Work

The dynamics of inequality: what have we learned?

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In the final episode of the DIAL podcast we’re looking at what’s been learned from DIAL projects about how and when inequality manifests in our lives and what its longer term consequences might be. We’re joined by Elina Kilpi-Jakonen from the University of Turku in Finland. Elina is the Scientific Coordinator for DIAL and, as the programme draws to a close she reflects on some of the programme’s highlights,  key findings and implications for the future.  

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we’re looking at what’s been learned from DIAL projects about how and when inequality manifests in our lives, and what its longer-term consequences might be. For this final episode of the series, we’re delighted to be joined by Elina Kilpi-Jakonen, from the University of Turku in Finland. Elina is the scientific co-ordinator for DIAL and today, as the programme draws to a close, she’s here to reflect on some of the program’s highlights, key findings and implications for the future. So welcome, Elina thank you very much indeed, for joining us. Now, first of all, I’m guessing it’s been no mean feat and indeed, I know, it’s been no mean feat, keeping an eye across 13 fantastic research projects with researchers based all over Europe. But just take a minute or two, if you would to remind us of what exactly the DIAL programme is and what it’s involved over the last few years.

Elina Kilpi-Jakonen  0:57 

So thanks a lot, Chris. The DIAL programme is, as you said, kind of transnational programme. And we’ve had 13 research projects involved. And all of those involve international collaboration. And it’s based in the social sciences and behavioural sciences, financed by NORFACE, which is a research organisation bringing together different funding institutes across Europe. And so the focus of DIAL has been on inequality and in particular inequality across the life course and trying to understand some of the structures of inequality cross nationally and some of the mechanisms kind of producing inequality and and what that means to people and societies as a whole.

Christine Garrington  1:41 

Wonder if I can ask you why it has been so important to look not just at inequality, per se, as you were saying there, but at how inequality manifests itself over the life course, because this is an important thing, isn’t it? And indeed how, when and where it sort of accumulates?

Elina Kilpi-Jakonen  1:57 

Inequality is a really complex and multifaceted issue. And so I think one one part of it is that inequality comes across in many different domains. So it’s important to take into account inequalities, for example, in education, labour market, health, and so on. And then I mean, to really understand where it comes from and what it means it’s important to look at the determinants across time, I mean, both across time for an individual and their parents, and so on, kind of that life course aspect, but also, for countries to see how it develops across time. Inequality isn’t something that just is, I mean, it develops. And so kind of building on that kind of developmental process to really kind of inform us about how we can do something about it, or how we can really kind of understand where it comes from, it’s important to take that into account.

Christine Garrington  2:58 

Now, you talked about the programme largely being based in the social sciences. But one of the key things about the project is that we’ve seen researchers from different disciplines as well as different countries coming together to try to tackle, as you say, as you rightly say, this incredibly complex area around inequality, what’s been the thinking there?

Elina Kilpi-Jakonen  3:20 

Well, I mean, inequality is something that interests a lot of academics working in different disciplines. And, and they come from it from from kind of different angles. And I think, because it is kind of a complex issue, and it’s an issue that kind of manifests itself in different ways. So really building on on the strengths of different disciplines, I think is a key key strength here. So we don’t only look at inequality in one domain, for example, say, say something like education, which would then be kind of a subset of disciplines that tend to be interested in inequality in education, but also how education is linked to inequalities in in other aspects and, and in addition to the kind of different domains that come from different disciplines, also, the ways in which we, we analyse it and building on the strengths and knowledge of different disciplines. I think is key here, key to, to just building a comprehensive picture and learning from each other, as well as as then taking that knowledge forward.

Christine Garrington  4:34 

It would be remiss of us not to talk about COVID. And in some ways, it was something of a setback for plans to to stage events and meetings around the the programme of research to get the word out there about it. But it also provided in some respects, a rather unexpected opportunity, didn’t it to use the programme to look at inequality in the context of COVID. So, so tell us a bit about that.

Elina Kilpi-Jakonen  4:58 

Yeah, so obviously the research programme began before COVID. And so the projects had their their kind of plans of what they wanted to do and the analysis that they were going to do. But given this massive impact that COVID had on on society and and on inequality as well. A lot of projects then decided that this would be a really important aspect to look at and an opportunity also to learn about inequality in a changing societal context. So different projects have taken this into account in different ways. But for example, there’s been kind of really important work on on just what happened to inequality for example, due to lock down and and the economic upheaval of COVID, not just the health implications, but then also using that upheaval, to think about how inequalities might be changed. And for example, so work by Alejandra Rodríguez Sánchez, Suzanne Harkness and Anette Fasang, looking at what happened to housework, during COVID. People were having to stay at home, both parents and children and seeing what happens to inequalities between men and women. And how the, the the number and age of children influences that and kind of what they saw was that obviously, this change in in family habits changed house work habits, but at the same time, when locked down ended a lot of couples returned to normal. So so even though there was a massive shift, and and people behaved differently for a short period of time, we can see that these kind of entrenched habits, then then go back to normal quite quickly.

Christine Garrington  6:43 

Yeah, really interesting piece of work that so. And also, despite COVID, you were able to, nevertheless, to involve a great number of stakeholders in in the research, what messages did you receive from them, I wonder about what was emerging?

Elina Kilpi-Jakonen  6:58 

So yeah, we’ve had some really interesting discussions with stakeholders, both policymakers and then kind of non-governmental organisations involved in both practical work and lobbying as well. And they’ve been really interested in in the work that we’re doing. So in particular, we’ve talked to stakeholders involved in kind of gender inequality work, and how participation in the labour market is unequal between men and women, and in particular, between mothers and fathers. And then we’ve also talked a lot to stakeholders involved in kind of childhood disadvantages, and how different types of children are put at a disadvantage. And what are some of the mechanisms kind of potentially either alleviating those disadvantages, or that are currently making those disadvantages larger, and that would kind of be important to look at. So we’ve kind of talked both about the the bigger picture of inequality, but also some of the mechanisms and obviously, stakeholders are, are often interested in what they can do. And then we’ve also had really good discussions about especially with policymakers also about the kinds of data that going forward, would be needed to, to kind of really analyse these things further. And I think there’s a lot of kind of shared interest in collecting data or making administrative data available for researchers to be able to address inequalities in the future.

