This discussion paper provides an updated analysis of gendered economic inequality in high- and middle-income countries. A review of the literature demonstrates that such an analysis needs to explicitly recognize that gender, poverty, and (economic) inequality are intrinsically linked. Specifically, the paper addresses two sets of questions:

• First, how do intra-family resource allocation and distribution patterns both reflect and shape gender inequalities in power and well-being, and what factors—including policy-related ones—can mitigate these inequalities?
• Second, how do families as gendered institutions contribute to broader socio-economic inequalities, and what can be done to reduce/reverse these inequalities?

Using data from the LIS Database, this paper shows considerable differences among 42 countries with respect to how likely women were to have their own income. The period from 2000 to 2010/2014 saw increasing rates of own incomes as well as women’s incomes constituting larger shares in total household income. A key finding is that, in countries where many women have an income of their own, relative poverty rates are lower.

The comparative analyses, combined with a review of the literature, suggest that welfare state arrangements that support working women not only improve the overall employment rates of women but also help to prevent particularly women in low-income households from living in dependence and instead to have an income of their own—thus reinforcing the potential for poverty reduction. Moreover, institutional contexts that are generally conducive to women’s employment tend to be effective across family forms.

I was a great pleasure to work with the excellent LIS team on this project, and an honour to prepare this report commissioned by UN Women (the United Nations organization dedicated to gender equality and the empowerment of women). This paper was produced for UN Women’s flagship report, “Progress of the World’s Women 2019”.

This project examines how the rise of women’s employment and earnings affected trends in economic inequality among all households, across OECD and European countries since the 1980s. So far, prominent explanations of economic inequality have neglected the potential impact of women’s rising earnings on inequality among households, even though it is one of the most profound developments in economic activity in recent decades.

This project theorizes and analyzes how trends in women’s employment and earnings affected vertical inequality: the extent to which household incomes differ. For economic inequality it matters a great deal whether the rise of women’s employment and earnings was predominantly among singles and single mothers, among women living in couples, or among households with additional earners that already were close to the top (or bottom) of the earnings distribution. In this project, I also study how institutional contexts shape employment and earnings of women across diverse households.

This proposed theory will be rigorously tested using state-of-the-art quantile regression techniques and longitudinal data from EU-SILC and LIS, combined with high quality indicators of institutional context. Empirical studies address four areas of particular interest: (A1.) family diversity including single parents, (A2.) causal inferences, and the impact of the institutional context that is characterized both by (B1.) family policy and (B2.) social security.

Will the Sverigedemokraterna become the largest party in Sweden? The best prediction we have: probably not. Although polls are not perfect, several recent polls independently estimate that the Sverigedemokraterna will win about 18% of the votes, with an error margin of about 2%. They may gain a so-called curtain bonus (people are hesitant to say they will vote for the Sverigedemokraterna to pollsters, but will do so behind the curtain of the voting booth), but are pretty far behind the largest party in the polls (the Social Democratic Party, at around 25%). Yet, of course, we all remember the polls predicting Hillary Clinton to win the presidential election …

At the very least, it does seem safe to say that the radical right will become an (even more) influential faction in Swedish politics. Having played only a marginal role in the years after their foundation in 1988, the Sverigedemokraterna won 3% of the votes in the national parliamentary elections in 2006, about 7% in 2010, and 13% in 2014. Polls suggest their support has been growing since, with a particularly marked rise during the 2015 refugee crisis. Tonight or tomorrow we will know how much they will have grown in 2018.

There is resistance, as is to be expected. In its most basic form, most people plan to vote for different parties, and most parties pledged they will not form a coalition with Sverigedemokraterna. Other forms of resistance, based on what I have seen and heard in Stockholm, include besmirching posters of the Sverigedemokraterna with swastikas and (what looks like) excrement, linking them to their roots of self-identification with the Nazi’s, calls for a ban on demonstrations for related (and far-right) groups, and semi-serious advertisements to remind voters to go and vote Sverigedemokraterna on Monday – the day after election day. I know these things happen in all elections, but I think it is an affront to the intelligence of all voters, including those voting for the Sverigedemokraterna. Stigmatizing people who vote for Sverigedemokraterna does not take seriously their political concerns and challenges in life.

