Estimating income poverty in the presence of measurement error and missing data problems (joint with Cheti Nicoletti and Franco Peracchi)ISER Internal Seminars

Reliable measures of poverty are an essential statistical tool for public
policies aimed at reducing poverty. In this paper we consider the
reliability of income poverty measures based on survey data which are
typically plagued by measurement error and missing data problems. Neglecting
these problems can bias the estimated poverty rates. We show how to derive
upper and lower bounds for the population poverty rate using only the sample
evidence and an upper limit on the probability of misclassifying people into
poor and non-poor. By using the European Community Household Panel, we
compute bounds for the poverty rate in eleven European countries and study
the sensitivity of poverty comparisons across countries to measurement
errors and missing data problems.

Presented by:

Francesca Foliano (ISER Visitor, University of Tor Vergata)

Date & time:

26 Mar 2008 13:00 pm - 26 Mar 2008 00:00 am

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