The economist working on how to reduce inequalities from childhood

We spoke to Gabriella Conti, Professor of Economics at the Department of Economics at UCL about her life and work.

Thinking back to her childhood in Naples, Gabriella Conti remembers walking into class at the start of a new school year and finding that the desks had changed position. The year before there was one desk for each child, but now the teacher had pushed them together to make a horseshoe shape. “On my side of the table, our parents were doctors, lawyers, dentists,” she remembers. “And on the other side were the children of an electrician, a grocer, a street cleaner. I don’t know why.”

As the year went on, she noticed that the children on the other side of the classroom were ill more often, tended to get lower marks, and were more likely to come to school without having done their homework. “Sometimes I would ask them: ‘why didn’t you do it?’ And they would say, ‘I didn’t have anyone who would help me,’ or ‘I didn’t have time; I had to help at home,’” she remembers. “This stays with you. And I thought: maybe when I grow up I can help to understand why this is happening.”

Today, that is what she does. As a professor of Economics at UCL, a Research Fellow at numerous other institutions, and an associate editor at two health economics journals, she studies how inequalities start in the home and how society can reduce them. Her research focuses on the economics of health, human development, and biology. It has sharpened our understanding of the causes and consequences of inequalities in health, and the effects, costs and benefits of policies to reduce them. She’s particularly interested in how conditions in early life affect wellbeing over a person’s life. “I’m a huge believer that if you want to make people more equal you have to start early,” she says. “Changing things later is really hard.”

One of her recent papers, for example, showed that combining services for children at one location - such as health services, parenting support programmes, childcare and early education - means children are much less likely to need go to hospital a few years down the line. Studying Labour’s Sure Start centres, she found that one extra centre per thousand children prevented around 2,900 hospitalisations a year when a child was five years old. For 11- to 15-year-olds, each extra centre prevented more than 13,150 hospitalisations.

Another recent paper strengthened the evidence that a home visiting programme during pregnancy and early childhood improves interactions between mothers and girls. If you are looking for policy options to improve children’s health and life chances, this is exactly the kind of evidence you need.

Using unconventional data

She enjoys using approaches and datasets that some economists would find unconventional. One of her papers looked at how parents’ beliefs connected with how they parented during the pandemic as a way to understand how to design policy better. Conti surveyed parents’ decisions during lockdown about whether to take their children to nursery despite the infection risks, play with them, or take them to play at friends’ houses. She also looked at diaries of how parents actually used their time, and compared parental time use with parents’ beliefs, which she elicited via an online survey. To explore the determinants of beliefs, she collected information on parents' main concerns via an open-ended question and analysed their responses using natural language processing techniques. This analysis revealed a correlation between perceiving lower returns on investment and expressing negative sentiment. The paper strengthened the evidence that parents’ perceptions of infection risk varied with education levels. But it also added a twist: so did their perceptions of how important it was to give children time to play. The paper reminds us that parents’ beliefs affect their choices, so any policy that wants to encourage take-up of childcare should tailor how they provide information, depending on whom it is targeting. Another paper used foetal ultrasound scans to show that inequalities emerge already in the womb, and to measure the factors determining birth weight, helping to clarify how it should be used as evidence for babies’ health, and providing a rationale for prenatal interventions. 

She attributes an interest in using these kind of datasets to the influence of her mother, a biologist. “When I was a child, she was always buying books for kids with cartoons about the human body, biology, cells, how babies are born, how we reproduce. So ever since I knew how the body worked, I became really interested in why one body ends up working better than another,” she says.

Using economics to understand the patterns of the everyday

Her undergraduate degree was law, but it contained modules on economics. She found in those modules something the law couldn’t offer: a powerful framework by which to understand the everyday circumstances hidden behind inequalities.“ People sometimes ask me why you use economics to study these things,” she says, “and the answer is that it provides very robust tools to analyse and interpret data, which you can use to inform policy to improve lives and make the world a bit better,” she says.

“A natural way of thinking about child development is that a child’s health and other dimensions of human capital depend partly on biology and partly on what parents do.” But that approach is limited, she argues. An economic model, on the other hand, makes it easier to think about these factors in a much more structured way, partly because it offers a framework to think also about the constraints people face. “Of course, we don’t have unlimited resources, we can’t do everything we want, and this is probably more true for parents,” she says. “That allows you to think about why some parents spend more time than others helping their children, giving them nutritious food, breastfeeding, taking them to the doctor if they’re unwell, reading or talking to them. You can start thinking: ‘is it the money? Maybe they have a budget constraint. Maybe they don’t have time. OK, there’s a time constraint. Maybe they actually don’t know. So there’s an information constraint. That framework can give you a better understanding of what’s going on,” she says, “which gives you a better way to think about how to improve things.” A financial constraint might be lifted with credit relief, subsidies, tax free childcare, or perhaps vouchers for nutritious food; a time constraint by maternity leave or parental leave; a knowledge constraint with information, and so on. “Without this framework, I would find it much harder to think about these problems,” she says.

Access to data 

One of her biggest disappointments in British politics of recent years is that so much of the data that is the lifeblood of this kind of work is not routinely collected in a harmonised fashion at a local level. She gives the example of the data on the early years workforce. After all, a health intervention for children at national level can only be as effective as the workforce that provides it. That makes it important to understand who is providing health visits and other interventions that make a difference to children, how qualified that workforce is, its size and professional make up, and so on. But both budget cuts and the decentralisation of many public health responsibilities have made this information very hard and time-consuming to collect (e.g. via Freedom-of-Information Requests) and to study.

If a policymaker was looking for something relatively cheap and politically uncontested to do that was likely to help improving life chances for millions of children who will be born in the coming decades, they could start by making sure this data on the early years workforce (starting from health visitors) is collected at local level, and linked with data on children’s outcomes. That would enable economists like Conti, driven by a desire to understand how to reduce inequalities from childhood, to get on with their work.