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Simulation Of Multinomial Probit Probabilities And Imputation Of Missing Data

In: Messy Data

Author

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  • Victor Lavy
  • Michael Palumbo
  • Steven Stern
Abstract
We use simulation methods to impute missing data. First we suggest how one can iteratively estimate a large number of parameters associated with a joint normal distribution function fof latent variable associated with the data. We suggest a way to test the joint normality assumption next. Finally, we propose a method to use draws from the estimated distribution efficiently in a method of simulated moments or simulated maximum likelihood procedure. In the second half of the paper, we apply the proposed methods ot two data sets from Jamaica with significant missing data problems. We find that the procedure provides better parameter estimates in simple models than present popular methods
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Suggested Citation

  • Victor Lavy & Michael Palumbo & Steven Stern, 1999. "Simulation Of Multinomial Probit Probabilities And Imputation Of Missing Data," Advances in Econometrics, in: Messy Data, pages 145-179, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(1999)0000013008
    DOI: 10.1108/S0731-9053(1999)0000013008
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    Cited by:

    1. Bound, John & Stinebrickner, Todd & Waidmann, Timothy, 2010. "Health, economic resources and the work decisions of older men," Journal of Econometrics, Elsevier, vol. 156(1), pages 106-129, May.
    2. Paul Sullivan, 2009. "Estimation of an Occupational Choice Model when Occupations are Misclassified," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    3. Todd R. Stinebrickner & Ralph Stinebrickner, 2000. "The Relationship Between Family Income and Schooling Attainment: Evidence from a Liberal Arts College with a Full Tuition Subsidy Program," University of Western Ontario, Departmental Research Report Series 20008, University of Western Ontario, Department of Economics.
    4. Stinebrickner, Ralph & Stinebrickner, T.R.Todd R., 2004. "Time-use and college outcomes," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 243-269.

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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