Christine Garrington  8:28 

Yeah, now a major part of your role, Elina has been to pull together all of these different strands of work in some way to ensure that we get to a, what we hope is a coherent picture of what’s been learned from the programme as a whole. And I wonder whether it’s possible in the short period of time that we have to say what has been learned from the programme as a whole?

Elina Kilpi-Jakonen  8:48 

Well, that’s no mean feat. To then kind of say what’s been learned because I think there’s such richness in the research coming through and I mean, we’ve only kind of touched upon some of the aspects just now. And so we what we’ve been trying to do is, is bring together kind of thematically, things we’ve learnt in terms of, for example, gender inequalities, as I just mentioned. So So really looking at further at kind of motherhood, penalties and how, how those might be potentially for example, by by further training ameliorated although at the same time, we need to remember that women tend to nowadays have higher education levels than men. So education isn’t always the key here. So also looking at kind of gender and sexual minorities, even though we’ve been making progress in terms of legislation and policy. The discrimination can still be kind of an ongoing issue for people and and kind of the legacy of the past is still a major issue for for LGBT citizens across Europe and even though legislation has progressed a lot to still the practices in terms of, of workplaces or educational institutions aren’t aren’t really catching up necessarily, to such a large extent. And then moving on to kind of a different area, I think there’s been a lot of really interesting work in terms of, of the role of genetics, which is a big new area of research in terms of social sciences, and how that plays into the reproduction of inequalities across generations and over the life course, and how that changes depending on the environment that people live in. So, so we’re learning a lot about so called gene environment interplay, and which is obviously kind of something that social scientists are really keen to look at is the the environmental aspect of, of how genes play out. So so we’re learning a lot about the fact that genes aren’t our destiny as such, but but the the context or the environment matters a lot for that.

Christine Garrington  11:00 

Yeah, lots of really fascinating and very, very innovative work that’s going on in that area, for sure. Now, you’re talking about stakeholders a moment ago, you’ve been responsible also for helping to ensure the dissemination of this research to to those non-academics as well as other researchers. So I’m interested to know and I think others will be interested to know what sorts of resources there are available. For those interested to know more, aside from the obviously, the dozens, and I know, there are dozens of journal articles and working papers that have have been produced if you’d like for the scientific community. But what else is there.

Elina Kilpi-Jakonen  11:34 

Starting from those journal articles, I think we’ve tried to make a kind of effort to make those more accessible in terms of both bringing them all to our website, but also providing summaries that are not just the academic abstract. So even looking at the journal articles, starting from from summaries that are more accessible to everyone involved, and not just researchers in those fields, I mean, abstracts can sometimes be a bit difficult to disentangle. Then bringing together the research we’ve we’ve been producing policy briefs that, I mean, obviously are aimed at policy audiences but I think those bring together thematically some of the research as well in a really nice way. So those are available on the on the website, then obviously, this podcast series, I think is has been a great way of disseminating the research. In addition to that, so we had our final conference last autumn. And some of those videos from the presentations are available still through the website. I mean, there’s both recordings of presentations that bring together entire projects, but also kind of individual, more finely specified research topics. But But in particular, there’s there’s videos of researchers presenting their whole project at the final conference. So I think those are also a great resource.

Christine Garrington  12:57 

Yeah, indeed, a wonderful library of materials that people can dip into at their leisure and really catch up on and get to grips with the important things that have emerged from this, this work. So finally, Elina, the ultimate aim of a programme like this is obviously to improve our understanding and knowledge on the one hand and influence change for the good with the understanding on the other. And I wonder if you’re able to say how, I know it’s very difficult, but if you can say how all this important work might feed into the thinking and policies of those seeking to reduce inequalities today, and in the future?

Elina Kilpi-Jakonen  13:32 

At the same time as advancing academic knowledge, we definitely have wanted these research results to be relevant for policymakers and to reach policymakers and indeed, kind of other organisations interested in in these types of inequalities and processes. I mean, on the one hand, there has been really great comparative work on the kind of institutional influences that policies in different countries have and I think that’s a really important thing to draw from in terms of, for example, education policy, or family policies for work life balance and the gender inequality in pay so, so looking at the across national differences and comparing countries and then learning from that. But then also, I mean, there’s been really detailed work into kind of the mechanisms of inequality and more specific interventions for example, and how those influence inequality and and then really digging more deeply into how inequality is reproduced and what we might be able to do about that. So for example, work on on parenting and how that reproduces inequalities among children and and then thinking about well, how we might be able to to provide more equitable parenting for children and what we can do about that. So I think there’s, there’s been work on multiple levels that hopefully we’ll be able for policymakers to draw on in terms of developing these things in the future.

Christine Garrington  15:07 

Thanks to Elina Kilpi-Jakonen, DIAL’s scientific co-ordinator for joining us for the final episode of this fourth series of the DIAL podcast. You can find all the resources that Elina mentioned in this episode on the DIAL website at www.dynamicsofinequality.org. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts. And don’t forget to subscribe wherever you find your podcasts to access all our earliest series.

Tackling inequalities in adolescence and working life

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In Episode 3 of Series 4 of the DIAL Podcast, we are in discussion with Richard Blundell. Richard is the Ricardo Professor of Political Economy at UCL, director of the ESRC Centre for the Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies and the principal investigator of a DIAL project looking at human capital and inequality during adolescence and working life. In this episode we explore the work done by this project tackling inequalities in adolescence and working life.

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we’re looking at what’s been learned from DIAL projects about how and when inequality manifests in our lives and what its longer-term consequences might be. For this episode, we’re delighted to be joined by Richard Blundell, David Ricardo Professor of Political Economy at UCL, and director of the ESRC Centre for the Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies. Richard is also the principal investigator of a DIAL project, looking at human capital and inequality during adolescence and working life. So welcome, Richard, thank you very much for joining us today.

Richard Blundell  0:40 

Thank you, Christine.

