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”.

The Luxembourg Income Study provides an invaluable source of income-surveys that are made compable across countries and over time. Not all the measurements of income are directly comparable, however. In some datasets the income variables were measured gross of income taxes and social contributions, whereas in other datasets they were measured net of income taxes and social contributions. Researchers seeking to do comparative analyses using the LIS will have to account for this difference between net and gross datasets.

In a new publication, we present netting down procedures, which are statistical tools that help improve the comparability of net and gross datasets in LIS. The paper discusses the issues involved with comparing net and gross income data, as well as the assumptions that are required when applying a netting down procedure. Two netting down procedures are discussed, and their performance in reducing bias is evaluated. The paper was co-authored by Rense Nieuwenhuis (that’s me – Institute for Innovation and Governance Studies (IGS), Universiy of Twente), Teresa Munzi (Data Team Manager and Research Associate of LIS) and Janet Gornick (Director of LIS).

The results indicate that directly comparing data on net and gross earnings (as a specific source of income) introduces bias to the analysis. This was not a surprising finding, because it is well known that progressive tax systems result in net earnings to be lower and distributed more equal than gross earnings. Nevertheless, it underlines the importance of carefully comparing net and gross earnings. Applying the netting down procedures allows users to approximate net earnings based on gross earnings and variables on income tax and social contributions. The paper provides the program code for use with SPSS, Stata, R, and SAS. The results of evaluating these netting down procedures suggest that the application of netting down improves comparative analyses across net and gross datasets in the Luxembourg Income Study.

Our new publication is titled “Netting Down Gross Earnings Data in the LIS Database: An Evaluation of Two Procedures”. The paper was published in the LIS Technical Paper Series, and is available online: http://www.lisdatacenter.org/wps/techwps/6.pdf

Last week, I was invited to present my dissertation research during the LIS Summer Workshop. My lecture was titled “Family Policies, Women’s Earnings, and Between-Household Inequalities: Using LIS for comparative analyses“. It consisted of three parts.

The first part of my lecture dealt with my argument to combine institutional and demographic explanations of women’s employment. I differentiate between two types of family policies, and how these affect women’s employment. These two types of family policies are reconciliation policies and financial support policies to families. Reconciliation policies were found to stimulates the employment of specifically mothers, thereby decreasing the employment gap between mothers and women without children. Financial support policies to fmailies with children, on the other hand, were found to increase this motherhood-employment gap.

Secondly, I have answered the question to what extent – and in what direction – women’s increased earnings have affected earnings inequality between households. Put simply: women’s earnings attenuate the earnings inequality between households. Moreover, reconciliation policies were found to stimulate women’s employment in such a way, that her attenuating contribution to household inequality was stronger, while financial support policies suppress this attenuating effect. This means that a family policy-context facilitating women’s employment contributes both to smaller inequalities within households, as well as between households.

The third part of my lecture was technical in nature, and specifically addressed comparative analyses using the LIS database. I presented a ‘netting down’ tool that may assist in comparing net and gross earnings data in the LIS database. Evaluations of the performance of this netting down tool suggest that netting down improves the quality of comparative analyses, but residual bias (between net and gross datasets) remained.

Presenting at the LIS Summer Workshop was an amazing experience, with attendants asking smart and constructive questions. I learned a lot from the experiernce, myself. The slides of my presentation are available upon request (r.nieuwenhuis@utwente.nl).

The premise of my project was something that is commonly believed amongst sociologists – and something I took for granted for many years. I even remember when I first learned about it during a first-year course on inequality. Simply put: because spouses’ earnings are positively correlated, the earnings inequality between households is thought to be bigger than the earnings inequality between individuals. Intuitively, this makes sense: it is easy to imagine how the earnings gap between households with two top-earners and households with two low-income spouses is quite big. Recently, a new book by Esping-Andersen (The incomplete revolution) is getting quite some attention, and is reporting on how increased women’s earnings have contributed to income inequalities between households in several countries.

I thought it would be very interesting to delve into this issue more, and try to analyze differences between countries in the degree to which women’s earnings affects the inequality between households in these countries. Interestingly, though, once I started working seriously on the project, it quickly became clear that women’s earnings attenuate – rather than increase – inequalities between households. Virtually all authors analyzing the contribution of women’s earnings to household inequalities report this attenuating affect, and do so for various countries and for different points in time. So, the common conception that women’s earnings generally increase inequalities, turned out to be a misconception. No need to be concerned of this unintended consequence of women’s increased labour force participation.

So, I had to revise my plan. I turned my attention to a systematic review of the literature with a special focus on how it is possible that spouses’ earnings are positively correlated (which, indeed, they are), but that when women’s earnings are high the inequalities between households tend to be reduced. I won’t spoil the anticipation by disclosing my results here (but please, do contact me if you want to be informed when these results become available), but I figured it out. Also, I am still working on a systematic analysis comparing countries with very interesting preliminary results (again, no spoilers).

This concludes the most technical part of this series of blogs on my New York experiences. Tomorrow some notes on how PhD students are trained in New York.

As said, the main reason I was in New York was to do research. Since my thesis is about the effectiveness of family policies, I wanted to work with an expert on this topic. It is difficult to think of someone who is more knowledgeable on this topic, and more experienced in doing high quality empirical studies, than prof. Janet Gornick. I was very enthusiastic that she agreed with me visiting her in New York for a couple of months, and that she was willing to supervise me, as well as to co-author a paper. Moreover, Janet Gornick is also the director of LIS (formerly known as the Luxembourg Income Studies).

LIS is a cross-national data center, located in Luxembourg.
LIS is home to the Luxembourg Income Study Database and the Luxembourg Wealth Study Database. These databases contain harmonised microdata from high- and middle-income countries around the world.

Their mission is to

… to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes.

Basically, this means that the LIS is a remarkably valuable source of data for my thesis, which is inherently country-comparative in design. And, indeed, the LIS proved to be a very detailed, well documented, and very carefully harmonized source of data. To work with these data, together with the director of LIS, was an inspiring experience. Moreover, the graduate center of the City University of New York (CUNY) invited me over as an Advanced Research Collaborative (ARC) Fellow, which was a great honor.