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Accounting for the dead in the longitudinal analysis of income-related health inequalities

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Listed:
  • Dennis Petrie
  • Paul Allanson
  • Ulf-G Gerdtham

Abstract

This paper develops an accounting framework to consider the effect of deaths on the longitudinal analysis of income-related health inequalities. Ignoring deaths or using inverse probability weights (IPWs) to re-weight the sample for mortality-related attrition can produce misleading results, since to do so would be to disregard the most extreme of all health outcomes. Incorporating deaths into the longitudinal analysis of income-related health inequalities provides a more complete picture in terms of the evaluation of health changes in respect to socioeconomic status. We illustrate our work by investigating health mobility in Quality Adjusted Life Years (QALYs) as measured by the SF6D from 1999 till 2004 using the British Household Panel Survey (BHPS). We show that for Scottish males explicitly accounting for the dead, rather than using IPWs to account for mortality-related attrition, changes the direction of the relationship between relative health changes and initial income position, while for other population groups it increases the strength of this relationship by up to 14 times. When deaths are explicitly incorporated into the analysis it is found that over this five year period for both Scotland and England & Wales the relative health changes were significantly regressive such that the poor experienced a larger share of the health losses relative to their initial share of health and a large amount of this was related to mortality.

Suggested Citation

  • Dennis Petrie & Paul Allanson & Ulf-G Gerdtham, 2010. "Accounting for the dead in the longitudinal analysis of income-related health inequalities," Dundee Discussion Papers in Economics 248, Economic Studies, University of Dundee.
  • Handle: RePEc:dun:dpaper:248
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    References listed on IDEAS

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    More about this item

    Keywords

    mortality; morbidity; income-related health inequality; mobility analysis; longitudinal data; inverse probability weights;
    All these keywords.

    JEL classification:

    • D39 - Microeconomics - - Distribution - - - Other
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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