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Misspecification Preferred: The Sensitivity of Inefficiency Rankings

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  • Uwe Jensen

Abstract

Ruggiero (European Journal of Operational Research 115, 555–563. 1999) compared the two popular parametric frontier methods for cross-sectional data—the stochastic frontier and the corrected OLS—in a simulation study. He demonstrated that the inefficiency ranking accuracy of the established stochastic frontier is uniformly inferior to that of the misspecified Corrected OLS (COLS) (which lacks an error term). The reason for his result remains unclear, however. In this paper, a more extensive simulation study is therefore conducted to find out whether the superiority of COLS is simply due to small sample sizes or to poor performance of the inefficiency level estimator. Copyright Springer Science+Business Media, Inc. 2005

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  • Uwe Jensen, 2005. "Misspecification Preferred: The Sensitivity of Inefficiency Rankings," Journal of Productivity Analysis, Springer, vol. 23(2), pages 223-244, May.
    • Handle: RePEc:kap:jproda:v:23:y:2005:i:2:p:223-244
    DOI: 10.1007/s11123-005-1330-y
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    1. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    2. Gong, Byeong-Ho & Sickles, Robin C., 1992. "Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 259-284.
    3. Uwe Jensen, 2000. "Is it efficient to analyse efficiency rankings?," Empirical Economics, Springer, vol. 25(2), pages 189-208.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    6. Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
    7. Ruggiero, John, 1999. "Efficiency estimation and error decomposition in the stochastic frontier model: A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 555-563, June.
    8. Bill L. Seaver & Konstantinos P. Triantis, 1995. "The Impact of Outliers and Leverage Points for Technical Efficiency Measurement Using High Breakdown Procedures," Management Science, INFORMS, vol. 41(6), pages 937-956, June.
    9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Citations

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    Cited by:

    1. Jensen, Uwe & Rässler, Susanne, 2005. "Where have all the data gone? Stochastic production frontiers with multiply imputed German establishment data," IAB-Discussion Paper 200515, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Parmeter, Christopher F., 2021. "Is it MOLS or COLS?," Efficiency Series Papers 2021/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Géraldine Henningsen & Arne Henningsen & Uwe Jensen, 2015. "A Monte Carlo study on multiple output stochastic frontiers: a comparison of two approaches," Journal of Productivity Analysis, Springer, vol. 44(3), pages 309-320, December.
    4. Jensen, Uwe & Rässler, Susanne, 2007. "The effects of collective bargaining on firm performance : new evidence based on stochastic production frontiers and multiply imputed German establishment data," IAB-Forschungsbericht 200703, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Leppin Julian S., 2014. "The Estimation of Reservation Wages: A Simulation-Based Comparison," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 603-634, October.
    6. Janda, Karel & Krska, Stepan, 2014. "Benchmarking Methods in the Regulation of Electricity Distribution System Operators," MPRA Paper 59442, University Library of Munich, Germany.
    7. Jensen, Uwe & Rässler, Susanne, 2006. "Stochastic production frontiers with multiply imputed German establishment data," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 39(2), pages 277-295.
    8. Jensen, Uwe & Gartner, Hermann & Rässler, Susanne, 2006. "Measuring overeducation with earnings frontiers and multiply imputed censored income data," IAB-Discussion Paper 200611, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    9. Julia Schaefer & Marcel Clermont, 2018. "Stochastic non-smooth envelopment of data for multi-dimensional output," Journal of Productivity Analysis, Springer, vol. 50(3), pages 139-154, December.
    10. Timothy J. Gronberg & Dennis W. Jansen & Lori L. Taylor, 2017. "Are Charters the Best Alternative? A Cost Frontier Analysis of Alternative Education Campuses in Texas," Southern Economic Journal, John Wiley & Sons, vol. 83(3), pages 721-743, January.
    11. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
    12. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    13. Sakouvogui Kekoura & Shaik Saleem & Doetkott Curt & Magel Rhonda, 2021. "Sensitivity analysis of stochastic frontier analysis models," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 71-90, March.
    14. Jensen, Uwe & Rässler, Susanne, 2006. "Stochastic production frontiers with multiply imputed German establishment data," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 39(2), pages 277-295.
    15. Uwe Jensen & Hermann Gartner & Susanne Rässler, 2010. "Estimating German overqualification with stochastic earnings frontiers," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(1), pages 33-51, March.

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