Now showing 1 - 2 of 2
  • Publication
    Selection bias and measures of inequality
    (University College Dublin. Institute for the Study of Social Change, 2002-02) ; ;
    Variables typically used to measure inequality (e.g., wage earnings, household income or expenditure), are often plagued by nonrandom item nonresponse. Ignoring non-respondents or making (often untestable) assumptions on the nonresponse sub-population can lead to selection bias on estimates of inequality. This paper draws on the approach by Manski (1989,1994) to derive bounding intervals on both the Gini coefficient and the Inter-Quartile range. Both sets of bounds provide alternative measures of inequality which allow for any type of selective nonresponse, while making no assumptions on the behaviour of non-respondents. The theory is illustrated measuring earnings inequality (over time and between samples) for post-unification Germany over the nineties.
      523
  • Publication
    Nonparametric bounds in the presence of item nonresponse, unfolding brackets, and anchoring
    (University College Dublin. Institute for the Study of Social Change (Geary Institute), 2001-09) ; ;
    Household surveys often suffer from nonresponse on variables such as income, savings or wealth. Recent work by Manski shows how bounds on conditional quantiles of the variable of interest can be derived, allowing for any type of nonrandom item nonresponse. The width between these bounds can be reduced using follow up questions in the form of unfolding brackets for initial item nonrespondents. Recent evidence, however, suggests that such a design is vulnerable to anchoring effects. In this paper Manski’s bounds are extended to incorporate the information provided by the bracket respondents allowing for different forms of anchoring. The new bounds are applied to earnings in the 1996 wave of the Health and Retirement Survey. The results show that the categorical questions can be useful to increase precision of the bounds, even if anchoring is allowed for.
      384