Dealing with the Endogeneity Problem in Data Envelopment Analysis
AbstractEndogeneity, 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 InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 47475.
Date of creation: Apr 2013
Date of revision:
Technical efficiency; DEA; Endogeneity; Monte Carlo.;
Find related papers by JEL classification:
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-16 (All new papers)
- NEP-ECM-2013-06-16 (Econometrics)
- NEP-EFF-2013-06-16 (Efficiency & Productivity)
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- William Greene, 2010.
"A stochastic frontier model with correction for sample selection,"
Journal of Productivity Analysis,
Springer, vol. 34(1), pages 15-24, August.
- William Greene, 2008. "A Stochastic Frontier Model with Correction for Sample Selection," Working Papers 08-9, New York University, Leonard N. Stern School of Business, Department of Economics.
- Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.
- Boris Bravo-Ureta & William Greene & Daniel Solís, 2012. "Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project," Empirical Economics, Springer, vol. 43(1), pages 55-72, August.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
- Schlotter, Martin & Schwerdt, Guido & Wößmann, Ludger, 2011.
"Econometric methods for causal evaluation of education policies and practices: A non-technical guide,"
Munich Reprints in Economics
19780, University of Munich, Department of Economics.
- Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
- Schlotter, Martin & Schwerdt, Guido & Woessmann, Ludger, 2010. "Econometric Methods for Causal Evaluation of Education Policies and Practices: A Non-Technical Guide," IZA Discussion Papers 4725, Institute for the Study of Labor (IZA).
- Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2009. "Econometric Methods for Causal Evaluation of Education Policies and Practices: A Non-Technical Guide," CESifo Working Paper Series 2877, CESifo Group Munich.
- Ruggiero, John, 2003. "Comment on estimating school efficiency," Economics of Education Review, Elsevier, vol. 22(6), pages 631-634, December.
- Ruggiero, John, 2004. "Performance evaluation when non-discretionary factors correlate with technical efficiency," European Journal of Operational Research, Elsevier, vol. 159(1), pages 250-257, November.
- Rosalind Levacic & Anna Vignoles, 2002. "Researching the Links between School Resources and Student Outcomes in the UK: A Review of Issues and Evidence," Education Economics, Taylor & Francis Journals, vol. 10(3), pages 313-331.
- Bifulco, Robert & Bretschneider, Stuart, 2003. "Response to comment on estimating school efficiency," Economics of Education Review, Elsevier, vol. 22(6), pages 635-638, December.
- Sergio Perelman & Daniel Santin, 2011.
"Measuring educational efficiency at student level with parametric stochastic distance functions: an application to Spanish PISA results,"
Taylor & Francis Journals, vol. 19(1), pages 29-49.
- Sergio Perelman & Daniel Santin, 2005. "Measuring educational efficiency at student level with parametric stochastic distance functions: An application to Spanish PISA results," CREPP Working Papers 0504, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
- Daniel Solís & Boris E. Bravo-Ureta & Ricardo E. Quiroga, 2007. "Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(4), pages 491-510, December.
- John Ruggiero, 2005. "Impact Assessment Of Input Omission On Dea," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 359-368.
- Carlos D. Mayen & Joseph V. Balagtas & Corinne E. Alexander, 2010. "Technology Adoption and Technical Efficiency: Organic and Conventional Dairy Farms in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 181-195.
- repec:zwi:journl:v:43:y:2012:i:1:p:55-72 is not listed on IDEAS
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Hédi Essid & Pierre Ouellette & Stéphane Vigeant, 2013. "Small is not that beautiful after all: measuring the scale efficiency of Tunisian high schools using a DEA-bootstrap method," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1109-1120, March.
- Bifulco, Robert & Bretschneider, Stuart, 2001. "Estimating school efficiency: A comparison of methods using simulated data," Economics of Education Review, Elsevier, vol. 20(5), pages 417-429, October.
- 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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