Determinants of individual income in EU countries: implications for social policy targeting

Introduction

The introduction of the Income Index constructed by authors as well as the identification of demographic, socio-economic and occupation-related factors influencing the income of individuals in EU countries is the main contribution of the paper. The Income Index makes it possible to analyze data of individuals from all EU countries.

Methods

The multiple hierarchical regression of EU-SILC microdata provides the factors that influence individuals' income.

Results

Outcomes show through which factors can be intervened in social policy settings to reduce income inequality. Factors significantly affecting the Income Index are the household composition, occupation sector (typically agriculture and accommodation and services are related to low incomes) and the degree of urbanization (rural areas with the lowest incomes of individuals).

Discussion

Findings confirm ongoing discussions about the specific position of single parent households in the labour market and their need for social support.

Size or Content of the Pie? Source of Income and Perceived Income Adequacy of Older Europeans

While public pensions are usually the main source of income in old age, other sources of income may have various consequences for pensioners' economic well-being across households and countries. In this study, we analyze how perceived income adequacy of older Europeans is shaped by the source and the income level. We hypothesize that the source of income can be related to a household's perceived income adequacy beyond the money it provides. We distinguish four categories of income sources: (old age) pensions, other social benefits, work, and capital. We show that the source of income is related to perceived adequacy beyond the money it provides. Compared with pensions, income from other social benefits or work is associated with lower, and income from capital with higher perceptions of adequacy. Perceived adequacy of income from different sources varied further across the household income level. The results convey important messages to the policy makers. Pensions are a powerful policy tool, as they provide positive externalities beyond their monetary value. Attention should also be paid to the low-income households' possibilities to save.

Well-Being Adjusted Health Expectancy: A New Summary Measure of Population Health

We propose a new summary measure of population health (SMPH), the well-being-adjusted health expectancy (WAHE). WAHE belongs to a subgroup of health-adjusted life expectancy indicators and gives the number of life years equivalent to full health. WAHE combines health and mortality information into a single indicator with weights that quantify the reduction in well-being associated with decreased health. WAHE's advantage over other SMPHs lies in its ability to differentiate between the consequences of health limitations at various levels of severity and its transparent, simple valuation function. Following the guidelines of a Committee on Summary Measures of Population Health, we discuss WAHE's validity, universality, feasibility sensitivity and ensure its reproducibility. We evaluate WAHE's performance compared to life expectancy, the most commonly used indicators of health expectancy (HE) and disability-adjusted life expectancy (DALE) in an empirical application for 29 European countries. Data on health and well-being are taken from the 2018 EU-SILC, and the life tables are from Eurostat. DALE is taken from the database of the Global Burden of Disease Programme. WAHE's sensitivity to univariate and multivariate state specifications is studied using the three Minimum European Health Module health dimensions: chronic morbidity, limitations in activities of daily living, and self-rated health. The empirical tests of the indicators' correspondence reveal that WAHE has the strongest correlation with the other SMPHs. Moreover, WAHE estimates are in agreement with all other SMPHs. Additionally, WAHE and all other SMPHs form a group of reliable indicators for studying population health in European countries. Finally, WAHE estimates are robust, regardless of whether health is defined across one or multiple simultaneous dimensions of health. We conclude that WAHE is a useful and reliable indicator of population health and performs at least as well as other commonly used SMPHs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10680-022-09628-1.

Linked lives, linked retirement? Relative income differences within couples and gendered retirement decisions in Europe

Our article investigates the role of relative income distributions within couples for individuals' retirement risks. It addresses the following questions: How does the share someone provides to the couple income affect that person's retirement decision? What gender differences do we observe and what contextual factors can explain country differences? Our multilevel analyses draw on data from the European Union Statistics on Income and Living Conditions (EU-SILC) study (2010-2016), comparing 26 countries. The results show that female main earners transition to retirement earlier than female secondary earners as they approach the official retirement age. This effect is even stronger in countries with more traditional gender norms. The opposite pattern is found for men, whereby male secondary earners retire earlier than male main earners in more gender traditional societies. We explain this finding on the basis of doing gender theories, which predict that gender-atypical behaviour in one area of life is compensated by traditional gender behaviour in other areas, especially in contexts with traditional gender norms. A further finding relates to the generosity of the country's pension replacement rate, which shows to be a factor facilitating retirement especially for those with an equal earning partner.

