### Abstract

Original language | English |
---|---|

Journal | Annals of Operations Research |

Volume | 211 |

Issue number | 1 |

Pages (from-to) | 37-48 |

Number of pages | 12 |

ISSN | 0254-5330 |

DOIs | |

Publication status | Published - Dec 2013 |

### Cite this

*Annals of Operations Research*,

*211*(1), 37-48. https://doi.org/10.1007/s10479-013-1438-9

}

*Annals of Operations Research*, vol. 211, no. 1, pp. 37-48. https://doi.org/10.1007/s10479-013-1438-9

**Do Efficiency Scores Depend on Input Mix? A Statistical Test and Empirical Illustration.** / Asmild, Mette; Hougaard, Jens Leth; Kronborg, Dorte.

Research output: Contribution to journal › Journal article › Research › peer-review

TY - JOUR

T1 - Do Efficiency Scores Depend on Input Mix?

T2 - A Statistical Test and Empirical Illustration

AU - Asmild, Mette

AU - Hougaard, Jens Leth

AU - Kronborg, Dorte

PY - 2013/12

Y1 - 2013/12

N2 - In this paper we examine the possibility of using the standard Kruskal-Wallis (KW) rank test in order to evaluate whether the distribution of efficiency scores resulting from Data Envelopment Analysis (DEA) is independent of the input (or output) mix of the observations. Since the DEA frontier is estimated, many standard assumptions for evaluating the KW test statistic are violated. Therefore, we propose to explore its statistical properties by the use of simulation studies. The simulations are performed conditional on the observed input mixes. The method, unlike existing approaches in the literature, is also applicable when comparing distributions of efficiency scores in more than two groups and does not rely on bootstrapping of, or questionable distributional assumptions about, the efficiency scores. The approach is illustrated using an empirical case of demolition projects. Since the assumption of mix independence is rejected the implication is that it, for example, is impossible to determine whether machine intensive project are more or less efficient than labor intensive projects.

AB - In this paper we examine the possibility of using the standard Kruskal-Wallis (KW) rank test in order to evaluate whether the distribution of efficiency scores resulting from Data Envelopment Analysis (DEA) is independent of the input (or output) mix of the observations. Since the DEA frontier is estimated, many standard assumptions for evaluating the KW test statistic are violated. Therefore, we propose to explore its statistical properties by the use of simulation studies. The simulations are performed conditional on the observed input mixes. The method, unlike existing approaches in the literature, is also applicable when comparing distributions of efficiency scores in more than two groups and does not rely on bootstrapping of, or questionable distributional assumptions about, the efficiency scores. The approach is illustrated using an empirical case of demolition projects. Since the assumption of mix independence is rejected the implication is that it, for example, is impossible to determine whether machine intensive project are more or less efficient than labor intensive projects.

KW - Data envelopment analysis (DEA)

KW - Homogeneous efficiencies

KW - Mix independence

KW - Kruskal-Wallis test

KW - Ranking

U2 - 10.1007/s10479-013-1438-9

DO - 10.1007/s10479-013-1438-9

M3 - Journal article

VL - 211

SP - 37

EP - 48

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 1

ER -