A major driving force behind the growing support for the Sverigedemokraterna is rising economic inequality. That’s right: inequality, not immigration. Even though concerns about immigration are often cited by people voting for Sverigedemokraterna, this cannot explain why support for this party has been rising specifically during the last decade. Sweden has a tradition of welcoming refugees and other immigrants that goes back a long time, and previously that did not lead to support for the radical right. A recent study (not yet peer-reviewed) indeed showed that a rise of inequality in Swedish municipalities, and not the number of immigrants, explained rising support for Sverigedemokraterna.

Inequality is rising profoundly in Sweden. In fact, of all the rich countries in the OECD, economic inequality was rising fastest in Sweden. And people are saying they struggle. They have difficulties finding affordable public housing. The social safety net is gone. For many, their pension is too low. No wonder that populists can convince voters that immigrants occupy ‘our’ houses, plunder ‘our’ safety net, and that ‘we’ have to choose between immigrants or pensions. No wonder, but in fact these concern have to do with politics – little with immigration. Public housing agencies made huge profits by selling substantial parts of their housing stock in the private market. The center-right government of 2006 substantially reduced levels of unemployment benefits, made it so that fewer people qualify for unemployment benefits, and gave tax benefits to the working. Intentionally, this government increased the income differences between working ‘insiders’ and ‘outsiders’ without a (secure) job. Poverty among pensioners is rising indeed, which is a direct result of pension privatization led (in important parts) by the social democrats in 1998. However, as pension rights accumulate over decades, the consequences of this pension reform are only now becoming apparent. These are just examples in the areas of housing, unemployment benefits, and pensions, but all took place long before the 2015 immigrant crisis that lent support to the Sverigedemokraterna.

Democracy is not for the faint of heart. Many voters, as well as the established parties vehemently disagree with the Sverigedemokraterna. And that is legitimate. Yet, no matter how strongly one disagrees with the solutions proposed by the Sverigedemokraterna, the problems faced by their electorate are real and should be taken seriously. Many face an insecure future and have difficulties to make ends meet, which in part is the direct result of political decisions made by the establishment. If the establishment does not listen, they stand to lose far more than today’s elections.

This week, Laurie Maldonado and myself are very proud to be guests on the podcast, to talk about our book The Triple Bind of Single-Parent Families. I don’t often find myself in a radio studio in Washington DC, and it was a great experience. The host Rebecca Vallas was smart, witty and so well prepared. She was very supportive, and I love what she wrote on the Triple Bind:

The U.S. has long demonized single parents – and especially single moms – like nowhere else in the western world. A new global anthology of research on treatment of families and single parents called The Triple Bind of Single-Parent Families offers a damning critique not of single moms, but of how the U.S. is hanging them, and their families, out to dry.

You can listen to our interview on Off Kilter (and subscribe to the always excellent podcast!) everywhere good podcasts are served, including:

• Itunes
• Soundcloud

Or simply listen to it here:

Abstract

It is demonstrated that family policies are an important aspect of the institutional context of earnings inequality among coupled households. Although seldom integrated into prominent analyses of economic inequality, women’s earnings are consistently found to reduce relative inequality among households. This means that family policies, as well-known determinants of women’s employment and earnings, are important contextual determinants of economic inequality. Using Luxembourg Income Study data from 18 OECD countries in the period 1981–2008, this study demonstrates that women have higher earnings, and that their earnings reduce inequality among coupled households more in institutional contexts with generous paid leave and public childcare. We found no sizeable association between financial support policies, such as family allowances and tax benefits to families with children, and the degree to which women’s earnings contribute to inequality among coupled households. Family policy arrangements that facilitate women’s employment and earnings are associated with less economic inequality among coupled households.

Nieuwenhuis, R., Need, A. & Van der Kolk, H. (2018). Family policy as an institutional context of economic inequality. Acta Sociologica. Forthcoming, online first: http://journals.sagepub.com/doi/full/10.1177/0001699318760125

Of course, all credit for winning matches goes to the players and their coaches. Popularity of (women’s) football in a country surely is important for being able to draft good teams. Training facilities, strategies, and all kinds of football-related factors will be of great importance, but those should be analysed by someone who actually knows something about football.

