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Missing ordinal covariates with informative selection

Author

Listed:
  • Alfonso Miranda

    () (Department of Quantitative Social Science, Institute of Education, University of London. 20 Bedford Way, London WC1H 0AL, UK.)

  • Sophia Rabe-Hesketh

    () (Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA. Institute of Education, University of London, London, UK.)

Abstract

This paper considers the problem of parameter estimation in a model for a continuous response variable y when an important ordinal explanatory variable x is missing for a large proportion of the sample. Non-missingness of x, or sample selection, is correlated with the response variable and/or with the unobserved values the ordinal explanatory variable takes when missing. We suggest solving the endogenous selection, or 'not missing at random' (NMAR), problem by modelling the informative selection mechanism, the ordinal explanatory variable, and the response variable together. The use of the method is illustrated by re-examining the problem of the ethnic gap in school achievement at age 16 in England using linked data from the National Pupil database (NPD), the Longitudinal Study of Young People in England (LSYPE), and the Census 2001.

Suggested Citation

  • Alfonso Miranda & Sophia Rabe-Hesketh, 2010. "Missing ordinal covariates with informative selection," DoQSS Working Papers 10-16, Department of Quantitative Social Science - UCL Institute of Education, University College London.
  • Handle: RePEc:qss:dqsswp:1016
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    Cited by:

    1. Jake Anders, 2012. "Using the Longitudinal Study of Young People in England for research into Higher Education access," DoQSS Working Papers 12-13, Department of Quantitative Social Science - UCL Institute of Education, University College London.

    More about this item

    Keywords

    Missing covariate; sample selection; latent class models; ordinal variables; NMAR;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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