Gender and Poverty Risk in Europe

Abstract

This study advances research on the structural dimension in the predominantly individual-oriented field of poverty studies by evaluating to what extent cross-national differences in population and structural characteristics can explain the differences in poverty outcomes by gender. To facilitate an approach that integrates individual and structural context dimensions, the paper takes advantage of multilevel techniques to test gender differences in the risk of being poor, entering into poverty, and exiting from poverty among seventeen European countries. The analysis covers single-adult households, drawing on data from the European Union Statistics on Income and Living Conditions (EU-SILC) for the years 2007–8. The study concludes that structural effects, such as welfare state policies, labor market characteristics, level of inequality, and the level of women's empowerment in the country, seem to be more relevant than individual effects in explaining differences in the gender poverty gap among countries.

Keywords:

• Gender
• poverty
• poverty dynamics
• multilevel analysis
• European Union Statistics on Income and Living Conditions

Keywords:

• J16
• I32
• O57

Acknowledgements

We would like to acknowledge the comments of participants at the German Social Science Infrastructure Services (GESIS) 2011 workshop in Mannheim, Germany. The financial support from the Spanish Ministry of Education through grant SEJ2009-11117 to Ana I. Moro-Egido and through grant SEJ2012-33993 to Elena Bárcena-Martín and Ana I. Moro-Egido is also gratefully acknowledged. All errors are solely ours.

Notes

We are conscious that because this analysis focuses on only two years, the dynamic dimension is limited. The reasons for that short period are: (1) the dataset (panel) spans only four years; and (2) if we consider transitions in a period larger than two years, the number of countries drops substantially, an important problem when using multilevel techniques. Nonetheless, the implications of the findings of this study can be extrapolated (albeit with caution).

There is a vast literature that analyzes the intrahousehold distribution of resources (see, for example, Jan Pahl [1983 1995] for Britain; Judith Treas [1993] for the US; Kristen R. Heimdal and Sharon K. Houseknecht [2003] for Sweden and the US).

Single-adult households account for 25.4 percent of the total sample. From the total sample, 47.8 percent of individuals live in households with the same number of adult women and men. Therefore, they do not contribute to the gender gap. Consequently, if we study one-adult households, we are focusing on the main identifiable source of the gender gap.

Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the UK, and the US.

Sweden, Norway, Denmark, Finland, Belgium, France, Germany, Italy, the Netherlands, Switzerland, Australia, Canada, the UK, and the US.

Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, the Netherlands, Norway, Spain, Sweden, Switzerland, the UK, and the US.

Sweden, Norway, Denmark, Finland, Australia, Belgium, the Netherlands, France, Germany, Switzerland, Australia, Canada, Ireland, the UK, and the US.

As Dewilde (2008) argues, the reasons for this are twofold. First, most authors point to the considerable variations among countries belonging to the same regime cluster, leading them to conclude that it may be essential to incorporate country-specific features into the analysis (Bertrand Maitre, Brian Nolan, and Christopher T. Whelan 2005). Second, in order to formulate meaningful policy recommendations, we need to know what policies are related to which individual outcomes, preferably controlling for other possible explanations such as differences among countries in terms of the characteristics of the population. Therefore, we need to study specific indicators of the welfare state.

Dewilde (2008) points out the link between the different parts of the welfare regime, where the strongest could be represented by the relationship between the welfare state (sensu stricto) and the labor market. As he describes, the labor market is generally quite flexible in the liberal welfare regime, but this is much less so in continental Europe. In social-democratic countries, the bargaining process between unions, employers, and governments has resulted in a certain amount of “controlled” flexibility. However, this is not the case in socially conservative and southern European countries. Moreover, due to strict labor market regulations in these areas, there has been an increase in “informal” flexibility, namely illegal employment (Gøsta Esping-Andersen 1999).

The GDP of each country is measured as GDP per capita in Purchasing Power Standards (PPS) of each country in relation to the EU average set to equal 100.

We drop countries in the dataset for which information on some of the variables used is missing (mainly the marital status and level of education), or the number of observations is limited. These countries are: Bulgaria, Cyprus, Estonia, Greece, Iceland, Lithuania, Latvia, Romania, Slovenia, and Slovakia.

We have followed the EUROSTAT recommendations in choosing the poverty line. We consider the whole population, not only singles, to measure the median income and therefore the poverty line. A sensitivity analysis using the 50 percent of the median income produced similar results.

The income categories at the individual level are gross employee cash or near cash income, company car, gross cash benefits or losses from self-employment (including royalties), unemployment benefits, old-age benefits, survivor benefits, sickness benefits, disability benefits, and education-related allowances, while income categories at the household level are income from rental of a property or land; family/children-related allowances, social exclusion not elsewhere classified, housing allowances, regular interhousehold cash transfers received; interest, dividends, profit from capital investments in unincorporated business; income received by individuals under age 16; minus regular interhousehold cash transfer paid; regular taxes on wealth; tax on income; and social insurance contributions.

This scale assigns a value of 1 to the first adult in the household, 0.5 to each remaining adult, and 0.3 to each member younger than age 14.

We refer to the following European countries: Austria (AT), Belgium (BE), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Poland (PL), Portugal (PT), Slovakia (SK), Slovenia (SI), Spain (ES), Sweden (SE), and the UK (UK).

They include income support, which means periodic payments to people with insufficient resources. Conditions for entitlement may be related not only to the personal resources but also to nationality, residence, age, availability for work, and family status. They also include other cash benefits, such as support for destitute and vulnerable persons to help alleviate poverty or assist in difficult situations. These benefits may be paid by private nonprofit organizations.

EU- 27 is composed of all of the countries in EU-25 plus Bulgaria (BG) and Romania (RO).

In this case, the odd is 1.23 and is statistically significant.