Instead, I decided to have a look at three factors that are not (directly) related to football. Gender (in)equality, first, represents women’s opportunities in a country. If inequality is high, fewer women may have the opportunity to play football, let alone to do so professionally. The size of a countries’ population, secondly, will facilitate drafting better players simply because in these countries there are more women who may discover to have talent for football. Finally, I look at how ‘rich’ a country is: richer countries may be able to provide better support to their teams, support (more) professional teams, and perhaps have more youth teams. The story came out a bit technical, but bear with me.

To test these ideas, I used data on the results of all matches played in Women’s Euro 2017 (including the qualification matches, but given the time of writing without the final). I used data on each match twice, once to assess the likelihood that team A would win, and once for team B. More sophisticated analyses would simultaneously account for characteristics of both teams in each match, as well as the structure of the tournament, but for now this should do. I then estimated a multilevel (logistic) regression model of the likelihood that each team would win their matches with random intercepts for each country (one might interpret these random effects as the latent capability of each team). Data from the United Nations were obtained on their Gender Inequality Index (from the Human Development Reports), population size, and GDP per capita. The latter two were logged and standardised. Some additional datapoints, for instance on Wales and Scotland, were obtained from wikipedia. Andorra and the Faroe Islands were removed due to missing data. It should be stressed that this is a very simple analysis, done for fun, and results should be interested with a grain of salt and certainly without causality.

The results are presented in the Table below. Model 1 is just a baseline model to estimate how much countries differ in their likelihood to win matches (represented by the random intercept variance, to which I’ll return later). Model 2 shows that countries with higher gender INequality have a lower likelihood of winning matches. Model 3 shows that countries win more matches when they have a larger population and a higher GDP per capita. The effect of gender inequality now vanishes (this is due solely to adding GDP to the model, not shown). This is easily explained: in more gender equal societies more people contribute to the formal economy, thus boosting GDP per capita. Thus, gender equal countries have performed better on Women’s EURO 2017 in part because their level equality made this countries more prosperous.

Finally, Model 4 shows that the effect of a higher GDP per capita are weaker in more gender unequal societies. In other words, the benefits that rich countries have only benefit women’s teams in Euro 2017 if these countries have an adequate level of gender equality. This interaction is shown in the Figure below. Countries that score higher than 0.2 on the gender inequality index (about the level of Latvia and Kazakhstan) have no benefit of an increase in their GDP per capita.

The Table also showed the random intercept variance to represent how much countries differed in their capability to win matches. In the baseline model this was estimated to be .99. The absolute number doesn’t mean that much, but when gender inequality is accounted for in model 2, the number is almost halved to .55. This means that levels of gender inequality explain almost half of the differences in countries’ performance in Women’s Euro 2017. Also accounting for population size and GDP per capita (model 3) further reduces the random intercept variance to .13, and the interaction between GDP and gender inequality leaves the variance at .06. This means that with these 3 variables, 94% of differences between countries’ performance can be explained.

One important take-away from these models is that the likelihood that a national team did well in Women’s Euro 2017 was determined by (/associated with) to a very large extent with structural factors that are not directly related to football. Another is that gender equality plays a major role.

Will the models tell us who will win tonight? No, for that purpose more detailed models would be required. The figure below shows the random intercepts (i.e. the latent capability of each country to win matches) as estimated for each country. The circles show the baseline estimates, indicating how well each team did during the tournament (for those interested, the triangles show how countries would have performed had it not been for their level of gender inequality. Generally, countries that did well would have done less well had it not been for their high level of gender equality. Romania and Russia, for instance, would actually have performed better if these countries had better gender equality.). So far, the Netherlands have done slightly better than Denmark (in part, of course, by the Netherlands beating Denmark earlier in the tournament). Yet, England is estimated to have done better than the Netherlands, and Germany better than Denmark (remember that these data also include the qualifying phase of the tournament). Evidently, both England and Germany are out already (eliminated by the Netherlands and Denmark, respectively) which indicates that there are plenty of things these models do not account for. Teams ‘growing’ into the tournament being one, and both the Netherlands and Denmark seem to have done so.

