The relationship between income and housing deprivation in Luxembourg: a longitudinal analysis

The relationship between income and housing deprivation in Luxembourg is analysed at both a cross-sectional and longitudinal level using data from the Panel Socio-Economique ?Liewen zu Lëtzebuerg? (PSELL3) for 2003 to 2009. Long-term housing deprivation is negatively associated with long-term income but this relationship is not confirmed when controlling for unobserved heterogeneity through fixed effect models. This finding suggests that housing deprivation is less affected by short variations in income than by measures of permanent income and that unobserved characteristics of households, such as their wealth or assets, may affect the relationship between long-term income and long-term deprivation.income; housing deprivation; Luxembourg; panel data

Rasch Model and Multidimensional Poverty Measurement

The topic of the multidimensionality of poverty is currently at the heart of many theoretical, empirical and institutional debates in the European Union. Despite this increasing interest, there seems to be no consensus on how to define and measure multidimensional poverty. Two aspects may be considered in measuring poverty: the number of dimensions and the nature of the underlying continuum. The question of the dimensionality of poverty, one versus many dimensions, has to be resolved in applying specific multidimensional methods, like factor analysis, where the one-dimensional solution is a special case of the multidimensional procedure. The question of the nature of the continuum concerns the relationship between the items in each dimension. Two kinds of relationship are considered here: homogeneous and hierarchical. In this paper, the interest of the Rasch model for verifying the hierarchical and cumulative nature of the relationship between the items is underlined. After presenting the main characteristics of the model, and its adjustment for testing poverty, an application confirming the multidimensional nature of poverty is performed on a Luxemburgish dataset (PSELL-3).multidimensional poverty ; Rasch model ; accumulation of disadvantages

Ordinal Variables and the Measurement of Polarization

This paper aims at proposing measures of polarization for the distribution of a variable when information on the latter is only ordinal. The measures proposed are borrowed from the recent literature on the measurement of segregation. An empirical illustration is given, based on the European Union Statistics on Income and Living Conditions (EU-SILC) for the year 2008. The ordinal variable refers to the ?ability to make ends meet? and polarization is measured between groups defined by the citizenship of the household member who answered the household questionnaire. Results show that Luxembourg and Estonia have the highest degree of polarization whereas Cyprus, Ireland and the United Kingdom display the lowest degree.polarization; ordinal information; EU-SILC; segregation

Item response theory and the measurement of deprivation: Evidence from PSELL-3

Item Response Theory (IRT) has recently been proposed as a framework to measure deprivation. It allows deriving a latent measure of deprivation from a set of dichotomous observed items of deprivation and analyzing determinants of deprivation. We investigate further the use of IRT models in the field of deprivation measurement. Firstly, the paper emphasizes the importance of item selection and the Mokken Scale Procedure is applied in order to select the items to be included in the scale of deprivation. Secondly, we apply the one and the two-parameter probit IRT models for dichotomous items on two different sets of items, in order to highlight different empirical results. Finally, we introduce a graphical tool, the Item Characteristic Curve (ICC) and analyse the determinants of deprivation in Luxembourg. The empirical illustration is based on the fourth wave of the Luxembourg socioeconomic panel “Liewen zu Lëtzebuerg” (PSELL-3).item response theory ; deprivation ; latent trait ; Mokken Scale ; PSELL3

Les mesures monétaires et directes de la pauvreté sont-elles substituables ? Investigations sur base de la courbe du ROC

L'utilité pratique des approches non monétaires de la pauvreté est interrogée sur base de l'étude du degré de recoupement entre mesures directes et mesure monétaire de ce concept. L'utilisation de la méthode graphique et non paramétrique de la courbe du Receiver Operating Characteristic (ROC) permet, contrairement à l'approche généralement utilisée, d'évaluer ce degré de recoupement indépendamment du seuil de privation utilisé. L'application de cette méthode aux données du Panel Communautaire des Ménages confirme l'aboutissement de nombreux travaux, à savoir que les résultats issus de ces deux approches se recoupent, mais de manière imparfaite. Dès lors, c'est le caractère complémentaire, plutôt que celui substituable de ces deux mesures qui prévaut. Un tel résultat plaide donc pour un approfondissement de la recherche sur les méthodes directes de mesure de la pauvreté, et ce en vue de compléter l'approche monétaire largement utilisée.Pauvreté monétaire ; Privation matérielle ; Courbe du ROC

A European Union Approach to Material Deprivation using EU-SILC and Eurobarometer data

The paper discusses methodological issues raised by the construction of indicators on material deprivation, which is defined here as an enforced lack of a combination of items depicting some aspects of living conditions related to housing conditions, possession of durables and capacity to afford basic requirements. More specifically, its focus is on the selection of items, their dimensional structure, their aggregation in a synthetic measure and their weighting. The paper also puts in perspective material deprivation and income-based poverty indicators to emphasise the complementarity of the two approaches. It covers the European Union countries available in the 2007 Community Statistics on Income and Living Conditions (EU-SILC) users’ data base.Material deprivation ; EU-SILC ; Eurobarometer ; Poverty ; European Union

Income poverty and material deprivation in European countries

Since 2009, the European Union (EU) portfolio of commonly agreed social in-dicators includes measures of material deprivation. The rationale for this inclu-sion is that if purely income-based indicators of poverty and inequality are es-sential, they are nevertheless not sufficient to satisfactorily reflect the diversity of living conditions in the EU, especially since the 2004 and 2007 enlarge-ments. The paper analyses the relationship between income poverty and mate-rial deprivation in 25 European countries (24 EU Member States plus Norway) and aims at identifying the most important factors that determine the risk of being income poor and/or materially deprived. It is based on the 2007 cross-sectional data of the EU Statistics on Income and Living Conditions (EU-SILC) users? data base.material deprivation; income poverty; European Union; Eu-SILC; open method of coordination; social inclusion

Robust cross-country analysis of inequality of opportunity

International rankings of countries based on inequality of opportunity indices may not be robust vis-vis the specific metric adopted to measure opportunities. Indices often aggregate relevant information and neglect to control for normatively irrelevant distributional factors. This paper shows that gap curves can be estimated from cross-sectional data and adopted to test hypotheses about robust cross-country comparisons of (in)equality of opportunity. (C) 2019 The Authors. Published by Elsevier B.V

Application of the EU-SILC 2011 data module "intergenerational transmission of disadvantage" to robust analysis of inequality of opportunity

This data article describes the original data, the sample selection process and the variables used in Andreoli and Fusco (Andreoli and Fusco, 2019) to estimate gap curves for a sample of European countries. Raw data are from 2011 roaster of EU-SILC, cross-sectional sample of module "intergenerational transmission of disadvantage". This article reports descriptive statistics of the using sample. It also discusses the algorithm adopted to estimate the main effects and details the content of additional Stata files stored on the online repository. These additional files contain raw estimates from bootstrapped samples, which form the basis for estimating gap curves and their variance-covariance matrices. The data article also reports representations of gap curves for all 16 selected countries. (C) 2019 The Authors. Published by Elsevier Inc