Christine Garrington  0:41 

I wonder if you can just start by telling us a little more specifically what this project has been investigating and why.

Richard Blundell  0:48 

Yeah, I’d be delighted to. What we’re looking at in this project is the evolution of inequality through adolescence and working life. Relating to the education streams, people choose how it affects their outcomes going forward into working life, what happens during working life, what kind of training seems to work, what routes to better jobs are for people who don’t, for example, go to higher education, university. Whether training can offset some of the gender gaps that we’ve been seeing opening up in the labour market, and whether choices in higher education matter for future labour market outcomes. So it’s very much about not the early years of school – there’s another project looking at that, that runs in parallel with our project, similar investigators, we’re working together with them. What we’re looking at here then is from adolescence onwards, and how the inequality evolves during adolescence and working life.

Christine Garrington  1:58 

So one area of focus has been women and work really very, very interested in in this, you’ve looked at the gender pay gap, the role of childcare, on women’s ability to return to work, and indeed, on the role of job training, among other things. So what would you say for you are the key things to have emerged from this particular area of work Richard?

Richard Blundell  2:18 

Yes, this is obviously absolutely central, the kind of pay gap between men and women and how it opens up through working life is something that’s been really hard to tackle and getting behind this, what are the drivers of it, and how to address it is really key to solving some of the most important inequalities that we see in working life. We’re working with researchers, mainly economists, and education researchers in Norway, in the UK and in France. That’s rather good, because those three countries have rather different systems of routes through education, into work, and different opportunities for women and men as they progress through their working life. And we wanted to understand what those differences could tell us about the gender pay gap. And therefore what policies could be perhaps most useful in addressing the gender pay gap.

Christine Garrington  3:25 

There are a couple of key things to come out of this one there.

Richard Blundell  3:28 

Some of its, you know, in some sense, pretty obvious. That is that work experience is really important for pay and for earnings as you go through your career for career progression. And of course, when children come along, women spend a fair amount of time not in work, perhaps still in employment on maternity leave, but not actually gaining the work experience that turns out to be so important in career progressions. We’ve kind of known that. But it’s become really acute, even part-time work is really not sufficient for women to keep up at work with their male colleagues. There are two kind of routes to addressing this. One is to provide good quality childcare, that can have two major benefits. One is it can provide good quality inputs and care for children, which is particularly important, especially in disadvantaged families. But it can also allow women to spend more time at work and developing their career profiles. There’s also a very large importance of mothers and fathers spending time with their children. And so when children come along, it’s kind of inevitable, really, that work may take second place, and that there’ll be less time engaged in work experience in progression. And remember, it’s exactly these years in the 20s and early 30s, where all the big career progression is made in working life, and women really fall behind there. So an alternative we’ve been looking at, and it turns out to be rather interesting is to work instead of on work experience, but on the human capital itself, once women come back into work.

Christine Garrington  5:25 

So what might that look like in reality, then Richard?

Richard Blundell  5:27 

So you can imagine the following scenario, a woman or a man, but unfortunately, it’s particularly typically, the woman who takes time off, once she returns to work, you can imagine her engaging in a training programme, and that can make up some of the loss. Well, we weren’t that optimistic about that to begin with. But we’ve become more optimistic for two reasons, particularly in the UK and in Norway. In Norway, using the Population Register, we can follow people, right the way through their working careers, we can follow the whole of the Norwegian population. It’s an exhaustive data set on everything everybody does – their qualifications, where they’re working, their family structure, and so on. And what we found is that it’s particularly successful for women to who’ve had a child early on in their career to return to some kind of schooling qualifications, and that can have a big boost to their career profiles and address some of the gender gaps that occur. In the UK it turns out similarly, women who returned to work spend quite a bit of time in training. And we found that that training, work related on the job training, it has to be accredited, and it has to be work related, those things have a payoff. And we feel that there’s real room for improving this type of training. It’s all part of designing education and training routes, during your working career, that work much better than the ones we currently have. And boy in in the UK, we’ve been training way behind in the organisation of formal routes into education and training through your working life, especially for those who don’t go to university.

Christine Garrington  7:29 

Now, I want to move on to talk about COVID. And obviously, although not expected when your project began, the pandemic, obviously, as well as being a terrible thing for us all did provide, however, what I’m guessing was quite a fascinating and important opportunity to look at the impacts of COVID on on people’s lives in this context of inequality. So what did you, what did you get to focus on there?

Richard Blundell  7:52 

Once we were into the first major wave of COVID, it was clear that it was going to exacerbate a lot of the inequalities during adolescence, during education and during working life, let alone health of course. The longer run impact that we’re seeing is on learning – the loss of learning, the loss of school time, the loss of engagement in learning, because of being not able to go to school, those children from deprived families have had much, much more learning loss over this period, than the privilege than children in more privileged families. It suddenly became clear that space was really important. But for learning for children, it was absolutely critical. If children didn’t have a quiet place with good digital access, a good setup for engaging in online classes, then that already put them behind behind. And there’s many studies showing there’s a huge gradient in space, in digital access, in access to these kinds of technologies across the income and and socio economic gradient. Losses have been extremely large, up to half a year of schooling loss for many, many children. The second point is that if you’re at home with educated parents, who are working from home and still have time to interact with you, you’re going to get that input from them. schooling is the great equaliser. It puts children from deprived backgrounds in an environment where they can learn perhaps things that they couldn’t learn at home. And that was taken away. The work on Norway and France shows exactly the same there. So learning loss, huge. This doesn’t usually happen in recessions by the way. This was very, very specific to COVID.

Christine Garrington  9:55 

And what about when you looked at matters related to work.

Richard Blundell  9:58 

All on the job training, apprenticeships just didn’t happen. In fact, for those in their early careers, you know – 18, 19, 20 – there was an almost complete end to apprenticeships. Apprenticeships fell back by 70% or more for that younger group, exactly the group that I was mentioning before. It’s vital that we get this on the job, accredited training, because they’re the ones not going to university, those going to university have been served rather better. I know from my experience here that we’ve at UCL, we’ve been keeping online classes and activities going at a pretty high level, actually. And the kind of students that we have here, can engage in that quite fully. But that’s very different for a student who didn’t make it to university, and who’s trying to gain their experience and training through apprenticeships, there’s just been no engagement. So this loss of learning has been huge.

