Testing over-representation of observations in subsets of a DEA technology

TY - JOUR

T1 - Testing over-representation of observations in subsets of a DEA technology

AU - Asmild, Mette

AU - Hougaard, Jens Leth

AU - Olesen, Ole Bent

PY - 2013/10/1

Y1 - 2013/10/1

N2 - This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and provides good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space. Potential applications include tests for whether benchmark units dominate more (or less) observations than expected.

AB - This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and provides good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space. Potential applications include tests for whether benchmark units dominate more (or less) observations than expected.

U2 - 10.1016/j.ejor.2013.03.038

DO - 10.1016/j.ejor.2013.03.038

M3 - Journal article

SN - 0377-2217

VL - 230

SP - 88

EP - 96

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 1

ER -