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Dealing with the Endogeneity Problem in Data Envelopment Analysis

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  • Cordero, José Manuel
  • Santín, Daniel
  • Sicilia, Gabriela

Abstract

Endogeneity, and the distortions on the estimation of economic models that it causes, is a familiar problem in the econometrics literature. Although non-parametric methods like data envelopment analysis (DEA) are among the most used techniques for measuring technical efficiency, the effects of endogeneity on such efficiency estimates have received little attention. The aim of this paper is twofold. First, we further illustrate the endogeneity problem and its causes in production processes like the correlation between one input and the efficiency level. Second, we use synthetic data generated in a Monte Carlo experiment to analyze how different levels of positive and negative endogeneity can impair DEA estimations. We conclude that although DEA is robust to negative endogeneity, a high positive endogeneity level, i.e., a high positive correlation between one input and the true efficiency level, significantly and severely biases DEA performance.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 47475.

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Date of creation: Apr 2013
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Handle: RePEc:pra:mprapa:47475

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Keywords: Technical efficiency; DEA; Endogeneity; Monte Carlo.;

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References

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Cited by:
  1. KONISHI Yoko & NISHIMURA Yoshihiko, 2013. "A Note on the Identification of Demand and Supply Shocks in Production: Decomposition of TFP," Discussion papers 13099, Research Institute of Economy, Trade and Industry (RIETI).

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