Christine Garrington  11:11 

I’m interested to know whether women were worse affected than men in this context?

Richard Blundell  11:16 

We thought it might affect women more but in fact, overall in employment and what have you, it’s been pretty neutral in the UK, that’s just because of the structure of industry we have here. But it hasn’t been neutral at home. We’ve seen, of course, mothers and fathers both having to do more childcare, because schools have been closed during lockdown, or children have been at home during self-isolation, even in periods without lockdown. But mothers of taken, have borne the brunt of the childcare at home, we followed women and families in surveys throughout COVID. And found that although childcare activities have increased for both male and female parents, there really has been an extra load on women. And again, that’s going to affect their careers, and other aspects of their life going forwards. All those things that we were concerned about before COVID. And that were the absolute centre of this project have all become all the more heightened through COVID. And I think the policy recommendations that have come out of this project are very, very relevant for the post COVID world that we’re now entering.

Christine Garrington  12:41

Yeah, I wonder how how easy it has been? Or how difficult I guess it’s probably the better question to to feed those recommendations in such a fast moving event that COVID has been and, you know, was it possible for that to feed through all of those findings, all of those important things into the policy sort of making cycle in order to try to mitigate some of those impacts? Or, or was that that must have been very challenging.

Richard Blundell  13:09 

For policy makers, at least civil servants have been very open, of course, to try and to figure out what’s been going on. And remember, the initial policy responses, at least on simple measures of inequality have been remarkably successful. You know, we haven’t ever had a recession, really, where there’s been so much support thrown into the economy, of course, we’re gonna have to pay for that. But some of the short run impacts, I think were mitigated, what we’ve focused on here, are the longer run ones, you know the the loss of learning, the loss of training, the loss of work experience, they’re not showing up even yet, they’re going to show up in the next few years. And it’s critical, we have an opportunity now to address them. And there is a lot of interest across the whole policy world, and government and around the world. In addressing this. In fact, as part of this project, we fed into the G20 meetings last year in Rome, and a major part of our work was used to suggest a kind of coordinated approach to designing the best interventions now to address what’s been going on with loss of education, and loss of work experience and training across more or less the whole developed world.

Christine Garrington  14:27 

Really great to hear that there’s been such an appetite for findings like these important findings to feed into policy, but I guess the devil is in the detail, right?

Richard Blundell  14:37 

Unfortunately, these are gonna have to be huge programmes. And the thing about huge programmes is that they can be hugely expensive and not necessarily very effective. We need to get this right. We need to get these education interventions and these training interventions done in the most efficient and effective way. And that’s where we can learn from other countries that do at least some things better, some things worse, we’re all learning from each other. And this project which brought in, you know, Norway, which has a pretty effective system of education and training right across the board, not just for those going to university, which is where we tend to focus. And France, which has, again, a very different system. So we can learn, we can learn from that. But yeah, I see a long impact of COVID, not just long COVID. But it’s hidden a bit at the moment, by the way, because of the uptick in the economy. You know, there’s quite a demand for certain types of jobs, as you’d expect, when there’s, you know, we’re coming out of a big, big recession like that, but I’m pretty sure that that’s hiding these big losses, they will turn up over time. So yeah, there’s, there’s a big hunger for this. We’re feeding a lot of a huge amount and working a lot with Department of Education here with the Treasury on what what should be done with other policy groups. And similarly in Norway, and France.

Christine Garrington  16:08 

Now, I know we’ve talked about the labour market a bit, but I wonder whether there’s anything else that you really would like to stress about that side of things, because this was a major part of your work?

Richard Blundell  16:19 

We had to invent things on the hoof and everyone was involved in that the furloughs remember, the furlough system didn’t exist. In fact, in the UK, and in many other economies, we’ve not, we’ve not been particularly good at providing general what one might call social insurance. That is, if people fall on hard times get reduced earnings, you know, do we make up the difference? At least in the in the shortish run, we don’t particularly do that very well, in the UK, we target very low incomes. We have a very targeted universal credit and benefit system. So it does prop up incomes at the bottom. And it does that actually quite well. Not always administratively perfectly, but it does it. But if you look at someone who’s on a kind of lower middle income, which is the group that really was hit during COVID, there’s very little support for them. Universal credit doesn’t do a great job, it just doesn’t replace their incomes – the furlough system did it replaced 80% of their income. And, and it was very successful in doing that, to the extent that as I said, you know, income falls and inequality increases didn’t happen in the way they often do during recessions. So in that sense, these policies have been very successful. On the downside, you know, they’re the things I mentioned, they’ve been very good at short run income support, at least for for many groups. But they’ve not been very good yet at addressing these losses in, in human capital investments. And work is about two things. It’s about earning money today. And it’s about in investing in skills that will earn you even more, or give you a better career profile, at least in the future. And it’s those longer term investments that I feel, or a fear of being really left to one side.

Christine Garrington  18:17 

I wonder whether you’ve seen anything that relates to how these inequalities manifest in respect of where people live, where they come from, is there something around place that’s quite important as well?

Richard Blundell  18:28 

We kind of knew there were geographical differences and differences by family background, it just, you know, we can see that in workings of our society. But I didn’t realise how big they were. And I think it’s been quite a shock to us. It’s not surprising, you know, that the emphasis now is on levelling up, at least it’s suggested it is in education is very important. What we found in this research, you know, looking at how well people do at school, and then into university, if they go there, and then into work is really striking, you know, some areas of the UK, for example, and this would be true in other economies as well, by the way, very few children actually make it to university. Take areas like Grimsby or Skegness those kinds of places we almost think of as left behind communities, children just don’t do so well. And not only that, if they do manage to get into higher education, they often don’t return to those communities. So those communities, once you look at people in work that just have many, many fewer people with higher education qualifications and skills to other areas. Let’s call them the thriving areas, many of which are in the southeast or in the more successful cities. And these differences are really important because they’re having huge impacts in the way people think about their well being levelling up political discourse.