Until Death Do Us Part. The Influence of Own and Partner's Socioeconomic Status on the Health of Spanish Middle-Aged Population

Objectives: To explore whether the influence of a partner’s socioeconomic status (SES) on health has an additive or a combined effect with the ego’s SES. Methods: With data on 4533 middle-aged (30–59) different-sex couples from the 2012 Spanish sample of the European Union Statistics on Income and Living Conditions (EU-SILC) survey, we apply separate sex-specific logistic regression models to calculate predicted probabilities of having less than good self-perceived health according to individual and partner’s characteristics separately and combined. Results: Both approaches led to similar results: Having a partner with better SES reduces the probabilities of not having good health. However, the combined approach is more precise in disentangling SES effects. For instance, having a higher educated partner only benefits health among Spanish low-educated men, while men’s health is worse if they have a working spouse. Conversely, women’s health is positively influenced if at least one couple member is economically active. Conclusions: There are significant health differences between individuals according to their own and their partner’s SES in an apparently advantageous population group (i.e., individuals living with a partner). The combinative approach permits obtaining more precise couple-specific SES profiles.

Are partner's features important to understand health at older ages? The Spanish case

OBJECTIVE

To analyse health differences among partnered individuals in Spain aged 65-81 considering their combined (education of both partners and age gap) and household (economic capacity of the household) characteristics.

METHOD

A cross-sectional study of the 2015 Spanish sample of the European Union Statistics on Income and Living Conditions survey (EU-SILC) on partnered individuals aged 65-81 years (N=1787). Using logistic regression models separately for women and men we obtained odds and predicted probabilities of having less than good health (95% confidence intervals) according to combined information from both partners on education and age, the household's economic capacity and partner's health status.

RESULTS

Probabilities of not having good health are significantly less among lower educated women whose partners are more highly educated (compared to both partners being lower educated) and among women whose partner is younger or has good health status. The latter also applies to men. Living in a household without economic difficulties also favours health (both sexes).

CONCLUSIONS

For both sexes a partner's health status is the variable that shows the largest effect on elderly partnered Spanish people's health but women's health appears to be more sensitive to their partner's educational attainment and the household's economic situation.

Who supports whom? Do adult children living at home share their incomes with their parents?

Across the developed world, young adults are now more likely to live with their parents than they were two or three decades ago. This is typically viewed, both in the media and in scholarly research, as an economic burden on parents. This article investigates, for the first time, the extent to which financial support is also given in the opposite direction, with young people contributing to their households' living costs. We use data on 19 European countries from the 2010 European Union Statistics on Income and Living Conditions (N = 553 in Austria to N = 2777 in Italy). Many young adults do share their incomes with their families, with the degree of sharing being the highest among the poorest households. In a substantial minority of households, particularly in lower-income countries, the contributions of young adult household members keep households out of poverty.

The Great Recession, financial strain and self-assessed health in Ireland

In this paper, we study the effects of the 2008 economic crisis on general health in one of the most severely affected EU economies-Ireland. We examine the relationship between compositional changes in demographic and socio-economic factors, such as education, income, and financial strain, and changes in the prevalence of poor self-assessed health over a 5-year period (2008-2013). We apply a generalised Oaxaca-Blinder decomposition approach for non-linear regression models proposed by Fairlie (1999, 2005). Results show that the increased financial strain explained the largest part of the increase in poor health in the Irish population and different sub-groups. Changes in the economic activity status and population structure also had a significant positive effect. The expansion of education had a significant negative effect, preventing further increases in poor health. Wealthier and better educated individuals experienced larger relative increases in poor health, which led to reduced socio-economic health inequalities.

