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Using least squares and tobit in second stage DEA efficiency analyses

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  • McDonald, John

Abstract

The paper examines second stage DEA efficiency analyses, within the context of a censoring data generating process (DGP) and a fractional data DGP, when efficiency scores are treated as descriptive measures of the relative performance of units in the sample. It is argued that the efficiency scores are not generated by a censoring process but are fractional data. Tobit estimation in this situation is inappropriate. In contrast, ordinary least squares is a consistent estimator, and, if White's [White, H., 1980. A heteroskedastic-consistent covariance matrix and a direct test for heteroskedasticity. Econometrica 48, 817-838] heteroskedastic-consistent standard errors are calculated, large sample tests can be performed which are robust to heteroskedasticity and the distribution of the disturbances. For a more refined analysis Papke and Wooldridge's [Papke, L.E., Wooldridge, J.M., 1996. Econometric methods for fractional response variables with an application to 401(k) plan participation rates. Journal of Applied Econometrics 11 (6), 619-632] method has some advantages, but is more complex and requires special programming.

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  • McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:2:p:792-798
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    1. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
    2. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    3. Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-844, September.
    4. McDonald, John F & Moffitt, Robert A, 1980. "The Uses of Tobit Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 318-321, May.
    5. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    6. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    7. Boland, Lawrence A, 1979. "A Critique of Friedman's Critics," Journal of Economic Literature, American Economic Association, vol. 17(2), pages 503-522, June.
    8. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    9. Laure Latruffe & Kelvin Balcombe & Sophia Davidova & Katarzyna Zawalinska, 2004. "Determinants of technical efficiency of crop and livestock farms in Poland," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1255-1263.
    10. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    11. John McDonald, 1974. "Errors in Economic Time Series: Some Implications for Estimation in Econometric Models," The Economic Record, The Economic Society of Australia, vol. 50(2), pages 278-286, June.
    12. Bjurek, Hans & Kjulin, Urban & Gustafsson, Bjorn, 1992. " Efficiency, Productivity and Determinants of Inefficiency at Public Day Care Centers in Sweden," Scandinavian Journal of Economics, Wiley Blackwell, vol. 94(0), pages 173-187, Supplemen.
    13. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    14. McDonald, John, 1974. "Errors in Economic Time Series: Some Implications for Estimation in Econometric Models," The Economic Record, The Economic Society of Australia, vol. 50(130), pages 278-286, June.
    15. Korostelev, A. P. & Simar, L. & Tsybakov, A. B., 1995. "Estimation of monotone boundaries," LIDAM Reprints CORE 1178, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Andrews, Donald W. K., 1988. "Chi-square diagnostic tests for econometric models : Introduction and applications," Journal of Econometrics, Elsevier, vol. 37(1), pages 135-156, January.
    17. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    18. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-632, Nov.-Dec..
    19. John McDonald, 1997. "Manorial Efficiency in Domesday England," Journal of Productivity Analysis, Springer, vol. 8(2), pages 199-213, May.
    20. John Ruggiero & Donald F. Vitaliano, 1999. "Assessing The Efficiency Of Public Schools Using Data Envelopment Analysis And Frontier Regression," Contemporary Economic Policy, Western Economic Association International, vol. 17(3), pages 321-331, July.
    21. Chilingerian, Jon A., 1995. "Evaluating physician efficiency in hospitals: A multivariate analysis of best practices," European Journal of Operational Research, Elsevier, vol. 80(3), pages 548-574, February.
    22. Frazer, William J, Jr & Boland, Lawrence A, 1983. "An Essay on the Foundations of Friedman's Methodology," American Economic Review, American Economic Association, vol. 73(1), pages 129-144, March.
    23. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    24. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    25. Korostelev, A.P. & Simar , L. & Tsybakov, A.B., 1995. "On estimation of monotone and convex boundaries," LIDAM Reprints CORE 1139, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. McDonald, John, 1976. "On the Insensitivity of the Autoregressive Moving Average Representations of Some Australian Qtrly Time Series," Econometrica, Econometric Society, vol. 44(6), pages 1277-1287, November.
    27. Andrews, Donald W K, 1988. "Chi-Square Diagnostic Tests for Econometric Models: Theory," Econometrica, Econometric Society, vol. 56(6), pages 1419-1453, November.
    28. Pagan, Adrian & Vella, Frank, 1989. "Diagnostic Tests for Models Based on Individual Data: A Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 29-59, Supplemen.
    29. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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