Christine Garrington  20:07 

You talked earlier a bit about their fabulous data in Norway that you had available to you. But we’ve also got some great data here in the UK, haven’t we, particularly when it comes to tracking young people through education?

Richard Blundell  20:20 

We have the National Pupil database that follows all children through school, through higher education, or through their education and training and into work right up to about the age of 28/29 now. So we’re, and that will go on. So this is a remarkable, a remarkable dataset of the kind that you would typically think of finding only in a Scandinavian country. So this has allowed us to do these differences. And we can look at two children doing exactly the same courses in the same university, and just look at the differences of outcome by parental background and they’re still there, they’re still quite important. So parental background really matters. But so does course choices and university choices. These things, I guess we knew that have a big impact. All these things that people are doing through their their education, and early working lives and at university have a long lasting impact. And many of the differences you can take back to geography, and parental background, and the early education investments. This is really providing a real detail in what’s driving the inequalities that we see at least in working, working careers.

Christine Garrington  21:47 

Yeah, on that note, I’d like to put a final question to you really about, you know, for those interested who in tackling inequality, obviously, including yourself and your fellow researchers, the wonderful team that you’ve talked about there. But for those who have responsibility for creating interventions through policy or practice, are there any essential takeaways, implications or recommendations for your project that you’d like to share?

Richard Blundell  22:11 

If there’s something we’re going to really have to address the in the UK and elsewhere it’s these geographic divides. It’s what is creating a lot of the political turmoil, I think, whether it be almost in any elections, we’ve seen the left behind areas. You know, the evidence is clear, these geographical divides, by socioeconomic background, and by areas are really important and long lasting. And it’s really up to us to figure out the best ways now, to address them as quickly as possible. They’ve been exacerbated through COVID and so they become even more urgent, I think, in the policy debate.

Christine Garrington  22:56 

And I guess my final final question, is there something specific that we should be focusing on?

Richard Blundell  23:03 

There’s a lot, but let me just pick on one, it’s a kind of old topic, it’s the it’s the point about good jobs. You can have successful interventions for people who come from, you know, backgrounds or haven’t been quite successful at education investments, you can make better choices during education. And we’ve seen how, with the data and work we’ve been doing, how that can be improved. But it’s really the match of the skills, the firms and the kind of work related nature of these training investments that’s so important. And what we have learned here is that, you know, small interventions on one aspect of this are not going to solve the problems. So you can think of the example of the, of just providing a job. What we’ve seen here is that just providing a job, say, Amazon warehouse job is not really going to help much with career profiles, you really need to match workers, develop their skills, and bring the right kind of firms that can enhance career profiles into these more left behind deprived areas. If we can get that to work, then there’s great hope that we can do something for the careers and wage profiles of people who’ve been doing rather less well than we’d like in society.

Christine Garrington  24:39 

Thanks to Richard Blundell for joining us for this episode of the DIAL podcast. You can find out more on the DIAL website at dynamicsofinequality.org and also on the IFS website at ifs.org.uk. Much of the work of Richard and his colleagues has also fed into the Deaton Review on inequality so do take a look there as well. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts.

The long-term effects of school closures

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by Alexander Ludwig and colleagues

This blog was first published by VOXeu.

After the outbreak of the COVID-19 crisis in the spring of 2020, politicians around the world closed schools and child-care centers together with businesses in an effort to contain the virus. According to the World Bank, around 1.6 billion school children were affected by these closures at their peak. While the economic costs of closing businesses arise immediately and are thus very salient, closed schools and child-care centers have negative economic effects on the human capital accumulation of children that only arise in the long run. Education is a crucial determinant of future wages, and schools are an important driver of intergenerational mobility. In the short-run, parents, and especially mothers, are struggling with combining work and child care while schools are closed, but what are the long-run economic impacts of Covid-related school closures on the affected children? 

A model of schooling and parental investment into children

To answer this question, we build a model that features public schooling as input into the human capital production of children, as well as monetary and time investment of parents into their children. At the core of the model, there is a human capital production function that features self-productivity, i.e. human capital builds on itself, and complementarity, i.e. the higher the human capital, the more productive is investment into human capital (Cunha and Heckman, 2007; Cunha, Heckman and Schennach, 2010). 

From age 4 to age 16 children reside with their parents who invest time and resources into their education, which, combined with public expenditures, governs the evolution of human capital of the children from kindergarten through high school. At the age of 16, high-school students decide whether to stop schooling and start working, to complete high school, or to obtain a college degree. At that time parents endow their children with intra-vivo transfers that can be used to finance higher education. The terminal school degree (college, high-school, high-school dropout) as well as the human capital accumulated during their schooling period determines wages of the children once they enter the labor market. 

We calibrate the model to data from the US. Parents are heterogeneous with respect to marital status, education, income, and assets. Parental characteristics affect not only the innate ability of their children, but also the optimal investment into their children. We model the school and child-care closures as a drop in governmental investment into children corresponding to school closures of six months. In addition, the COVID-19 shock comprises a fall in parental income through increased unemployment, with a larger incidence for less educated parents. We then use the model as a laboratory to ask how parents react to these shocks, and what are the ultimate labor market and welfare effects on the children? 

Our main results are summarized in Table 1. We find that the children affected by the school closures suffer long-run average wage losses of -1%. These wage losses lead to a reduction in welfare corresponding to a consumption equivalent variation of -0.7%. An important driver of the long-term wage losses are changes in the final educational attainment of the children; the table summarizes the percentage point changes in the education shares. Translated into percent changes, the share of college educated children falls by -2.6%, and the share of high school drop-outs increases by 4.1%, due to the fact that the children impacted by COVID-19 school closures early in their life arrive at age 16 with significantly less human capital than in the absence of COVID-induced school closures.

Thus, there are significant permanent negative effects associated with a purely temporary shock. For the children, the negative effects of the temporary school closures are much more important than the negative effects caused by the temporary income drop of their parents: school closures account for 90% of their overall welfare loss.

