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May 2, 2022

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 don't become large. And right now, it looks as if they are becoming much larger actually. And we also see that this has long term impact. So if you lose some part of a school year, so for example, if you lose 1/3 of a school year, this, we can find or in the past, this was associated with a drop in lifetime income of 3, 4 or 5%. And so this, this can have huge implications for the generation of students affected. And so it's really important because we will have to live with COVID. And we need to make sure that we don't have to close schools, again, by investing in digital infrastructure and so on and making it possible that even when people are at home or this case, also not only for COVID, but also for other reasons that they can still participate in schooling. So this will be really important.

Christine Garrington  4:46 

Yes, indeed. Let's move away from COVID. One of the project's key aims was to investigate how the circumstances as we said that a child grows up in influences some of the most important decisions they make later on, you mentioned in your first answer about education and work and all of those key decisions that can take us down a certain path. Tell us a bit more about what you were hoping to get to really sort of get to grips with here.

Andreas Peichl  5:13 

So the starting point for research is rooted in the philosophical theories of distributive justice. And they, and also from an economic point of view, there's always the question, how to tackle inequalities. And in general, there are three ways to tackle inequalities. One is, the typical way is what we call redistribution. So this is, after all, the labour market outcomes, for example, are observed and we put a taxes and pay transfers and benefits to people to redistribute incomes. But the philosophical question then is, when we do this, how much do we want to redistribute how much inequality in the labour market do we want to have? And we know that for efficiency reasons, it's not good to have perfect equality, because then people don't have incentives to work and or to earn income. But we also know that very extreme inequality is not very good. But we don't know exactly where this optimal level is. But what we know is that there are other inequalities, where it's clear that this is something that we don't want. And this is what we in one paper, we call it unfair inequality, or this is inequality, where it's beyond your control your your poor, because there's something that you cannot influence. And this is what we wanted to investigate in this project. What are these circumstances, that children but also people later in life, have that make them for example, poor or rich? So is it the parental background, or we are in some work, we're also we're looking at the genetic endowment of people, but also other things, the places where you grow up could matter. And then it's important for policymakers, if you start tackling these inequalities already early in life, then maybe you don't need so much redistribution later in life. Because if there's a level playing field, and everybody has the same chances to achieve incomes, then typically inequalities in the labour market will be much less pronounced as they are today. So it was really the aim to see how much of the inequality that we observe today, for example, in labour earnings, labour market outcomes, how much of this can be explained by by early childhood circumstances already?

Christine Garrington  7:35 

And what were the key things to emerge from the work that you did?

Andreas Peichl  7:38 

The first thing is that, that we came up with some novel ideas and measures how to exactly measure this, this unfair bit of inequality to really disentangle this, not only in theory, but also empirically and, to some extent, also, using some some novel methods. For example, machine learning and big data ideas, in some ways or another. But also, the other thing was really trying to auto assemble also data, large datasets in paper in Sweden, really looking over several generations to see what is really the, the impact of these childhood circumstances. But what we see is really that childhood matters a lot. I mean, it's not surprising, everybody, I think, if you if you think back of your own childhood, or if you're, if you're having kids, you see how much impact parents can have have on children. And if there's inequality in let's say, how good parents are or how parents treat their children, then it's clear that this will lead to inequalities down the road. And so but I think what what's really interesting in our research was to put numbers on this to really see which inequalities seem to matter more and which maybe to a lesser extent, and then also trying to get at the main mechanisms and sort of the causal links between what it was what is it really that has an impact on on outcomes of children later in life?

Christine Garrington  9:15 

And you wanted to really sort of dig deep and see how those decisions that we've been talking about translate into later, later life social and economic outcomes, didn't you? What did you see there?

Andreas Peichl  9:27 

So yeah, we see that it's really that these these childhood circumstances matter in later life so it's, they matter directly in early childhood and then when when kids go to school or to high school, so really educational choices, but also educational performance is affected by these early childhood circumstances and then it continues, it's it's occupational choices, that matter it's but it's also we see impact on family formation - when to marry when to have children be it earlier or later in life, this is affected. And it matters for for labour market outcomes for career aspirations for, and then for for which jobs for which incomes people earn and so on. So it really matters all the way. We're also still working on projects to see whether it matters for early retirement decisions, for example, in general retirement decisions. So it seems to be that really the whole later life is affected by these early childhood circumstances.

Christine Garrington  10:39 

Yeah, that's so interesting. And I know that, you know, you are particularly keen to see whether you could actually, you know, really find causal links between early life circumstances and later life outcomes, you know causality, something that we know is always very, very difficult to show. But could you see that in any anything you did?

