DIAL Dynamics of Inequality Across the Lifecourse (DIAL)

In Episode 7 of Series 2 of our podcast we talk with Professor Susan Harkness from the University of Bristol and PI of DIAL's EQUAL LIVES project about how economic disadvantage accumulates for single mothers and the impacts on their income and risk of poverty of having a child and splitting up from a partner.
The Accumulation of Economic Disadvantage: The Influence of Childbirth and Divorce on the Income and Poverty Risk of Single Mothers is research by Professor Susan Harkness of the University of Bristol and is published in Demography.
 
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 emerging findings from DIAL's Equal Lives project. Our guest today is Professor Susan Harkness from the University of Bristol and PI of Equal Lives. She's been looking at how economic disadvantage accumulates for single mothers, and the impacts on their income and risk of poverty of having a child and splitting up from a partner. I started by asking her about the background to her research.
Susan Harkness  0:28 
I think for a long time, there's been an assumption that single mothers are more likely to be poor or living in low income because they're not living with a male breadwinning partner. And I think one of the things that's been much less well recognised is that in the US, but also elsewhere, single mothers are much more likely to be poor than single fathers and I think one of the reasons for this is not just that they don't live with a partner, but also because they face an enormous economic hit because of motherhood. And I think the motherhood penalty. We know, we know it exists. We know mothers are much less likely to work than fathers. And when they do work, that they're more likely to be paid less. And what I wanted to do was try and connect to this research with research from single parenthood to see what the impact on single mothers' incomes was.
Christine Garrington  1:16 
So what was it here that you wanted to look at specifically and why then?
 
Susan Harkness  1:21 
Okay, so I wanted to think about why single mothers were more likely to have low income so what was the penalty to single motherhood? And in doing that, I wanted to think about single motherhood is a process that sort of evolves over the life cycle. So first of all, we know that mothers when they have children, they face this economic penalty in the labour market, and then when they separate, they're left in this very vulnerable position because their employment earnings have just declined so much.
Christine Garrington  1:49
And for this research, where did you get your information from? And can you tell us sort of why it is a good source for for looking at these particular issues? 
Susan Harkness  1:58 
Yes, so we looked at data from the Panel Study for Income Dynamics and it's a great source of data because it allows us to look at people over time. In the case of our study, we've followed them for over 10 years, since becoming mothers to look at what happened to their incomes around these kind of critical lifecourse transitions. One of the great advantages of it is that we can see how people were doing before they became single mothers and we can see how they were doing after and then we can kind of look at how each of these different life course events - motherhood, partnership dissolution - leads to changes in their economic circumstances. Another major advantage of this data is that it's got a really large sample size, and therefore we can think a bit more also about the heterogeneity the experience of single mothers. And what we mean here is that we can think about whether all single mothers effectively look the same or whether different routes into single motherhood have a different impact on their incomes. So what we did in this particular case was think about how single mothers differ according to whether the

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 th

In Episode 5 of Series 4 of the DIAL Podcast we’re in conversation with Andreas Peichl, Professor of Macroeconomics and Public Finance at the University of Munich and Principal Investigator of a DIAL project looking at the impact of childhood circumstances on individual outcomes over the life-course (IMCHILD). 
 
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. Today, we're delighted to be joined by Andreas Peichl, Professor of Macroeconomics and Public Finance at the University of Munich, and Principal Investigator of a DIAL project looking at the Impact of Childhood Circumstances on Individual Outcomes over the Life-Course. So, welcome, Andreas, thank you very much for joining us. And I wonder if you can start by telling us a bit about what this project has been investigating and why?
Andreas Peichl  0:39 
So the project IMCHILD the Impact of Childhood Circumstances on Individual Outcomes over the Life-Course, had the aim to investigate how early decisions that usually parents make for their children's are really at the beginning of life, the early childhood, how these what we call circumstances for the child. So this is something that children typically cannot influence. Because these are decisions by made mostly by parents, how these circumstances affect decisions later in life. So for example, the transition to adulthood, be it educational or occupational choices, family formation, or later labour market outcomes. And the really, the idea was to see whether we find that the early childhood circumstances matter later in life. And then the next question, if this is the case, was what are the causal links? What are the mechanisms for this? And also, what can policymakers do about it if they aim at achieving something like equality of opportunity? So what can policymakers do to to level the playing field, so to say, later in life.
Christine Garrington  1:54 
Now, I'm interested to know as we record this conversation, COVID is something we certainly seem to be learning to live with right now, although COVID wasn't an issue, when you started this project, it certainly became one. And you've taken time to consider which children have been most affected by school closures for example. Can you tell us a bit about what you found there?
Andreas Peichl  2:14 
First, what we found is that in any country that we looked at, and especially in Germany, that was the main focus of this part of the analysis, but we also looked at other countries. That low achieving students, so students that were already not doing too well, in school, they were affected the most. And at the same time, students from non academic parents and lower socioeconomic status backgrounds, they were also affected the most. So sometimes, it's a combination of those two factors that are the same children, so low achieving, and low socio-economic status, but it's not exclusive. So, in general, low achieving students and lower socio-economic background, especially non-academic parents, those were the kids that were affected the most by, for example, school closures. But in general, we see that there was a large decrease in learning time for all students in school. And so basically, the whole cohort, were really affected by this.
Christine Garrington  3:21 
Right and, of course, as we, as we say, as we talked about learning to live with COVID, there are going to be already are, if you like longer term implications of this for children, educators and policymakers who are keen to ensure that any pre-existing inequalities don't become more deeply ingrained. Have I got that right?
Andreas Peichl  3:42 
Yes. So it's, it's really through it, we need to make sure that these existing inequalities d