Table 1: Aggregate Outcomes of School Closures and Income Recession

Baseline change for children of biological age
average 4 6 14
change in %p
share s=no 12.15% 0.50 0.56 0.67 0.31
share s=hs 54.53% 0.38 0.27 0.32 0.43
share s=co 33.32% -0.88 -0.83 -0.99 -0.74
change in %
PDV gross earn $784,196 -0.99 -0.96 -1.19 -0.77
CEV children – -0.70 -0.72 -0.84 -0.54

These negative effects emerge despite the optimal efforts of parents to offset the impact of school closures by increased parental time and resource inputs into their children’s education. On average, parents increase their time investment into children by 3.8%, and their monetary investment by 5.1%. However, due to their own income loss, parental intra-vivo transfers fall by -0.3%. These changes imply welfare losses of -0.3% for the parents themselves.

The average long-term gross earnings loss of -1% for the children translates into a net earnings loss of -0.8%, assuming no changes in the tax and transfer system. Given the progressivity of labor income taxes, the lower average earnings lead to disproportionally lower tax payments. Thus, while the tax system to some degree shelters children from the future negative income effects, the flip side is that future government revenues fall by more than the gross earnings loss endured by these future workers, namely by -1.8%. Thus, COVID-19 school closures in the short-run foreshadow a substantial fiscal crisis in the long run.

Younger children and children from disadvantaged households suffer more

The earnings and welfare effects of the school closures depend significantly on the age at which they happen. For children aged 6 who are about to start primary school when the COVID-19 school closures occur, long-term earnings losses amount to -1.2%, with associated welfare losses of -0.8%. By contrast, for children aged 14, these losses are approximately one third lower, amounting to -0.8% and -0.5%, respectively. The reason for this age pattern is that human capital builds on itself, and lower human capital leads to lower optimal investments in the future.

Thus, for children aged 6, parents optimally increase their investments at the time of the closures but cannot completely offset the human capital loss on impact. This leads to lower parental investments in future periods, relative to a world without the school closures. Compared to children of age 6,  younger pre-school children are somewhat sheltered from the negative effects of the closures, because at that age parental investments play a more important role for human capital accumulation than governmental investments. 

In addition to the age of the child, parental characteristics are a crucial determinant of the magnitude of the earnings and welfare losses for children from the COVID-19 crisis. The welfare losses of the school closures for children are decreasing in parental education as well as in parental assets. Well-to-do parents have more resources to help out their children during the school closures, and also have a higher incentive to do so.

Their children have on average higher human capital than the children of less well-off parents, and thus, given the complementarity of investments and human capital, larger investment increases after the school closures subside are optimal for them. Therefore, the role of parental characteristics for the school success of children is amplified by the COVID-19 school closures.

Prolonged school closures make the effects worse

The current second Covid-19 wave in the fall of 2020 makes prolonged school closures a reality in some school districts, and renewed school closures a possibility in many more. We find that the welfare effects of one-year school closures are more than twice as large as the welfare effects of six months school closures. The loss in schooling and associated human capital accumulation is harder to offset the longer the crisis lasts. 

Hybrid and digital teaching

Many schools relied on various forms of digital teaching during the school closures, and nowadays implement hybrid teaching formats, combining in-person instruction and remote teaching. The literature thus far provides only scant evidence on the effectiveness of online vs. in-person instruction, and thus it is hard to gauge the long-run consequences of digital teaching.

Yet, there is evidence that children from disadvantaged households have less access to and/or make less use of digital forms of teaching during the current crisis. Opportunity insights reports that student participation in online math work decreased immediately for all children at the start of the school closures, but ultimately decreased by 41% for children from low income ZIP codes by the end of the school year compared to January 2020, by 32% for children from middle income ZIP codes, and not at all for children from high income ZIP codes.

It is plausible that both the equipment for digital teaching among teachers, as well as the equipment and the provision of quiet learning spaces for the students depend on socio-economic characteristics. While we cannot put hard numbers on the differential use of online learning by parental characteristics, our model allows us to trace out the heterogeneous wage and welfare effects, by parental background, when the length of school closures is negatively correlated with socio-economic characteristics of the parents.

For example, if one assumes that the school closures in combination with distance learning opportunities correspond to a complete school closure of 3 months for children of college educated parents, but of 6 months for children of high school dropouts, then the welfare impact is -0.7% for the latter group, but only -0.3% for the former group.

Conclusion

School and child-care closures have significant negative long-term consequences on the human capital and welfare of the affected children, especially those from disadvantaged socio-economic backgrounds. This reduction in human capital accumulation is likely slowing the long-run growth prospects of countries, especially those whose economies are relatively human capital intensive, such as the U.S. and Europe.

Thus, school and child-care closures are potentially very costly measures to avoid the spread of the Covid-19 virus. This point was initially largely lost in the political debate, likely because these negative effects arise only in the long-run and thus are not immediately measurable. Medical research now also indicates that children are not the primary drivers of the COVID-19 pandemic, in contrast to pandemics caused by the influenza virus.

During the current second wave of the crisis in the fall of 2020, governments seem more committed to keep schools and child-care centers open as long as possible. For example, Germany and France are closing restaurants, bars, and the entertainment industry during their “lockdown light” in November 2020, but not schools and child-care centers. Our research suggests that this policy choice has the potential to pay significant long-run dividends for future generations, even though it might contribute to a more rapidly evolving second wave of Covid-19 infections in the short-run.

The Long Term Distributional and Welfare Effects of Covid-19 School Closures, by Nicola Fuchs-Schündeln, Dirk Krueger, Alexander Ludwig and Irina Popova, was published by the Centre for Economic Policy Research in August 2020: CEPR Discussion Paper 15227.

Work and family lives: Who has a chance of having it all?

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In Episode 6 of Series 2 of our podcast, we talk with Professor Anette Fasang from Humboldt University and Professor Silke Aisenbrey from Yeshiva University about their research looking at how inequality plays out in the parallel work and lives of black men and women in the United States.

Transcript

 

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In this series, we discuss findings from DIAL’s Equal Lives project, which looks at how inequality impacts the lives of young adults. Our guests are Anette Fasang and Silke Aisenbrey, they’ve been looking at the parallel work and family lives of black and white men and women aged 22 to 44 in the United States. I started by asking Anette to explain the background to their work.

