Gender inequality in COVID-19 times: An interview with Professor Climent Quintana-Domeque

The effects of the COVID-19 pandemic have been felt across all aspects of daily life in the UK. Consequently, there has been a big increase in the amount of research being conducted that is examining direct health implications of the pandemic, as well as downstream ramifications such as the effect on businesses and individuals' social life. However, one impact of the pandemic that has received less attention is the potential differential impact of the pandemic on men and women.

I recently had the chance to sit down with one of the most influential researchers in this space, Climent Quintana-Domeque, PhD, a professor of economics at the University of Exeter, a research fellow at the IZA Institute of Labor Economics, a fellow of the Global Labor Organization, and one of the editors of the Oxford Bulletin of Economics & Statistics. We discussed his latest paper ‘Gender Inequality in COVID-19 Times: Evidence from UK Prolific Participants’ as well as his research more broadly.

Hi Climent, thanks so much for taking the time to talk with me. I wonder if we could start off with you giving me a brief description of your main area of research?

I am essentially an applied economist and I work on health, labor, family, and development economic issues. I'm interested in social science questions, and the way that economists like myself typically look at these types of questions is by trying to understand behavior, how people interact, how people make decisions, and how people are affected by different things such as the markets, policies, and their daily interactions with others. During this pandemic, I have been doing a lot of work on understanding how the pandemic has affected different groups in the population.

How did you get started in this area and what are the main questions you are trying to answer with your research?

When I was an undergraduate I was really interested in labor economics decisions, for example, my undergraduate thesis examined how the minimum wage can affect educational decisions of individuals. However, as my career progressed I became more interested in how economic conditions can affect individual’s and families health and wellbeing, for instance, when economic conditions are good then people are more likely to be healthy and less likely to succumb to disease. This has led me to my current work at the intersection of the health and labor economics perspectives.

Recently, I have been thinking about two main questions. The first one is - what are the key determinants of children’s wellbeing? I have done a lot of research looking at the impact on a child if the mother experiences a shock such as an economic crisis, a natural disaster, or terrorist-related activity whilst the child is still in-utero. By way of an example, in one study we examined the economic crisis in Argentina in 2001-2, the first hurricane that hit Brazil in 2004, and terrorist activity in Spain between 1980-2003, and found that children who were in-utero during these events tended to have worse birth-outcomes, including a lower birth weight, which we know from other studies can drive lower educational attainment and lower earnings later in life. I am very interested in being able to infer the actual causal effect of being exposed to these negative shocks at this critical stage of life.

I am also interested in how individuals match in the so-called ‘marriage market’. Humans make many so-called ‘market’ decisions about factors such as what is the best job for us, and who are the best partners for us. While job choices are clearly based on an economic market, choices in partners have no explicit ‘price’, so I have been working on examining the key characteristics that matter for people to match to each other. We have worked on developing theoretical and empirical frameworks to understand this from multiple dimensions. At the end of the day, we're interested in understanding how families actually form, because this is going to have implications on wellbeing, and especially on the wellbeing of the children in these families.

That sounds like a really fascinating area to work in. I wanted to talk specifically about your recent paper regarding gender inequality during COVID that you ran on Prolific. I thought it was absolutely fascinating, but also gave significant cause for concern. I was wondering if you could take me back to the inception of that paper and tell me how you first came up with the idea of looking specifically at gender inequality during COVID?

We decided to implement this piece of research around mid-May 2020, about two months after the first nationwide lockdown in the UK.

At that point it was clear that we were seeing differential effects of the pandemic in different social groups in the UK and there was also research from the U.S. alerting that the pandemic would have unequal consequences in society. It is also well-known that women typically take on more household responsibilities, such as childcare and housework, than men, so it seemed natural to expect that the consequences of the pandemic and the associated lockdown would impact men and women differently. We therefore set out to try to document the situation regarding men and women in the UK.

We wanted to focus on two key components. The first was whether the concerns about the economic and health implications of the pandemic were the same for men and women. To that end we decided to ask participants questions regarding their level of concern about (a) the economic situation created by the pandemic, and (b) getting and spreading the virus, as well as its lethality. The second factor we investigated was whether mental wellbeing differed between the two groups. We wanted to take a holistic approach to this aspect of the work so we included a number of measures designed to examine mental wellbeing, such as instruments to measure anxiety and depression. We were also interested in examining how these two components related to one another.

Another big part of this study was an examination of how the labor responsibilities of men and women changed due to the pandemic and associated lockdown. We therefore asked participants about the number of hours they worked in the labor market (i.e., outside the home) and the number of hours worked in the non-labour market (i.e., in the home) at that exact point in time and also three months prior.