Water expenses by households living in Flanders: Data availability in the Belgian EU-SILC

Few data sources in developed countries contain for a representative sample of households information on water expenses alongside a rich set of reliable information on individual and household characteristics. In this Data in Brief we describe the Belgian EU-SILC data, which we used for ‘Measuring water affordability in developing economies. The added value of a needs-based approach’ (Vanhille et al., 2018) [1]. EU-SILC can be obtained from the Belgian National Statistical Institute and is the most important representative household survey on income and living conditions in the European Union, and contains, among others, an advanced measurement of household income. It is not well-known, though, that national datasets often contain more information, making them suitable for studies that are somewhat outside the ‘core scope’ of EU-SILC. One example is studying the consumption of water by households, as can be done for Belgium. In this article we briefly introduce the Belgian EU-SILC and present the data on water expenses for households living in Flanders. In 2015, 50 per cent less than 23 EUR on water, while 90 per cent spent less than 45 EUR on water.

The Structure of Subjective Well-Being and Its Relation to Objective Well-Being Indicators: Evidence from EU-SILC for Serbia

In this article, we examine the structure of the subjective well-being and its relation to objective well-being indicators using the data from the European Union's Survey on Income and Living Conditions (EU-SILC) from Serbia. This is one of the first papers to analyze a new module on subjective well-being from EU-SILC micro-dataset (with over 20,000 respondents). We investigate the factor structure of the items and the differences in the association of subjective well-being dimensions with objective indicators of well-being within the Organisation for Economic Co-operation and Development Better Life Initiative framework. Three factors emerge from the principal components analysis: general life satisfaction, affective well-being, and satisfaction with the local environment. The analysis further reveals that life satisfaction is more related to the material living conditions, such as income, unemployment, and housing conditions, while affective well-being is more related to non-material indicators of well-being such as perceived health, personal security, and social connections. On the other hand, positive and negative affect within the affective well-being are not clearly separable, nor is the eudaimonic indicator from either life satisfaction or affective well-being.

Effect of having private health insurance on the use of health care services: the case of Spain

Background

Several stakeholders have undertaken initiatives to propose solutions towards a more sustainable health system and Spain, as an example of a European country affected by austerity measures, is looking for ways to cut healthcare budgets.

Methods

The aim of this paper is to study the effect of private health insurance on health care utilization using the latest micro-data from the European Community Household Panel (ECHP), the Spanish National Health Survey (SNHS) and the European Union Statistics on Income and Living Conditions (EU-SILC). We use matching techniques based on propensity score methods: single match, four matches, bias-adjustment and allowing for heteroskedasticity.

Results

The results demonstrate that people with a private health insurance, use the public health system less than individuals without double health insurance coverage.

Conclusions

Our conclusions are useful when policy makers design public-private partnership policies.

Differences Between Household Income from Surveys and Registers and How These Affect the Poverty Headcount: Evidence from the Austrian SILC

We take advantage of the fact that for the Austrian SILC 2008-2011, two data sources are available in parallel for the same households: register-based and survey-based income data. Thus, we aim to explain which households tend to under- or over-report their household income by estimating multinomial logit and OLS models with covariates referring to the interview situation, employment status and socio-demographic household characteristics. Furthermore, we analyze source-specific differences in the distribution of household income and how these differences affect aggregate poverty indicators based on household income. The analysis reveals an increase in the cross-sectional poverty rates for 2008-2011 and the longitudinal poverty rate if register data rather than survey data are used. These changes in the poverty rate are mainly driven by differences in employment income rather than sampling weights and other income components. Regression results show a pattern of mean-reverting errors when comparing household income between the two data sources. Furthermore, differences between data sources for both under-reporting and over-reporting slightly decrease with the number of panel waves in which a household participated. Among the other variables analyzed that are related to the interview situation (mode, proxy, interview month), only the number of proxy interviews was (weakly) positively correlated with the difference between data sources, although this outcome was not robust over different model specifications.

Opening the black box of under-health people: the case of Spain

The most famous modern definition of health was created during a Preamble to the Constitution of the World Health Organization in 1946: "Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity." This definition has not been amended and, since then, many indicators have been proposed to measure health such as Self-Assessed Health (SAH) status. It provides an overall measure of a population's health based on individuals' personal perceptions of their own health.In this paper, we focus our analysis on "under-health" as the fact of having a level that falls behind the health requirements necessary to perform what is considered an "expected life based on Self Assessed Health". For Spain using the European Union Statistics on Income and Living Conditions (EU-SILC), we can confirm there exist under-healthy people by occupation, age group and sex. Additionally, under-healthy workers are most likely to be found among skilled agricultural, fishery workers and elementary occupations.

