This paper aims at properly measuring and evaluating the impact of equivalence scales on poverty and inequality at both national and regional (Oblast) level in Ukraine. A new equivalence scale set is proposed and estimated on the basis of the UHLSC data; for some regions the precision of the estimate results as not being sufficient due to small sub-sample sizes. A variant of EBLUP small area estimation technique is proposed and implemented to estimate poverty measures properly and to reduce standard errors of such estimates; the variant concerned is based on a ratio approach: in this way the effect of the difficult-to-qualify institutional and historical factors, common to the country and its regions, is abstracted.

This study provides a step-by-step account of how fuzzy measures of non-monetary deprivation and also monetary poverty may be constructed at the regional level, based on the Mozambican Household Budget Survey 2008-09 (IOF08). To our knowledge, this is the first attempt to apply Fuzzy Set Theory to poverty measurement in Mozambique. The dataset we used is the most recent budget survey available for Mozambique and it is representative of the national, regional (North, Centre, South), provincial and urban/rural level. In order to construct a Fuzzy Set index of poverty, monetary as well as non-monetary indicators are considered, and two different measures of deprivation are subsequently constructed: the Fuzzy Monetary (FM) and Fuzzy Supplementary (FS).

This paper performs an economic poverty and inequality mapping of three children age categories in Malta; it consists in the first attempt based on income from the EU-SILC survey and Census data. From a policy-making point of view, the availability of such key economic indicators at locality level certainly provides a valuable tool in assessing the effectiveness of national strategies and in identifying areas that need to be targeted by new policies; in fact sample surveys alone cannot provide reliable information at such a fine level of detail, while national censuses are not designed to and cannot be extended to cover specific topics such as economic poverty and inequality. Thus, the merging of the two sources provides policy-makers with a new insight into the differences between localities. There are also benefits of a technical nature, particularly in terms of sampling strategies, that can be derived from this study. Through such an exercise it is possible to identify economic homogeneity and/or heterogeneity among households with children in different localities: this is useful when defining strata for sampling design for surveys aiming at studying other economic phenomena relating to children.

The Europe 2020 Strategy has formulated key policy objectives or so-called “headline targets” which the European Union as a whole and Member States are individually committed to achieving by 2020. One of the five headline targets is directly related to the key quality aspects of life, namely social inclusion; within these targets, the European Union Statistics on Income and Living Condition (EU-SILC) headline indicators at risk-of-poverty or social exclusion and its components will be included in the budgeting of structural funds, one of the main instruments through which policy targets are attained. For this purpose, Directorate-General Regional Policy of the European Commission is aiming to use sub-national/regional level data (NUTS 2). Starting from this, the focus of the present paper is on the “regional dimension” of well-being. We propose to adopt a methodology based on the Empirical Best Linear Unbiased Predictor (EBLUP) with an extension to the spatial dimension (SEBLUP); moreover, we compare this small area technique with the cumulation method. The application is conducted on the basis of EU-SILC data from Austria and Spain. Results report that, in general, estimates computed with the cumulation method show standard errors which are smaller than those computed with EBLUP or SEBLUP. The gain of pooling SILC data over three years is, therefore, relevant, and may allow researchers to prefer this method.