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To explain single-mother poverty, existing research has either emphasized individualistic, or contextual explanations. Building on the prevalences and penalties framework (Brady et al. 2017), we advance the literature on single-mother poverty in three aspects: First, we extend the framework to incorporate heterogeneity among single mothers across countries and over time. Second, we apply this extended framework to Germany, the United Kingdom and Sweden, whose trends in single-mother poverty (1990–2014) challenge ideal-typical examples of welfare state regimes. Third, using decomposition analyses, we demonstrate variation across countries in the relative importance of prevalences and penalties to explain time trends in single-mother poverty. Our findings support critiques of static welfare regime typologies, which are unable to account for policy change and poverty trends of single mothers. We conclude that we need to understand the combinations of changes in single mothers' social compositions and social policy contexts, if we want to explain time trends in single-mother poverty.

Over the last 10 years at-risk-of-poverty rates across Europe have been rather stable or rising only slightly. However, certain demographic groups face comparatively high poverty risks. Lone mothers belong usually to the most affected groups by income poverty - but variations are striking. Though, still little research has been done for explaining this vast variation across Europe. It is argued that institutional arrangements in the labor market and the welfare state shaped by existing gender inequalities have an impact on lone mothers' poverty risks. For instance, in countries where women's access to (full time) paid work is low and/or the gender pay gap is high, lone mothers are particularly disadvantaged due to the absent (male) partner. Furthermore, the lack of public childcare and a gendered eligibility to social benefits aggravate lone mothers' poverty risk. I also hypothesize that gendered institutional arrangements mediate the effect of individual characteristics on lone mothers' poverty risks - namely the poverty-reducing effect of employment and the poverty-enhancing effect of children. To prove these hypotheses empirically, I compare 25 European countries running several multi-level models based on pooled EU-SILC data (2009-2012). Results show that existing gender inequalities - particularly the access to full time employment for women and gender-specific welfare eligibility - indeed account for country differences in the level of lone mothers' poverty risk. Furthermore, there is empirical evidence that gender inequalities in the labor market shape the poverty-reducing effect of full time employment. Other specific mechanisms modeled in form of cross-level interactions cannot be supported by the data.

Considerable attention focuses on the risks of poverty, defined as individual-level labor market and family characteristics more common among the poor than the non-poor. This article first develops a framework for analyzing the risks of poverty in terms of prevalences (share of the population with a risk) and penalties (increased probability of poverty associated with a risk). Comparing the four major risks (low education, single motherhood, young headship, and unemployment) across 29 rich democracies, we show there is greater variation in penalties than prevalences. Second, we apply this framework to the U.S. We show that prevalences cannot explain high U.S. poverty as the U.S. has below average prevalences. Rather, the U.S. has high poverty partly because it has the highest penalties. U.S. poverty would decline more with crossnational median penalties than cross-national median prevalences, and U.S. poverty in 2013 would actually be worse with prevalences from 1970 or 1980. Third, we analyze cross-national variation in prevalences and penalties. We find very little evidence that higher penalties discourage prevalences, or that lower penalties encourage prevalences. We also show welfare generosity significantly moderates the penalties for unemployment and low education. We conclude with three broader implications. First, a focus on risks is unlikely to provide a convincing explanation or effective strategy for poverty. Second, despite being the subject of the most research, single motherhood may be the least important of the risks. Third, for general explanations of poverty, studies based solely on the U.S. are constrained by potentially large sample selection biases.

Considerable attention focuses on the risks of poverty, defined as individual-level labor market and family characteristics more common among the poor than the non-poor. This article first develops a framework for analyzing the risks of poverty in terms of prevalences (share of the population with a risk) and penalties (increased probability of poverty associated with a risk). Comparing the four major risks (low education, single motherhood, young headship, and unemployment) across 29 rich democracies, we show there is greater variation in penalties than prevalences. Second, we apply this framework to the U.S. We show that prevalences cannot explain high U.S. poverty as the U.S. has below average prevalences. Rather, the U.S. has high poverty partly because it has the highest penalties. U.S. poverty would decline more with crossnational median penalties than cross-national median prevalences, and U.S. poverty in 2013 would actually be worse with prevalences from 1970 or 1980. Third, we analyze cross-national variation in prevalences and penalties. We find very little evidence that higher penalties discourage prevalences, or that lower penalties encourage prevalences. We also show welfare generosity significantly moderates the penalties for unemployment and low education. We conclude with three broader implications. First, a focus on risks is unlikely to provide a convincing explanation or effective strategy for poverty. Second, despite being the subject of the most research, single motherhood may be the least important of the risks. Third, for general explanations of poverty, studies based solely on the U.S. are constrained by potentially large sample selection biases.