Health Effects of Unemployment in Europe During the Great Recession: The Impact of Unemployment Generosity

Social and economic security could be particularly important for health among the unemployed. Nevertheless, knowledge is still lacking as to whether and how different policy contexts affect health when people move into unemployment. This article investigates whether and to what degree the unemployment generosity explains why individual health effects of unemployment vary across Europe. The 2008-2011 longitudinal panel of the European Union statistics on income and living conditions (EU-SILC) and fixed-effects models are used to estimate the individual effects of unemployment on self-rated health (SRH). Social spending on unemployment is used as a proxy for unemployment generosity. The results show that unemployment generosity is associated with reduced negative effects of unemployment on SRH. For every increase in adjusted purchasing power standard spending, the negative effect of unemployment on SRH is reduced by 0.003 (SE = 0.001) and the change in SRH is improved by 0.002 (SE = 0.001) for each year following the transition, after controlling for time-variant confounders at the individual level and unemployment rate at the macro level. The association between spending on unemployment and cross-national differences in individual health changes that occur as people enter unemployment provides a robust indication of the mitigating health effects of unemployment generosity.

Spatial Variation in EU Poverty with Respect to Health, Education and Living Standards

We examine the European Union (EU) countries and within-country areas (i.e., large urban areas, small urban areas, and rural areas) that are the most disadvantageous with respect to multidimensional poverty and in each of the investigated dimensions, i.e., health, education, and living standards. To this end, we construct the Multidimensional Poverty Index and its sub-indices: the Poverty in Health Index, Poverty in Education Index, and Poverty in Standard of Living Index. All of these indices provide information regarding the fraction of people who live in poverty, as well as information on the poverty intensity experienced by the poor. Our results indicate that the scale of poverty in the EU countries is diversified, with Denmark and Sweden being the most affluent countries, and Latvia, Bulgaria, and Romania being the most disadvantageous. We demonstrate that there are countries with no differences in the levels of poverty within a country, such as Denmark, Sweden, Spain, Finland, and the Czech Republic, and countries, usually less affluent ones such as Romania, Bulgaria and Lithuania, where considerable geographical inequality is present. In general, in countries with a high and moderately high number of poor, the worst situation with respect to the scale of poverty is observed in rural areas, and the best situation is observed in large urban areas, with the exception of Greece, Italy, and Portugal, where in large urban areas, the situation is the worst. In countries with a low number of poor, in general, the poverty is relatively higher in large urban areas.

A Measure to Target Antipoverty Policies in the European Union Regions

The reformed cohesion policy (CP), which is the major investment tool in the European Union (EU) for delivering the Europe 2020 targets, will soon make available substantial funds to improve the quality of life of the EU citizens through supporting the economic and social development of the EU's regions and cities. Because the reformed CP has intensified the emphasis on measuring results, also with respect to reducing poverty and social exclusion, this paper is about measuring poverty to better target EU local policies. We propose a measurement of poverty at the sub-national level in the EU by means of three poverty components describing absolute poverty, relative poverty and earnings and incomes. The core data source is the cross-sectional European Statistics on Income and Living Conditions (EU-SILC) micro-data, waves 2007-2009. Data reliability at the sub-national level is statistically assessed and the regional level is described whenever possible. To calculate the poverty components, an inequality-adverse type of aggregation is applied in order to limit compensability across indicators populating a component. No aggregation is, however, performed across the three components. In the computations of income-related indicators, individual disposable income adjusted for housing costs, used as a proxy for the costs of living, is used. Poverty is confirmed to be a multi-faceted phenomenon with clear within-country variability. This variation depends on the type of region likely linked to the urbanisation level and, consequently, to the costs of living. The proposed measure may serve to better target anti-poverty measures at the local, sub-national level in the EU.