What these analyses do suggest, is that Denmark and the Netherlands would not have been final had these not been rich countries with high levels of gender equality. For the rest, who will win tonight is up to the players.

In this period, women’s share of household earnings grew, spouses’ earnings became more strongly and positively correlated in various countries, and inequality in women’s earnings was reduced. Inequality in household earnings increased due to the rising correlation between spouses’ earnings, but was reduced more by the decline of inequality in women’s earnings.

Had women’s earnings remained unchanged since the 1970s and 1980s, inequality in household earnings would have been higher around 2010 in all observed OECD countries. Household inequality was reduced least by trends in women’s earnings in countries with a long history of high female labor force participation, such as Finland (3% reduction) and Sweden (5%), and most in countries that observed a stronger increase in female labor-force participation in recent decades such as Spain (31%) and the Netherlands (41%).

As more countries are reaching a plateau in the growth of women’s employment and earnings, the potential for further stimulating women’s employment and earnings to counter both women’s and household inequality seems to be increasingly limited.

Nieuwenhuis, R., van der Kolk, H., & Need, A. (2017). Women’s earnings and household inequality in OECD countries, 1973–2013. Acta Sociologica, 60(1), 3–20. http://doi.org/10.1177/0001699316654528

The book, however, leaves the topic of gendered inequality largely unaddressed. Indeed, Milanovic discusses why an exclusive focus on horizontal inequality (inequality between groups, including gendered inequality) is undesirable, because it may lead to unproductive identity politics in relation to specific horizontal inequalities, and because it does not address the root cause of inequality. Yet, while relevant, these arguments do not convince that a greater emphasis on gendered inequalities would not have been informative regarding the measurement and explanations of global inequality. Below, I list three reasons why including a focus on gender can improve our understanding of trends in global inequality.

First, the analyses presented in ‘Global Inequality’ seem to implicitly assume that all income is shared equally within the household. Indeed, incomes are equivalised to account for differences in household size and composition, but then it is assumed that there is no inequality within households in the degree to which women and men have equal access to, and control over, how to spend the household income. Admittedly, there is not so much empirical research that does account for such differences (Cantillon, 2013), but a literature on this topics seems to be emerging and indicating that women typically have less access to, and control over, household income (Bennett, 2013). Not accounting for this likely leads to understating levels of global inequality among individuals.

Secondly, the level of economic inequality between women and men is intrinsically linked to levels of inequality among households (Lam, 1997). Milanovic discussed how homogamy drives up inequality among households. This is true indeed, but the resulting correlation between partners’ earnings is typically quite low. In a recently published study, Nieuwenhuis Need, and Van der Kolk (2017), focusing on OECD countries from 1973 to 2013, showed how women’s rising earnings were indeed associated with a somewhat higher correlation between spouses’ incomes. But the same trend was also associated with a substantial decrease in inequality among women (living in coupled houseohlds). So, while inequality in household income increased due to the rising correlation between spouses’ income, it was reduced more by the decline of inequality in women’s incomes. Thus, the net effect has been that women’s rising incomes were a driving force reducing inequality among households – at least in rich democracies in recent decades.

Thirdly, levels of gender (in)equality vary substantially across countries and over time – even when just limiting our focus to economic inequality. Trends towards gender equality have been observed to stagnate in various countries (including the Nordic countries, where women’s employment rates have been comparatively high for a long period already) or even reverse like in the United States (Boushey, 2008). If inequality is rising in these countries, as shown by Milanovic, this could be related to stagnating gender inequality. At the same time, in other countries there is much more potential for further reducing household inequality by means of promoting gender equality. Furthermore, women’s (rising) incomes have contributed substantially to countries’ average income levels. On the one hand this means that countries in which trends towards gender equality are stagnating may see less growth in average income levels. On the other hand, it means that countries with high levels of gender inequality (in terms of economic participation) have the opportunity to foster growth in average incomes by stimulating women’s (equal) participation on the labour market. To the extent that these countries are poorer, such as China and India, promoting economic gender equality will thus also help these countries to catch up with the average income levels in richer countries – thus reducing global inequality.