Anette Fasang  0:27 

So recently, or for a longer while actually there has been quite a bit of talk about intersectional inequalities, so overlapping categories of inequality, very prominently, gender and race that we also look at in our paper. And here the ideas that black women, for example, face specific disadvantages that white women don’t, but that are also different from the challenges that, for example, black men face. And this is a type of our field of research that often works with qualitative data, for example, or is quite theoretical also activism oriented. And that’s actually not at all where Silke and I come from, we are more sort of quantitative statistics oriented people do inequality research in this area. But we found this new intersectionality approach extremely important, and tried to get sort of a quantitative what we call life course, perspective on intersectional inequalities. And for us, the life course perspective here is really important. Because when you think about differences between social groups, if you measure them at one point in time, for example, their incomes at age 30, you will, of course, find differences, and you’ll find inequality. But what we try to do is follow people really from age 20, to age 40, to see how different types of advantages and disadvantages accumulate, because what accumulates over the life course, tends to be much larger than disparities measured at any specific time point. And we think that’s particularly important when you’re trying to assess differences between social groups, to not understate the actual extent of disadvantages and advantages that people accumulate over time,

Silke Aisenbrey  2:17

Where we are coming from, it’s really to look at at the life of a person in terms of a movie, like understand it really, as this bigger concept and understand every step of the way, as a result of what happened before. Anette and I did like a big project where we did something similar, where we addressed similar questions about the intersection of careers and family careers, so to speak, where we compare Germany and the US. And in that research, we found that there’s a lot happening within the US that we actually can’t get a grip on. So that was the start off point for this project, where we’re like, there’s so much race segregation in these life courses happening in the US that we actually want to kind of look deeper into that.

Christine Garrington  3:07

Anette then just take us a little bit more deeply then into what it was you were looking specifically in this paper to get to grips with and why?

Anette Fasang  3:15 

Yes, we used a great data source, the so called National Longitudinal Study of youth for the United States, which has followed individuals for many years, re-interviewing them every year. And here we could for men and women born in the 60s, we could reconstruct their entire life courses from age 20 to 40. So their educational and work careers, when they were in school, when they finish, whether they were unemployed, whether they were on family leave, and which types of jobs they were in, where we could also distinguish was this sort of a low level low paying lower skilled job or a higher level highest high skilled job? So that’s how we could reconstruct their careers and for their family lives we also know exactly – were they living with a co-residential partner? When did they have children? Did they separate? Did they re-partner? And so we were able to reconstruct these entire life courses for black and white men and women to assess what kind of advantages and disadvantages accumulate over time for these different social groups.

Silke Aisenbrey  4:24 

We’re talking about comparing black individuals to white individuals in this paper, and that, of course, leads to this question – so why is that our focus? There are more groups than that in the US. And for us, it was that we really wanted to clearly focus on the on the white privilege and not kind of on the underprivileged group, and compare those to the group that we had the most data on and that were black women and black men. So we excluded Hispanics and other minorities in this specific research, so that’s why you’re having the comparison of black and white individuals here.

Anette Fasang  5:00   

What is often done, especially in this quantitative inequality research is that you have one point of reference and that’s typically white men. And then you interpret differences of white women, black women, black men, all referring to the white male experience and this in a way normalises it that the intersectionality approach or intersectionality theory criticises and we kind of jump on this paradigm by comparing all four groups visa vie as each other. So we compare black men to black women, to white women, to white men, and so on, and have all these pairwise comparisons to contextualise each group situation much more than only using this one reference point, as is often done.

Christine Garrington  5:44 

You talked about the normalising there Anette – what are the advantages? What makes it better if you like by taking this approach? Perhaps Silke you want to pick up?

Silke Aisenbrey  5:52 

Anette has said this beautifully. And I think your question is exactly on point so that the idea is that it normalises the privilege by not talking about the privilege. So in a way, if you compare every group to white men, the privilege that white male careers inhabits it basically gets unseen. So our commitment here and also the commitment of intersectionality research is really to say like, point out the privilege also describe the privilege and don’t only focus on those who are underprivileged. And we were very committed to that approach throughout the paper.

Christine Garrington  6:29 

That’s so interesting. Now, let’s dig right in now and look at the comparison that you made between white and black men, what were the key things to emerge there?

Silke Aisenbrey  6:38 

I think that the one thing that comes over and over is really when we look at the group of white men is really, basically they can have it all in the sense that they can have the high prestige career. And they can combine this high prestige career with any kind of family formation, they can be like single, they can have three kids, they can have one kid. So all of that is possible for white men, whereas for all the other groups, I know you just asked about black men, all of these variations are not open in the same way.

Anette Fasang  7:12 

A core focus of our paper was that we wanted to have these both aspects of the life course – work and family – and also look at the interplay between the two. And the idea here was that if events for example, in the family life strongly constrained economic opportunities. For example, if typically women but also men have children very early, that really limits their career prospects later on, especially if this is single parenthood. So this would be one way how an event in the family life course can constrain opportunities in the work life course. And the other way around, for example, for men, and we see this especially for black men holding a stable job, at least a stable job, even if it’s not a high stakes high earning job at at least a stable job is almost a precondition for then forming a stable partnership and having kids. So the two life course domains are interrelated in these many different ways that play out in mutually affecting each other over these entire 40, 20 years, that we observe the life course. And here our idea was is that if the connection between the two life domains work and family is very strong, that means that events in one life domain condition and constrain what is possible in the other life domain. So this is a in a sense, a sign of disadvantage, because there are more limited opportunities economically, but also for different family lives. And if they are unrelated, that means whatever happens in the work and family domain, whatever disadvantages or advantages there are, doesn’t spill over into the other life domain. And there’s just a wider set of possibilities for how life courses evolve. And indeed, what we found was that this interrelationship between work and family lives, was really, really low for white men. So basically non-existent, as Silke just described, it doesn’t mean that everybody gets what they want. Not all white men get get what they want. But for them, everything is possible in the sense that it actually occurs empirically, you have these very many different combinations of work and family lives. And this was quite different for the three other groups. And here we found that the strongest interrelation between work and family lives where they sort of condition and constrain each other was evident for black women.

