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Efficient Probit Estimation with Partially Missing Covariates

Author

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  • Conniffe, Denis

    () (National University of Ireland, Maynooth)

  • O'Neill, Donal

    () (National University of Ireland, Maynooth)

Abstract

A common approach to dealing with missing data is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. We derive a new probit type estimator for models with missing covariate data where the dependent variable is binary. For the benchmark case of conditional multinormality we show that our estimator is efficient and provide exact formulae for its asymptotic variance. Simulation results show that our estimator outperforms popular alternatives and is robust to departures from the benchmark case. We illustrate our estimator by examining the portfolio allocation decision of Italian households.

Suggested Citation

  • Conniffe, Denis & O'Neill, Donal, 2009. "Efficient Probit Estimation with Partially Missing Covariates," IZA Discussion Papers 4081, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp4081
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    References listed on IDEAS

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    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. Peter Dolton & Donal O'Neill, 2002. "The Long-Run Effects of Unemployment Monitoring and Work-Search Programs: Experimental Evidence from the United Kingdom," Journal of Labor Economics, University of Chicago Press, vol. 20(2), pages 381-403, Part.
    3. Chesher, Andrew, 1984. "Improving the Efficiency of Probit Estimators," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 523-527, August.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    9. Conniffe, Denis, 1985. "Estimating regression equations with common explanatory variables but unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 27(2), pages 179-196, February.
    10. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    11. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
    12. John Y. Campbell, 2006. "Household Finance," Journal of Finance, American Finance Association, vol. 61(4), pages 1553-1604, August.
    13. 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.
    14. 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.
    15. Michael Beenstock, 2004. "Rank And Quantity Mobility In The Empirical Dynamics Of Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 50(4), pages 519-541, December.
    16. Luigi Guiso & Tullio Jappelli, 2000. "Household Portfolios in Italy," CSEF Working Papers 43, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    17. Cameron,A. Colin & Trivedi,Pravin K., 2008. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9787111235767.
    18. 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.
    19. 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.
    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. 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.
    22. Carol C. Bertaut & Martha Starr-McCluer, 2000. "Household portfolios in the United States," Finance and Economics Discussion Series 2000-26, Board of Governors of the Federal Reserve System (U.S.).
    23. 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.
    24. 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.
    25. Feldstein, Martin S, 1976. "Personal Taxation and Portfolio Composition: An Econometric Analysis," Econometrica, Econometric Society, vol. 44(4), pages 631-650, July.
    26. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
    27. 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.
    28. 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.
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    Cited by:

    1. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    2. Laitila, Thomas & Wang, Lisha, 2015. "A Two-Step Estimator for Missing Values in Probit Model Covariates," Working Papers 2015:3, Örebro University, School of Business.

    More about this item

    Keywords

    risk aversion; probit model; portfolio allocation; missing data;

    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

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