52nd Congress of the European Regional Science Association: "Regions in Motion - Breaking the Path", 21-25 August 2012, Bratislava, Slovakia
One of the targets of Europe's growth strategy (Europe 2020) is "reduction of poverty by aiming to lift at least 20 million people out of the risk of poverty or social exclusion". Since poverty is a multidimensional concept, EUROSTAT proposes three indicators to calculate it: people at risk-of-poverty after social transfers (persons are at risk of poverty if their equivalent disposable income is below the risk-of-poverty threshold, which is set at 60 % of the national median after social transfers); severely materially deprived people (severely materially deprived persons have living conditions greatly constrained by a lack of resources and cannot afford at least four of the following: to pay rent or utility bills; to keep their home adequately warm; to pay unexpected expenses; to eat meat, fish or a protein equivalent every second day; a week holiday away from home; a car; a washing machine; a colour TV; or a telephone) and people living in households with very low work intensity (persons are defined as living in households with very low work intensity if they are aged 0-59 and the working age members in the household worked less than 20 % of their potential during the past year.). We concentrate on the first two indicators and analyze the relationships between them using the Spanish Survey on Living Conditions 2010. Following EUROSTAT methodology we found that 2,590,148 Spanish households can be considered poor and 504,227 are deprived. But only 262,280 are, at the same time, poor and deprived. In order to improve deprivation index we substitute EUROSTAT methodology by Fuzzy method but results do not get better. Additionally, we test both deprivation indicators with households' income distribution (percentiles) and find very significant inconsistencies: some deprived families belong to the highest income percentiles and some variables used to work out the indexes have sample problems. The main conclusion of the article is that in order to calculate a poverty multidimensional index we should take into account that social exclusion variables and indexes have to be analyzed very carefully before using them to classify people as deprived, at least in the Spanish case.