Andreas Peichl  10:58 

Yeah so we were looking, we were, of course, trying to establish causal links. But the perfect design research designed for to establish a causal link is to have some random allocation of the treatment and then have a control group. But it's, of course, not possible to randomly assign children to parents. So you need to come up with with different ways for for to identify these causal relationships. And typically, you can look at, at policy policy reforms and one policy that is affecting children are parental leave policies. So there's variation across countries, but also sometimes within countries. So for example, in Germany, there was a difference in these policies between former East Germany and West Germany. And what we see is children where the parents had more parental leave time, paid parental leave, when the kids were born, and were young, that these children later in life were happier. So they had a higher life satisfaction, then compared to children, where the parents didn't have as much paid parental leave, and then didn't take up as much parental leave. So it's really that also that these these policies at the very beginning at the start of the life, so like parental leave, has an impact. And so that's something where policy makers can start with. Another thing is what you can see is in schools, when you have, for example, all day schools versus only schools in the morning, or until until lunch, which is where there's a lot of variation, also within Germany, across states, you see that if you have these all day schools, there is a positive impact on on grades and also then later attending the university track. And in in the end on going to university for children. Which is basically also sort of to some extent levelling the playing field a bit because it's taking out the, the influence of part of the influence of parents on on the learning success of children. And so this is really this having this all day schools and parental leave and related policies can have an impact and can reduce inequalities later in life. So this is really important also for policymakers to think about it.

Christine Garrington  13:24 

Yeah, some really interesting and important findings from your project, Andrea's and I wonder for you, personally, if you like, was there anything that really surprised you or was a real standout?

Andreas Peichl  13:34 

So I think there were many interesting findings, and it was not completely unexpected that childhood circumstances matter. But I think what surprised me the most is that in a developed country, like Germany, it's these early childhood circumstances really matter all the way, basically until retirement. And it's and that a lot of policies are in place to with the aim of levelling the playing field, but they do not really succeed. So for example, in Germany, kids from parents with an academic background, about three quarters of these kids go to university, whereas only less than 20% of kids from non-academic background parents go to university. And it's all the schooling and the resources that are put into the system don't seem to help here. And so in many other countries, developed Western countries, it's not better in some countries like the US it's even worse. And so that's really something where I think the the policymakers in the in the next years need to put emphasis on to really make sure that we can somehow achieve equality of opportunities.

Christine Garrington  14:52 

Yeah, I wonder if you would say that there's anything that we've learned from your project that we really didn't know before?

Andreas Peichl  14:58 

We always knew that these circumstances matter, but we did not really maybe know how much and some of the causal links, but I think one thing, what we have also investigated and are still working on is also the impact of, for example, genetic endowment. And this is something where in recent years, there were advances where such data became available. And we can really see that, that this really matters for in their associations of your genetic endowment with other outcomes later in life. And this is really something to think about and what to do there. Because the policy implications there are not so clear.

Christine Garrington  15:39 

Yeah, that's such a fascinating area, for sure. Now, I mean, you've you've said a lot already about policy, which I think has been really, really interesting and important. But for all of those interested in tackling inequality through interventions in policy or practice, I wonder if there are any sort of essential takeaways or recommendations from this work that you would want to share?

Andreas Peichl  15:59 

So I think, if you want really want to tackle inequalities, much of the focus currently, I think, is on redistribution. So after all, the labour market outcomes are there and people earn incomes, but I think that's, that's really too late. Our project shows you need to start much earlier. So it's really you need to tackle it before people go to the labour market. So really education, and it's important and to to level, the playing field there. And there, especially it's the early childhood education so that other people have already shown that it's the first three or six years that are really, really important. And so for policymakers, they should put much more emphasis on, let's say, schooling and educating teachers for this early childhood education. And in a lot of countries. One thing is that child care, it's typically it's child care and not child education at these ages, as it's called, so it's making sure that the basically the kid survives the day, but it's, it's more important, so you need to really also make sure that the kids start learning something so this and then parents often have to pay for it, varying amounts depending on the country and so on. But so you should make this free for really from the beginning from starting with six, eight months old, this should be free and there needs to be enough educated teachers for the different age range. So to really start with very early ages, because typically what we see in many countries is that the children from from better off parents go to these these institutions, but not those from the from worse off parents and so it's really about the starting there to level the playing field because if you only do it later with redistribution, then it's too late and you've missed all the chances to change something.

Christine Garrington  17:57 

Thanks to Andres Peichl for discussing the findings and implications of DIAL's IMCHILD project. You can find out more about this and other dial research on the 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 earlier, the forthcoming episodes.