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In light of the EU2030 strategy for poverty alleviation, this paper provides an assessment on the quality of estimates of poverty and inequality indicators at sub-national level (NUTS2) in Germany and Italy. Given the elaborated survey design of EU-SILC and the complexity of some poverty and inequality indicators that we consider in this paper, we use the Taylor linearization approach to estimate their variance. As a further assessment on the goodness of these estimates, we use a Fay–Herriot model to see in what extent we can obtain estimates with lower mean squared error using small area estimation. Our results reveal high territorial heterogeneity in living conditions across sub-national domains, in particular in some southern regions of Italy and some eastern government regions of Germany. Moreover, results from Fay–Herriot model reveals higher gains in efficiency for the 36 government regions of Germany especially for income-inequality indicators. • we use the Taylor linearization approach to estimate variance in poverty indicators. • we use a Fay–Herriot model to obtain estimates with lower mean squared error. • we map the spatial distribution of poverty indicators at NUTS-2 level. • Our results reveal high territorial heterogeneity across sub-national domains. [ABSTRACT FROM AUTHOR]