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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

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Paper provided by Department of Economics, Finance and Accounting, National University of Ireland - Maynooth in its series Economics, Finance and Accounting Department Working Paper Series with number n1960908.pdf.

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Length: 36 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:may:mayecw:n1960908.pdf
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Web page: http://www.maynoothuniversity.ie/economics-finance-and-accounting

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  1. Chesher, Andrew, 1984. "Improving the Efficiency of Probit Estimators," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 523-27, August.
  2. 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 241-53, April.
  3. Tullio Jappelli & Luigi Pistaferri, 1999. "Intertemporal Choice and Consumption Mobility," CSEF Working Papers 23, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  4. 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, 09.
  5. 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 380-88, October.
  6. 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.
  7. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
  8. 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.
  9. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, June.
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  11. John Y. Campbell, 2006. "Household Finance," NBER Working Papers 12149, National Bureau of Economic Research, Inc.
  12. 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.
  13. Guiso, Luigi & Jappelli, Tullio & Terlizzese, Daniele, 1996. "Income Risk, Borrowing Constraints, and Portfolio Choice," American Economic Review, American Economic Association, vol. 86(1), pages 158-72, March.
  14. Harvey S. Rosen & Stephen Wu, 2003. "Portfolio Choice and Health Status," NBER Working Papers 9453, National Bureau of Economic Research, Inc.
  15. 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.
  16. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
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  22. 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.
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