Can you describe to me the main findings of the study?

Let's start with the picture in June 2020. What we observed is that women were more concerned than men about getting and spreading the virus, and also perceived the virus as more prevalent and lethal. So in the health concern domain there were these clear dissociations between the groups. In the economic domain, women also had a more negative outlook than men. For example, one of the questions asked participants to forecast unemployment rates in June of that year (2020), after six months, and after one year. What we observed was that women systematically reported a worse economic situation in that they expected a much higher unemployment rate than men do both in June, 2020, but also in December, 2020, and in June, 2021. Importantly, all participants were given factual information about the unemployment rate in March 2020 meaning that different predictions of unemployment going forward could not be due to a lack of information about the current rate.

The other dimension that we looked at is mental health. We measured mental health using a number of different indicators and found clear evidence of a gender gap in mental health, with women being in a worse situation in terms of mental health than men. This was apparent on any measure we used, including the generalized anxiety scale (GAD-7), reported anxiety attacks in the last two weeks, and a depression indicator based on the patient health questionnaire (PHQ-9).

That’s really interesting and quite worrying! Given the disparity between men and women in both health concerns and mental health, I'm wondering if you have any kind of intuition on directionality of these effects? Are the differences in health and economic concerns driving the difference in mental health or vice-versa?

This is a very important question. To see if we could find out what is driving the gaps between genders we collected a number of demographic characteristics such as family income, educational attainment, type of job, number of children, or family size, but found that accounting for differences on these variables did not explain to the observed differences in concerns and mental health between the genders. What we did find is that the differences in health concerns between genders partly explained the difference in mental wellbeing. So the fact that women are more worried about getting or spreading the virus seems to explain part of the gap in mental health between men and women, but not all. So the bottom line would be COVID-19 related health concerns rather than economic ones explain part of the gender gap in these different measures of mental health.

What about the comparison of labor responsibilities before and after the first lockdown?

When we looked at time allocation patterns (amount of hours devoted to specific activities), we found that the gender gap in hours of childcare and hours of housework increased regardless of whether we controlled for social demographic dimensions. This means that women were spending more time looking after children and doing housework than before the pandemic, and that this increase was greater than that observed for men.

We also observed that the number of hours of work had decreased more sharply for women than men since the pandemic. So, in effect, what these data show is that the pandemic has amplified inequalities that already existed.

Now obviously we are still in the midst of this pandemic, and currently in a second national lockdown, so I was wondering whether you had any plans to follow-up with this work and see how these findings may have changed over time?

I think that that would be a great idea, but, as an economist, I'm always very concerned about making the right comparisons. One of the issues we have when examining mental health or mental wellbeing is that there could be an issue related to seasonality - it's not the same thing to compare mental health during December or January when there is much less light and so on, to mental health in April or May. So if we do run a follow-up survey we want it to be run in June for a fair comparison. There is actually a literature involved in trying to understand whether the effect of the first lockdown was more like a shock, and then people have since adapted to it, but again, conclusions are a bit difficult because unless you have the data comparing the same month over the years then it's not very revealing. So it's a bit tricky, but it’s something that I’m definitely interested in examining in the months and years to come, lets see if we can get the funding!

Great, I'd be fascinated to read a follow up, as I don't have a strong intuition about how these data would have changed, but it'd be interesting to find out! My final question is if there's one thing to come out of this study, one impact that it could have, what do you hope that would be?

I think there are two ways of thinking about that. One is making sure that, when thinking about policies, gender plays a role.

Policies can no longer be blind with respect to gender, because it's clear that there are differences in terms of who spends more time on average with the kids or with household production. Therefore, when we think about the lockdown, the consequences are going to be different for men and women and it's important to consider which types of policies can be used to compensate for these differential negative effects.

In terms of research, I hope this work highlights that it's important for researchers to spend more time thinking about modeling and understanding what is happening in the household. These models can inform us about the consequences of economic and health shocks, like the pandemic, and help us to understand who is going to be more or less affected. Also, in the future, I hope that researchers will aim to collect more data from other groups who have the potential to be negatively affected, for instance, ethnic minority groups. This work shows that it is clearly important to understand inequality and in order to do so we need to gather lots of information for different groups in society.

Thank you Climent, and best of luck with your future research!

Professor Quintana-Domeque tweets at @ClimentQD and uses Prolific to conduct his research, sign up today and join him and 3000+ other researchers doing groundbreaking work using our platfrom.

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