The study of multidimensional deprivation has become one of the most relevant lines of research in the analysis of low‐income households. The search for significant relationships between multidimensional deprivation and income poverty has been a central issue and most empirical studies have found a very weak link. This paper aims at examining the possibility of an aggregation bias in national‐level studies, which could conceal disparities between regions. As regional differences and decentralization processes stand out in Spain as compared to other OECD countries, we focus the analysis on this country. Latent class models are used to define deprivation indices using the Spanish EU‐SILC. The results seem to show that the absence of significant relationships between both phenomena still holds at a regional level. The decomposition methods used in the paper show that it might be due to some regional singularities in some determining factors of income and multidimensional poverty.
The main aim of this paper is to defining a multidimensional housing deprivation index and identifying the main determining characteristics of this phenomenon, using Spain as reference. A latent variable model is used in order to overcome some of the traditional difficulties encountered in multidimensional deprivation studies. The construction of a latent structure model has allowed a set of partial housing deprivation indices to be grouped together under a single index. It has also enabled each individual to be assigned to a different class depending on the level and type of deprivation. Results show that the vector of observed variables (having hot running water, heating, a leaky roof, damp walls or floor, rot in window frames and floors, and overcrowding) and the correlations among such variables can be explained by a single latent variable. There are also specific characteristics that differentiate the population affected by housing deprivation
The purpose of this research is to examine the contribution of unemployment to income inequality and poverty in various OECD countries. These relationships have been explored using Luxembourg Income Study micro‐data. Considerable differences across OECD countries are revealed through the use of within‐household unemployment distributions. These differences help to explain most of the observed divergences in the relationship between unemployment and income distribution, in conjunction with the heterogeneous influence of social benefits on the economic position of the unemployed in these countries. A sub‐group decomposition analysis corroborates the limited effect of unemployment on income distribution in most of the considered countries. However, it seems clear that the unemployed are among those with the highest risk of experiencing poverty.
JEL classification: D31, I32, J31.
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