Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models

• 成果类型: Article
• 署名作者: Simar, L; Wilson, PW
• 署名单位: Universite Catholique Louvain; University of Texas System; University of Texas Austin
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.44.1.49
• 发表日期: 1998
• 页码: 49-61
• 关键词: data envelopment analysis; bootstrap; resampling methods; frontier efficiency models

摘要

Efficiency scores of production units are generally measured relative to an estimated production 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 reasonable estimator of it. This paper provides a general methodology of bootstrapping in nonparametric frontier models. Some adapted methods are illustrated in analyzing the bootstrap sampling variations of input efficiency measures of electricity plants.