Whether and to what extent trends in gender equality will affect future trends in global inequality remains an empirical question. But, together these arguments demonstrate that gender (in)equality is a driving force of inequality both within nations and between nations. Now, these points of critique are easily reaised, but very difficult to empirically substantiate (or refute). I don’t think Milanovic has the data to do so, and neither do I have them. In fact, I don’t think such data exists for a substantially long period of time. Yet, I think these comments are important to keep in mind when interpreting the evidence on long-term trends in global inequality, and when thinking about questions that beg answering in future research.

References

Bennett, F. (2013). Researching Within-Household Distribution: Overview, Developments, Debates, and Methodological Challenges. Journal of Marriage and Family, 75(3), 582–597. http://doi.org/10.1111/jomf.12020

Boushey, H. (2008). “Opting out?” The effect of children on women's employment in the United States. Feminist Economics, 14(1), 1–36. http://doi.org/10.1080/13545700701716672

Cantillon, S. (2013). Measuring differences in living standards within households. Journal of Marriage and Family, 75, 598 – 610. (online)

Lam D (1997) Demographic variables and income inequality. In: Rosenzweig M and Stark O (eds) Handbook of Population and Family Economics. Amsterdam; New York: Elsevier, pp.1015–1059.

Milanovic, B. (2016). Global inequality: A new approach for the age of globalization. Harvard University Press. (Publisher’s website)

Nieuwenhuis, R., van der Kolk, H., & Need, A. (2017). Women's earnings and household inequality in OECD countries, 1973–2013. Acta Sociologica, 60(1), 3–20. http://doi.org/10.1177/0001699316654528

If you happen to be in New York and are interested in attending this talk, please contact me. There might be some ‘tickets’ available.

From the announcement:

Women’s employment rates have risen markedly across OECD countries in recent decades, although evidence is mounting that this trend is stagnating. Rense Nieuwenhuis will discuss how these trends have affected earnings inequality within and among coupled households, as well as poverty rates. His research is based on LIS data to cover OECD countries for about 3 decades. In his talk, he will also relate his findings to current policy developments in Europe.

Rense is a sociologist interested in how the interplay between social policies and demographic trends gives rise to economic inequalities. His publications appeared in the Journal of Marriage and Family and the European Sociological Review, among other journals. In 2014 he obtained a Phd (‘Cum Laude’) from the University of Twente in the Netherlands, and currently he is an assistant professor at the Swedish Institute for Social Research (SOFI).

Light refreshments will be provided. After the talk, all are welcome to join us for a social gathering at Bryant Park. 

I think not, but these arguments were actually made recently in the Dutch public debate on women’s employment (). Against this background, a website on Social Problems in the Netherlands, called socialevraagstukken.nl and initiated by a variety of established research organisations, invited me to write a piece based on my dissertation. The piece, which is in Dutch, was published today and can be found online. In line with the goals of the website, I tried to stick to the facts – hoping to counter some fact-free-opinions similar to those reproduced above.

The core of my argument is that there (still?) are systematic differences in how Dutch men and women respond to having their first child – with 37% of first time mothers deciding to stop being employment or reducing their hours, compared to 7% of young fathers.

In my dissertation I found that mothers were less likely to be employed than women without children, which I called the motherhood-employment gap. The size of this motherhood-employment gap was found to vary over time and across OECD countries. Institutional explanations of this empirical regularity were tested. In addition, it was examined how women’s earnings affected earnings inequality between households.

My dissertation led to the insights that reconciliation policies stimulate women’s employment by closing the motherhood-employment gap, increase women’s earnings, and reduce inequality among women and between households. Overly long childcare leave decreases women’s employment, and higher educated women benefit more than lower educated women from (paid) leave. Financial support policies to families with children increase the motherhood-employment gap, reduce women’s earnings, and increase inequality among women and between households.