Christine Garrington  9:43

Yes, on that note, I’m really interested to know because the picture was slightly different, wasn’t it for for black and white women.

Anette Fasang  9:49 

Yes, that is also I think an important point of our paper, that there’s a lot of research showing how the for example, family lives of lower educated black and white women are quite different. But we see equally large differences among highly educated black and white women. There’s really a lot of evidence that initial economic resources and then economic opportunities along the life course – so education, access to high quality jobs and so on – but also resources in the parental home. Those, those all have really strong effects on family lives. And then there’s also evidence showing how events and family lives like becoming a parent has repercussions for careers. So here there’s this whole literature on motherhood penalties how mothers make less money than childless women. But overall, the evidence that economic starting conditions are stronger predictors for family lives, is more convincing, and just broader than for the other way around that family events restrict their opportunities and work lives. And so what we argue here is that black men and women’s family options will be limited because they, on average, have worse economic starting conditions. And then for women, on the other hand, compared to men, there will be more repercussions of their family lives for their careers, which is also based on previous studies. And so if you take those two together, then of course, white men will have the most options because they are on average in economically privileged situations compared to the other groups on average. And their work events in their work lives, even unemployment have relatively modest effects on their family lives. Whereas when you go to the other end of the extreme here, black women, they’re both disadvantaged because they are black and face, on average, lower economic resources that limit their family options. And then because they are women, their family lives have stronger repercussions on their work careers. So that’s how the strongest interrelation in this long term interplay between the two life domains plays out according to our data,

Silke Aisenbrey  12:01 

I just want to go back to what I said earlier that one of the like, important things about our research is that we really also want to look at privilege. So I think it’s worth kind of just looking at this high prestige group to kind of make that comparison and what you can really see when we look at black women that there is this double under privilege happening, that you can’t even find empirically any black women in this high prestige group. So you you do find white women, and there mainly have no kids or have a kid later in life. And you do find some black men who also only have one kid and later in life, but you can’t even find black women. And I think that’s something that needs to be pointed out and needs to be underlined.

Christine Garrington  12:46 

No that’s a really important point to make Silke thank-you. So when you were thinking about the policy intervention implications of all this, then you sort of started to consider what might work best, what was your thinking Silke?

Silke Aisenbrey  12:59 

It’s a very complicated question because you you will see that when you look at at the medium prestige group and at the high prestige group that a lot is attached to having children or not having children and for women also, to have partners. And as we know, a lot of work in home still falls on the burden of women. So I think childcare is definitely like a very, very big thing. And especially in the US, where like most childcare for smaller children is private, it is hardly accessible for anyone who is not working in a high prestige career. So I think childcare is really one of the like main things that we need to like look at.

Anette Fasang  13:37 

So another thing that I found really striking was when we looked at these work, family life courses, and which ones are most prevalent for black men, but we found as Silke said, there is a smaller group of black men who have that highest earnings, one or two children, usually late or classic, successful upper middle class life course. But these are only 12% of black men. That means the remaining 88% have low, in our case really low prestige jobs with low earnings. There are no stable middle class careers among black men of these generations that we’re looking at. And what I found particularly striking and this is something you can only see in this longitudinal process perspective, that 62% of them have unstable low prestige, low income careers. So that means they are frequently interrupted by periods of unemployment or being out of the labour force entirely. So that means 62% of black men in these cohorts have really precarious careers. And all of them actually have family lives that are either childless or they’re single fathers. So these precarious work careers really go along with having sort of non-traditional or at least family careers that don’t go along with stable co-residential partnerships. And how this bridges into the policy point is that I think one thing our findings, if you take them all together really support quite strongly is that the lack of initial economic opportunity sets, especially black men and women on a difficult path early on, and really limits their family opportunities. So what is implied and this of course, is if you want to equalise work family life courses among these four intersectional groups, then equalising economic starting conditions would be quite important early in early childhood or in early adulthood. And this is these early interventions are particularly important because then you can break cycles of increasingly cumulatively, increasing advantages or disadvantages like these vicious or virtuous cycles that we know from many different studies tend to play out over time in these life courses.

Silke Aisenbrey  16:00 

I also think that the access to education is just still very, very segregated for different groups in the US. So I think that’s also always something that needs to be said.

Anette Fasang  16:09 

What also was interesting about these findings is actually how the large proportion of people who remain in similar career tracks that they entered early on, there is of course, some upward mobility there is also some downward mobility. But we see many people are kind of locked in the same precarious careers over 20 years from age 20 to 40. That never make it out. So I think many things are missed. If you only look at, for example, people’s work situation at age 25. When you take into account how many of them who are in disadvantageous positions actually remained in those for very extended periods of time.

Silke Aisenbrey  16:52 

Parental leave also, of course comes to mind when we think about these full careers. And this is also important because when we talk about cumulative advantages, we see that in the US parental leave is often only accessible if you have careers and medium or high prestige jobs. So if you’re once on this career track, the advantages just cumulate between like childcare, and parental leave, all of these things are accessible, much easier to people who are already in privileged positions.

Christine Garrington  17:25 

“Uncovering Social Stratification; Intersectional Inequalities in Work and Family Life Courses by Gender and Race” is research by Anette Fasang and Silke Aisenbrey and is published in the journal Social Forces. You can find out more about the Equal Lives project at www.equal-lives.org and subscribe to the DIAL podcast to access earlier and forthcoming episodes. Thanks for listening to this episode, which was presented and produced by Chris Garrington.

Unemployed parent? How does that affect a teen’s school choices and achievements?

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In the second Episode of Series 2 of our podcast looking at research emerging from the Equal Lives project, we talk to Jani Erola and Hannu Lehti from the University of Türku in Finland about their research, The heterogeneous effects of parental unemployment on siblings’ educational outcomes. They use high quality Finnish data and robust methods to see how having an unemployed parent affects how teenage children get on at school. They discuss their findings and what they might mean for those seeking to support the families of people out of work and to reduce inequalities over the life course.

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