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A growing polarization of society accompanied by an erosion of the middle class is receiving increasing attention in recent German economic and social policy discussion. Our study contributes to this discussion in two ways: First, on a theoretical level we propose extended multidimensional polarization indices based on a constant elasticity of substitution (CES)-type well-being function and present a new measure to multidimensional polarization, the mean minimum polarization gap, 2DGAP. This polarization intensity measure provides transparency with regard to each single attribute, which is important for targeted policies, while at the same time respecting their interdependent relations. Second, in an empirical application, time is incorporated, in addition to the traditional income measure, as a fundamental resource for any activity. In particular, genuine personal leisure time will account for social participation in the sense of social inclusion/exclusion and Amartya Sen’s capability approach.

Instead of arbitrarily choosing the attribute parameters in the CES well-being function, the interdependent relations of time and income are evaluated by the German population. With the German Socio-Economic Panel (GSOEP) and detailed time use diary data from the German Time Use Surveys (GTUSs) 1991/1992 and 2001/2002, we quantify available and extended multidimensional polarization measures as well as our new approach to measuring the polarization of the working poor and affluent in Germany.

There are three prominent empirical results: Genuine personal leisure time in addition to income is an important and significant polarization attribute. Compensation is of economic and statistical significance. The new minimum 2DGAP approach reveals that multidimensional polarization increased in the 1990s in Germany.

The authors propose a framework to estimate the probability of being poor in a dynamic setting based on a large information set that includes individual characteristics and macro-economic variables. The joint inclusion of personal characteristics along with contextual factors allows separation of idiosyncratic shocks from aggregate shocks affecting poverty. The authors combine data from different cross-sectional surveys and fit a dynamic logistic hierarchical model within a Bayesian framework using standard Markov chain Monte Carlo techniques. The authors’ approach is exemplified by estimating household poverty status in Kyrgyz Republic as a function of time, regions, country, regional level variables and household level socio-demographic characteristics.

This paper examines the effect of welfare reform policies on changes in poverty in the United States during 1992–2005. Using state-level panel data we estimate latent trajectory models to determine if welfare reform has contributed to changes in the trajectories of poverty growth (decline) beyond what would have naturally occurred through the passage of time. Our results show that (a) states vary considerably in both their mean initial level as well as trajectories of poverty; (b) welfare reform was responsible for nearly 27% of the decline in poverty during the study period; (c) the economy played a secondary role, responsible for a 10% reduction in poverty; and (d) income support policies like minimum wage and child support collection also had an important role to play, with the latter contributing as much as welfare reform to poverty reduction. Our estimates remain robust against changes in modeling strategies and methods.

Using real-time data from the University of Luxembourg’s COME-HERE nationally representative panel survey, covering more than 8,000 individuals across France, Germany, Italy, Spain, and Sweden, the author investigates how income distributions and poverty rates have changed from January to September 2020. The author finds that poverty rates increased on average in all countries from January to May and partially recovered in September. The increase in poverty is heterogeneous across countries, with Italy being the most affected and France the least; within countries, COVID-19 contributed to exacerbating poverty differences across regions in Italy and Spain. With a set of poverty measures from the Foster–Greer–Thorbecke family, the author then explores the role of individual characteristics in shaping different poverty profiles across countries. Results suggest that poverty increased disproportionately more for young individuals, women, and respondents who had a job in January 2020 – with different intensities across countries.

There has been a rapid expansion in the literature on the measurement of multidimensional poverty in recent years. This paper focuses on the longitudinal aspects of multidimensional poverty and its link to dynamic income poverty measurement. Using panel household survey data in Vietnam from 2007, 2008, and 2010, the paper analyses the prevalence and dynamics of both multidimensional and monetary poverty from the same dataset. The results show that the monetary poor (or non-poor) are not always multidimensionally poor (or non-poor) – indeed the overlap between the two measures is much less than 50 percent. Additionally, monetary poverty shows faster progress as well as a higher level of fluctuation than multidimensional poverty. We suggest that rapid economic growth as experienced by Vietnam has had a larger and more immediate impact on monetary than on multidimensional poverty.

Supposing that decisionmakers in any country and at any point in time tolerate a certain fixed level of perceived poverty, differences in poverty aversion are called for to explain observed international and intertemporal variations in poverty statistics. Under the Natural Rate of Subjective Poverty hypothesis advanced in this paper, variations in the degree of poverty aversion are estimable and can be explained by political and socioeconomic factors. The methodology is applied to US data from 1975 to 1998 and across nations using cross-section data from the mid-1990s. Factors such as the political affiliation of government officials, public expenditure, per capita income, and economic growth account for much of the variation in poverty aversion implied by our hypothesis. The relationship between inequality aversion and poverty aversion is also explored, with the aid of a parallel “natural rate” hypothesis for inequality (Lambert et al., 2003). Our findings provide a new framework in which to interpret observed correlations between poverty, inequality, and social welfare.

This paper investigates the effect of household size, and in particular of the number of children of different age groups, on poverty, defined as being in a situation of low income. We apply various static and dynamic probit models to control for the endogeneity of the variables of interest and to account for unobserved heterogeneity, state dependence, and serially correlated error components. Using Luxembourg longitudinal data, we show that the number of children of different age groups significantly affects the probability of being poor. However, the magnitude of the effect varies across different specifications. In addition, we find strong evidence of true poverty persistency due to past experience, spurious poverty persistency due to individual heterogeneity, and transitory random shocks.

An axiomatic approach is used to propose a measure of extreme poverty which is not only multidimensional in nature, but also recognizes the fact that there are interaction effects between different deprivations, and that the length of time during which deprivations are felt may also have a negative impact on household well-being. The proposed definition of extreme poverty formalizes an approach developed by Joseph Wresinski, the founder of the International Movement ATD Fourth World.

Poverty and informal employment are often regarded as correlated phenomena. Many empirical studies have shown that informal employment has a causal impact on household poverty, mainly through low wages. Yet other studies focus on the reverse causality from poverty to informality, arising from a range of constraints that poverty poses to jobholders. Only recently have empirical researchers tried to study the simultaneous two-way relationship between poverty and informality. However, existing studies have relied upon cross-sectional data and static econometric models.

This chapter takes the next step and studies the dynamics of poverty and informality using longitudinal data. Our empirical analysis is based on a bivariate dynamic random-effect probit model and recent panel data from Argentina. The method used provides a means of assessing the persistence over time of poverty and informal employment at the individual level, while controlling for both observed and unobserved determinants of the two processes. The results show that both poverty and informal employment are highly persistent processes. Moreover, positive spillover effects are found from past poverty on current informal employment and from past informality to current poverty status, corroborating the view that the two processes are also shaped by interrelated dynamics in segmented labor markets.

We analyse the determinants of poverty transitions, defined as movements across a low-income threshold, in Luxembourg. Data used are those from the Luxembourg socio-economic panel ‘Liewen zu Lëtzebuerg’ (PSELL3) running from 2003 to 2009. Using an endogenous switching first-order Markov model, we control for potential endogeneity to low-income transitions due to both initial conditions and non-random attrition. We find that employment protects from both remaining poor and entering poverty while several characteristics of the head of the household, such as low education or citizenship, and also household composition and housing tenure status are correlated to poverty entry but not to poverty persistence. In addition, attrition and initial low income are found to be endogenous processes with respect to low-income transitions. Finally, genuine state dependence accounts for a substantial level of aggregate state dependence.