Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models

@article{Simar1998SensitivityAO,
  title={Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models},
  author={L{\'e}opold Simar and Paul W. Wilson},
  journal={Management Science},
  year={1998},
  volume={44},
  pages={49-61}
}
Efficiency scores of production units are generally measured relative to an estimated pro-duction frontier. Nonparametric estimators (DEA, FDH,···) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data-generating process in this complex framework and to propose a… 

Figures and Tables from this paper

A NOTE ON THE CONVERGENCE OF NONPARAMETRIC DEA ESTIMATORS FOR PRODUCTION EFFICIENCY SCORES

Efficiency scores of production units are measured by their distance to an estimated production frontier. Nonparametric data envelopment analysis estimators are based on a finite sample of observed

Estimation of Cost Efficiency in Non-parametric Frontier Models

TLDR
A bootstrap methodology for robust estimation of cost efficiency in data envelopment analysis that re-samples "naive" input-oriented efficiency scores, rescales original inputs to bring them to the frontier, and then re-estimates cost efficiency scores for the rescaled inputs.

Asymptotics for DEA estimators in non-parametric frontier models

Non-parametric data envelopment analysis (DEA) estimators based on linear programming methods have been widely applied in analyses of productive efficiency. The distributions of these estimators

A general methodology for bootstrapping in non-parametric frontier models

TLDR
This paper proposes a general methodology for bootstrapping in frontier models, extending the more restrictive method proposed in Simar & Wilson (1998) by allowing for heterogeneity in the structure of efficiency.

ASYMPTOTICS AND CONSISTENT BOOTSTRAPS FOR DEA ESTIMATORS IN NONPARAMETRIC FRONTIER MODELS

Nonparametric data envelopment analysis (DEA) estimators based on linear programming methods have been widely applied in analyses of productive efficiency. The distributions of these estimators

A comparison of parametric and nonparametric estimation methods for cost frontiers and economic measures

ABSTRACT This article examines the empirical performance of alternative frontier estimators’ ability to replicate a known underlying technology and economic measures such as multi-product and

Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data

This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main

Statistical Inference in Nonparametric Frontier Models: The State of the Art

Efficiency scores of firms are measured by their distance to an estimated production frontier. The economic literature proposes several nonparametric frontier estimators based on the idea of

A multi-parametric method for bias correction of DEA efficiency estimators

TLDR
A non-resampling multi-parametric method to deal with the sensitivity of DEA estimators is provided and it is shown that the new method’s estimations provide a better fit to the population than the estimations of the standard and smoothed bootstrap.

A Bootstrap-Regression Procedure to Capture Unit Specific Effects in Data Envelopment Analysis

The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to
...

References

SHOWING 1-10 OF 28 REFERENCES

Estimating efficiencies from frontier models with panel data: A comparison of parametric, non-parametric and semi-parametric methods with bootstrapping

The aim of this article is first to review how the standard econometric methods for panel data may be adapted to the problem of estimating frontier models and (in)efficiencies. The aim is to clarify

Iterated bootstrap with applications to frontier models

The iterated bootstrap may be used to estimate errors which arise from a single pass of the bootstrap and thereby to correct for them. Here the iteration is employed to correct for coverage

A general framework for frontier estimation with panel data

The main objective of the paper is to present a general framework for estimating production frontier models with panel data. A sample of firms i = 1, ..., N is observed on several time periods t = 1,

Aspects of statistical analysis in DEA-type frontier models

TLDR
This paper focuses on the basic characteristics of DEA models from a statistical point of view and some trails are proposed for introducing stochastic noise in DEA models, in the spirit of the Kneip-Simar (1995) approach.

Hypothesis tests using data envelopment analysis

A substantial body of recent work has opened the way to exploring the statistical properties of DEA estimators of production frontiers and related efficiency measures. The purpose of this paper is to

Measuring the efficiency of decision making units

On Farrell Measures of Technical Efficiency

In this paper we consider the problem of evaluating the performance of production units in terms of their technical efficiency. Several attempts have been made to solve this problem and a number of

The bootstrap: To smooth or not to smooth?

SUMMARY The bootstrap and smoothed bootstrap are considered as alternative methods of estimating properties of unknown distributions such as the sampling error of parameter estimates. Criteria are

The Role of the Reference Technology in Measuring Productive Efficiency

After a twenty year lull, the measurement of productive efficiency is enjoying a revival. In particular, the index of efficiency developed by Debreu (I95i) and later utilised by Farrell (I957) has