In this chapter, we used EU-SILC data, Income Tax Office data and Population Census data to estimate the incidence (Head Count Ratio, HCR) and the intensity of poverty (Poverty Gap, PG), in 2012, at the provincial level in Italy by means of small area estimation methods. Given the presenceof spatial correlation, we used a spatial estimator, the spatial Fay-Herriot estimator, to improve the precision of the area-level direct estimates of the two target indicators.
Small Area Methods for Estimating Local Poverty Indicators
Caterina Giusti;Stefano Marchetti
2017-01-01
Abstract
In this chapter, we used EU-SILC data, Income Tax Office data and Population Census data to estimate the incidence (Head Count Ratio, HCR) and the intensity of poverty (Poverty Gap, PG), in 2012, at the provincial level in Italy by means of small area estimation methods. Given the presenceof spatial correlation, we used a spatial estimator, the spatial Fay-Herriot estimator, to improve the precision of the area-level direct estimates of the two target indicators.File in questo prodotto:
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