In Episode 4 of Series 4 we're talking to Professor Sakari Lemola from the University of Bielefeld and formerly from the University of Warwick. Sakari is one of the Principal Investigators of the DIAL project PremLife, which has been looking at what factors can provide protection and increase resilience for preterm children’s life course outcomes. 
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 Professor Sakari Lemola. He's from the University of Bielefeld and formally from the University of Warwick, and one of the Principal Investigators of the DIAL project, PremLife, which has been looking at what factors can provide protection and increase resilience for preterm children's life course outcomes. So Sakari, thank-you so much for joining us today. It's great to have you on the DIAL podcast. I wonder if you can start by telling us a bit more specifically what this project has been investigating and why?
Sakari Lemola  0:45 
So the PremLife project has been particularly focused on the role of protective factors for social and educational transitions after preterm birth. Preterm birth is defined as birth before the 37th gestational week. Then there are two further categories one distinguishes between moderately to late preterm children at its birth between the 32nd and 36th gestational week - moderately and late preterm children. But they're also very preterm children who are born before the 32nd gestational week. So in the PremLife project, we specifically look at both of these groups - the very preterm children and moderately and late preterm children compared to term born children and try to figure out what are their disadvantages they have in their lives? And also, what are protective factors that may improve their outcomes? In some domains they actually do really well when certain protective factors are present.
Christine Garrington  1:50 
Can you tell us something about how common preterm births are?
Sakari Lemola  1:54 
The incidence of preterm birth has been rising in the last few decades. So in the UK, around 7% of all babies are born preterm each year. This means that two children in an average sized primary school class are likely to have been born preterm and in spite of the advances in neonatal care of preterm birth in the last few decades, and also decreasing mortality rates, which is a very good thing. Negative long term, sequels and consequences of preterm birth have still remained, particularly for very preterm children, those born before the 32nd gestational week that means eight weeks too early or even earlier than that. That leads to medical complications, which often require distressing but life saving treatments frequent are, for instance, neonatal asphyxia, hypoxia due to immature lungs. Necessary treatment involves ventilation, continuous positive airway pressure, surfactant treatment, but also treatment with stress hormones, prenatal corticosteroids treatments to accelerate the long development.
Christine Garrington  3:10 
And so Sakari what does life look like for those children compared with their full-term born peers?
Sakari Lemola  3:16 
They often have an increased risk for poor cognitive development, they show poor educational outcomes, less favourable employment outcomes in adulthood and increased risk for developing mental health problems. And in the PremLife project, we try to specifically answer the question, first of all, of course, what are protective factors for those born preterm. But also we try to focus also to figure out out about what are the social and emotional development of the preterm birth, particularly related to social relationships, wellbeing a

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 cours

In Episode 2 of Series 4 of the DIAL Podcast, we are in discussion with Professor Hans van Kippersluis from the Erasmus University in Rotterdam. Hans, a professor of applied economics, is the Principal Investigator on the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities, which has used innovative methods and data to explore the interplay between nature and nurture in generating health and education inequalities.
 
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 some of the DIAL projects about how and when inequality manifests in our lives, and what its longer term consequences might be. For this second episode of the series, we're delighted to be joined by Hans van Kippersluis, Professor of Applied Economics at the Erasmus University in Rotterdam. And Principal Investigator of the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities - put more simply nature versus nurture. So Hans, welcome to the podcast. And I wonder if you can start by talking us through what researchers working on this project have actually been looking into.
Hans van Kippersluis  0:42  
What we've been doing in this project is essentially incorporating the recent availability of genetic data into social science and most prominently economic analysis. And so most of our work has focused on the interplay between genes and the environment. So in the introduction, you mentioned nature versus nurture, but actually more accurately, what we're doing is nature and nurture jointly into how they shape essentially education and health outcomes. And I think this is also the main innovation of our project, because biologists have studied nature before; social scientists have  of course, extensively studied nurture, but not many have studied the interplay, the interaction between the two. And I think this was sort of the main innovation for why we got the funding some five years ago. And so what we have done is mostly studying this interplay. But along the way, we have also made some methodological contributions to a field which is very new. Then we've also used genetic data to test all their theories, and also, I think, enrich the framework of equality of opportunity.
Christine Garrington  1:35  
Yeah, fantastic project. And as you've just said, you've made unprecedented use of genomic as well as survey data in the research, tell us a bit more about the information that you've been able to access? And how you've been able to use it?
Hans van Kippersluis 1:47  
Yeah, sure. So the interesting thing is that more and more social science datasets, so data sets that have been traditionally used by social scientists, and these are mostly extensive surveys,  are now collecting DNA information from their respondents. And this is often from blood or saliva. And what they did is basically, so more than 99% of DNA is the same across human beings. And so what we are using is only this remaining less than 1% of the variation. And these are called snips. And snips are points of your DNA that differ across human beings. And there's roughly 1 million of them. And so what we do, basically also other people have done is sort of aggregating these tiny effect sizes into an index. And this is called the polygenic index. And this is telling us something about your genetic predisposition towards a certain outcome. And this is quite interesting, because this data, this new variable, essentially can be added to existing datasets. And so we have a wealth of information that has been collected in the past on surveys on existing data. And then we simply add one indicator, one new variable. This is telling us something about people's genetic predisposition. And just to be clear, this is not like a deterministic variable. It also exhibits quite a b