IDEAS home Printed from
   My bibliography  Save this paper

An Efficient Estimator for Dealing with Missing Data on Explanatory Variables in a Probit Choice Model


  • Denis Conniffe

    () (Economics, National University of Ireland, Maynooth)

  • Donal O’Neill

    () (Economics, National University of Ireland, Maynooth)


A common approach to dealing with missing data in econometrics is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. In this paper we consider a particular pattern of missing data on explanatory variables that often occurs in practice and develop a new efficient estimator for models where the dependent variable is binary. We derive exact formulae for the estimator and its asymptotic variance. Simulation results show that our estimator performs well when compared to popular alternatives, such as complete case analysis and multiple imputation. We then use our estimator to examine the portfolio allocation decision of Italian households using the Survey of Household Income and Wealth carried out by the Bank of Italy

Suggested Citation

  • Denis Conniffe & Donal O’Neill, 2008. "An Efficient Estimator for Dealing with Missing Data on Explanatory Variables in a Probit Choice Model," Economics, Finance and Accounting Department Working Paper Series n1960908.pdf, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
  • Handle: RePEc:may:mayecw:n1960908.pdf

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    2. Guiso, Luigi & Jappelli, Tullio & Terlizzese, Daniele, 1996. "Income Risk, Borrowing Constraints, and Portfolio Choice," American Economic Review, American Economic Association, vol. 86(1), pages 158-172, March.
    3. John Y. Campbell, 2006. "Household Finance," Journal of Finance, American Finance Association, vol. 61(4), pages 1553-1604, August.
    4. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
    5. Denis Conniffe, 1983. "Small-Sample Properties of Estimators of Regression Coefficients Given a Common Pattern of Missing Data," Review of Economic Studies, Oxford University Press, vol. 50(1), pages 111-120.
    6. Peter Dolton; & Donal O'Neill, 1997. "The Long-Run Effects of Unemployment Monitoring and Work-Search Programs: Some Experimental Evidence from the U.K," Economics, Finance and Accounting Department Working Paper Series n710897, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
    7. Rosen, H.S.Harvey S. & Wu, Stephen, 2004. "Portfolio choice and health status," Journal of Financial Economics, Elsevier, vol. 72(3), pages 457-484, June.
    8. Cameron,A. Colin & Trivedi,Pravin K., 2008. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9787111235767, March.
    9. Claudia Biancotti & Giovanni D'Alessio & Andrea Neri, 2008. "Measurement Error In The Bank Of Italy'S Survey Of Household Income And Wealth," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 54(3), pages 466-493, September.
    10. Tullio Jappelli & Luigi Pistaferri, 2006. "Intertemporal Choice and Consumption Mobility," Journal of the European Economic Association, MIT Press, vol. 4(1), pages 75-115, March.
    11. Brunello, Giorgio & Miniaci, Raffaele, 1999. "The economic returns to schooling for Italian men. An evaluation based on instrumental variables1," Labour Economics, Elsevier, vol. 6(4), pages 509-519, November.
    12. Horowitz, Joel L. & Manski, Charles F., 2006. "Identification and estimation of statistical functionals using incomplete data," Journal of Econometrics, Elsevier, vol. 132(2), pages 445-459, June.
    13. Chesher, Andrew, 1984. "Improving the Efficiency of Probit Estimators," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 523-527, August.
    14. Hamermesh, Daniel S., 1999. "LEEping into the future of labor economics: the research potential of linking employer and employee data," Labour Economics, Elsevier, vol. 6(1), pages 25-41, March.
    15. Christian Gourieroux & Alain Monfort, 1981. "On the Problem of Missing Data in Linear Models," Review of Economic Studies, Oxford University Press, vol. 48(4), pages 579-586.
    16. Hartog, Joop & Ferrer-i-Carbonell, Ada & Jonker, Nicole, 2002. "Linking Measured Risk Aversion to Individual Characteristics," Kyklos, Wiley Blackwell, vol. 55(1), pages 3-26.
    17. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    18. Dolton, Peter & O'Neill, Donal, 1996. "Unemployment Duration and the Restart Effect: Some Experimental Evidence," Economic Journal, Royal Economic Society, vol. 106(435), pages 387-400, March.
    19. Couch, Kenneth A, 1992. "New Evidence on the Long-Term Effects of Employment Training Programs," Journal of Labor Economics, University of Chicago Press, vol. 10(4), pages 380-388, October.
    20. Guiso, Luigi & Jappelli, Tullio & Pistaferri, Luigi, 2002. "An Empirical Analysis of Earnings and Employment Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 241-253, April.
    21. Luigi Pistaferri, 2003. "Anticipated and Unanticipated Wage Changes, Wage Risk, and Intertemporal Labor Supply," Journal of Labor Economics, University of Chicago Press, vol. 21(3), pages 729-754, July.
    22. Christopher Paul & William Mason & Daniel McCaffrey & Sarah Fox, 2008. "A cautionary case study of approaches to the treatment of missing data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 351-372, July.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Bolhaar, Jonneke & Lindeboom, Maarten & van der Klaauw, Bas, 2010. "Insurance Search and Switching Behavior," CEPR Discussion Papers 7942, C.E.P.R. Discussion Papers.
    2. Bolhaar J & Lindeboom M & van der Klaauw B, 2009. "Insurance Search and Switching Behaviour at the time of the Dutch Health Insurance Reform," Health, Econometrics and Data Group (HEDG) Working Papers 09/14, HEDG, c/o Department of Economics, University of York.

    More about this item


    Missing Data; Probit Model; Portfolio Allocation; Risk Aversion;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:may:mayecw:n1960908.pdf. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: () or (Candi Patterson) or (Katrina Wingle). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.