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Ramalho, E. A., Ramalho, J. J. S. & Henriques, P. D. (2010). Fractional regression models for second stage DEA efficiency analyses. Journal of Productivity Analysis. 34 (3), 239-255
E. A. Ramalho et al., "Fractional regression models for second stage DEA efficiency analyses", in Journal of Productivity Analysis, vol. 34, no. 3, pp. 239-255, 2010
@article{ramalho2010_1734880698545, author = "Ramalho, E. A. and Ramalho, J. J. S. and Henriques, P. D.", title = "Fractional regression models for second stage DEA efficiency analyses", journal = "Journal of Productivity Analysis", year = "2010", volume = "34", number = "3", doi = "10.1007/s11123-010-0184-0", pages = "239-255", url = "http://link.springer.com/article/10.1007%2Fs11123-010-0184-0" }
TY - JOUR TI - Fractional regression models for second stage DEA efficiency analyses T2 - Journal of Productivity Analysis VL - 34 IS - 3 AU - Ramalho, E. A. AU - Ramalho, J. J. S. AU - Henriques, P. D. PY - 2010 SP - 239-255 SN - 0895-562X DO - 10.1007/s11123-010-0184-0 UR - http://link.springer.com/article/10.1007%2Fs11123-010-0184-0 AB - Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models is the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed. ER -