility of errors-...
textabstractThis paper develops a novel statistic for firm efficiency called efficiency depth that a...
This paper discusses statistical procedures for testing various restrictions in the context of nonpa...
textabstractWe consider the issues of noise-to-signal estimation, finite sample performance and hypo...
We propose procedures for testing statistically the significance of violations of nonparametric test...
This paper develops a new nonparametric model for efficiency estimation. In contrast to Data Envelop...
We consider how one might test observed choice data for consistency with optimizing models in the pr...
A rich literature on the analysis of efficiency in production has developed since pi- oneering work ...
This paper tests the farm level profit maximization hypothesis using a nonparametric production anal...
This paper demonstrates that standard central limit theorem (CLT) results do not hold for means of n...
This paper discusses various statistics for testing hypotheses regarding returns to scale in the con...
This paper tests the farm level profit maximization hypothesis using a nonparametric production anal...
It is well-known that Type I or Type II error control in parametric statistical inference is related...
AbstractThe purpose of the paper is to point to usability of data envelopment analysis (DEA) for tec...