Multivariate Models for the Estimation of Poverty Indicators By Administrative Region and Household Type

In recent years, the measure of regional disparities on household poverty and social exclusion has received increasing attention by policy makers and this has produced a growing demand of sub-national statistical information on income parameters. Many studies have shown a strong connection between poverty and some characteristics of the household such as its composition, highlighting the concentration of the greatest economic difficulties in particular household typologies. For this reason, the aim of the work is to provide estimates of some poverty indicators for domains defined by cross-classifying the population by household typology (9 categories) and administrative region (20 categories), on the basis of data collected for Italy by the “European Union – Statistics on Income and Living Conditions” survey (EU-SILC). The need of estimating simultaneously more than one parameter is due to the multidimensionality of the studied phenomenon. In particular, we focus on three poverty rates based on three different thresholds, so to distinguish between poor people (PR, standard poverty threshold defined as the 60% of median of personal equivalent income), very poor people (PR80, threshold defined as the 80% of the standard poverty threshold) and people who are at risk of becoming poor (PR120, threshold defined as the 120% of the standard poverty threshold). The considered source, EU-SILC, is a sample survey on households’ income and social conditions, coordinated by Eurostat (Eurostat, 2005), designed to provide reliable estimates of main parameters of interest for areas within countries that do not correspond to our target domains. The number of units sampled from those domains are too scarce, in many cases, to obtain reliable estimates of the parameters of interest, therefore some small area estimation strategies have to be considered.