IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0147.html
   My bibliography  Save this paper

Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates

Author

Listed:
  • Leslie E. Papke
  • Jeffrey M. Wooldridge

Abstract

We offer simple quasi-likelihood methods for estimating regression models with a fractional dependent variable and for performing asymptotically valid inference. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to use ad hoc transformations to handle data at the extreme values of zero and one. We also offer some new, simple specification tests by nesting the logit or probit function in a more general functional form. We apply these methods to a data set of employee participation rates in 401(k) pension plans.

Suggested Citation

  • Leslie E. Papke & Jeffrey M. Wooldridge, 1993. "Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates," NBER Technical Working Papers 0147, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0147
    Note: PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0147.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    2. Gurmu, Shiferaw & Trivedi, Pravin K., 1993. "Variable Augmentation Specification Tests in the Exponential Family," Econometric Theory, Cambridge University Press, vol. 9(1), pages 94-113, January.
    3. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July.
    4. repec:cup:etheor:v:9:y:1993:i:1:p:94-113 is not listed on IDEAS
    5. Wooldridge, Jeffrey M., 1991. "Specification testing and quasi-maximum- likelihood estimation," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 29-55.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Song, Jingyu & Delgado, Michael & Preckel, Paul & Villoria, Nelson, 2016. "Pixel Level Cropland Allocation and Marginal Impacts of Biophysical Factors," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235327, Agricultural and Applied Economics Association.
    2. Dietmar Harhoff, 1999. "Firm Formation And Regional Spillovers - Evidence From Germany," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 8(1-2), pages 27-55.
    3. 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.
    4. Hanemann, W. Michael & Kanninen, Barbara, 1996. "The Statistical Analysis Of Discrete-Response Cv Data," CUDARE Working Papers 25022, University of California, Berkeley, Department of Agricultural and Resource Economics.
    5. José M. R. Murteira & Joaquim J. S. Ramalho, 2016. "Regression Analysis of Multivariate Fractional Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 515-552, April.
    6. Hirokazu Ishise & Miwa Matsuo, 2015. "US–Canada border effect between 1993 and 2007: smaller, less asymmetrical, and declining," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 151(2), pages 291-308, May.
    7. Nour Meddahi & Eric Renault, 1998. "Quadratic M-Estimators for ARCH-Type Processes," CIRANO Working Papers 98s-29, CIRANO.
    8. Lindvall, Lars, 2003. "Does Public Spending on Youths Affect Crime Rates?," Working Paper Series 2004:3, Uppsala University, Department of Economics.
    9. Blackburn, McKinley L., 2007. "Estimating wage differentials without logarithms," Labour Economics, Elsevier, vol. 14(1), pages 73-98, January.
    10. Russell Davidson & James G. MacKinnon, 1988. "Specification Tests Based on Artificial Regressions," Working Paper 707, Economics Department, Queen's University.
    11. Lejeune, Bernard, 2009. "A diagnostic m-test for distributional specification of parametric conditional heteroscedasticity models for financial data," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 507-523, June.
    12. Giovanni Forchini & Grant Hillier, 2005. "Ill-conditioned problems, Fisher information and weak instruments," CeMMAP working papers CWP04/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    14. Bettina Becker & Martin Theuringer, 2000. "Macroeconomic Determinants of Contingent Protection: The Case of the European Union," IWP Discussion Paper Series 02/2000, Institute for Economic Policy, Cologne, Germany.
    15. Broze, Laurence & Gourieroux, Christian, 1998. "Pseudo-maximum likelihood method, adjusted pseudo-maximum likelihood method and covariance estimators," Journal of Econometrics, Elsevier, vol. 85(1), pages 75-98, July.
    16. Goergen, Marc & Renneboog, Luc & Correia da Silva, Luis, 2005. "When do German firms change their dividends?," Journal of Corporate Finance, Elsevier, vol. 11(1-2), pages 375-399, March.
    17. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    18. Dionne, G., 2000. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud," Ecole des Hautes Etudes Commerciales de Montreal- 00-04, Ecole des Hautes Etudes Commerciales de Montreal-Chaire de gestion des risques..
    19. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    20. Magnus, Jan R., 2007. "The Asymptotic Variance Of The Pseudo Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 23(5), pages 1022-1032, October.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberte:0147. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.