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Fractional Response Models - A Replication Exercise of Papke and Wooldridge (1996)

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  • Harald Oberhofer
  • Michael Pfaffermayr

Abstract

This paper replicates the estimates of a fractional response model for share data reported in the seminal paper of Leslie E. Papke and Jeffrey M. Wooldridge published in the Journal of Applied Econometrics 11(6), 1996, pp.619-632. We have been able to replicate all reported estimation results concerning the determinants of employee participation rates in 401(k) pension plans using standard routines provided in Stata. As an alternative, we estimate a two-part model that is able to cope with the excessive number of boundary values of one in the data. The estimated marginal effects are similar to that derived in that paper. A small scale Monte Carlo simulation exercise suggests that the RESET tests proposed by Papke and Wooldridge in their robust form are useful for detecting neglected non-linearities in small samples.
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Suggested Citation

  • Harald Oberhofer & Michael Pfaffermayr, 2012. "Fractional Response Models - A Replication Exercise of Papke and Wooldridge (1996)," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 6(3), September.
  • Handle: RePEc:wyz:journl:id:250
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    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Joaquim J.S. Ramalho & Jacinto Vidigal da Silva, 2009. "A two-part fractional regression model for the financial leverage decisions of micro, small, medium and large firms," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 621-636.
    3. Papke, Leslie E. & Wooldridge, Jeffrey M., 2008. "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 121-133, July.
    4. Esmeralda A. Ramalho & Joaquim J.S. Ramalho & José M.R. Murteira, 2011. "Alternative Estimating And Testing Empirical Strategies For Fractional Regression Models," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 19-68, February.
    5. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053.
    6. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    7. Winfried Pohlmeier & Volker Ulrich, 1995. "An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 339-361.
    8. 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..
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    16. Pericoli, F.M. & Pierucci, E. & Ventura, L., 2013. "Cross-border equity portfolio choices and the diversification motive: A fractional regression approach," Economics Letters, Elsevier, vol. 121(2), pages 282-286.

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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