The social scientist using a wealth of data to identify policies that reduce inequality

Luca Maria Pesando is a social science researcher at New York University Abu Dhabi. Luca studies how families are changing around the world, particularly in low- and middle-income countries. He is also working with policy organizations and connecting with government representatives to influence policy. Annie Brookman-Byrne talks with Luca about the origins of his passion for this area, and the most exciting questions he’s exploring.

Annie Brookman-Byrne: What are the most important questions about family structures and education you’ve been trying to answer?

Luca Maria Pesando: Here are just a few examples of the questions I’m exploring: How and when do the multiple family forms and structures that exist in the world change in response to societal forces such as educational expansion, industrialization, and technological progress? Do these changes impact children and other members of the family? I’m also investigating why child marriage persists, why fertility is not declining in parts of sub-Saharan Africa, how educational expansion affects how couples are formed, and why some couples exhibit more gender-equal behaviors than others. In my research on school systems, I study how families and schools can narrow or widen educational inequalities as children move from one grade in school to the next.

“It is therefore important that policymakers pay more attention to structural barriers and gender norms when devising policies.”  

I’m also trying to find out how inequalities in resource-deprived areas might be reduced. What is the most effective path – enacting policies giving cash to poorer families, changing age-at-marriage laws, modifying divorce laws, implementing educational interventions, or running empowerment programs? The answers are often complex. In one of my studies, I found that giving parents in rural Morocco cash was effective in reducing school dropout and boosting school progression among girls. However, cash did not address a significant barrier to further progression, namely the fact that girls were relied upon to carry out unpaid work, such as washing dishes and fetching water, leaving less time for them to engage in learning opportunities.

In another piece of research, I found that after Mali lowered the minimum legal age for girls to marry from 18 to 16 in 2011, it led to more teen marriages, particularly among the most disadvantaged, such as girls lacking education. Together, these findings suggest that new policies in the realm of family or education may be effective only for certain groups of children, and may even exacerbate inequalities if not carefully crafted. It is therefore important that policymakers pay more attention to structural barriers and gender norms – such as confining girls to the role of primary caregivers in the household – when devising policies.    

ABB: Where did your passion for working on these questions come from?

LMP: Ultimately it can be traced back to my childhood. I travelled regularly to sub-Saharan Africa and Latin America to assist my father in his volunteer medical campaigns, which included founding an eye hospital in rural Kenya. But instead of instilling in me a passion for medicine, the poverty and inequality I witnessed daily in families and households inspired me to work to effect change by pursuing a career in research and policy analysis.

ABB: How will your research help children?

LMP: This is a big challenge, given the gap between social science research, policy making, and policy implementation. To help bridge this gap, I seek to produce policy-relevant interdisciplinary work that will ultimately have a positive impact on children’s lives, either directly or indirectly.

And of course, the importance of data shouldn’t be overlooked! Collecting and analyzing data may seem an indirect way of helping children. But estimating how different family structures affect children’s health and educational outcomes, for example, can be really useful for other researchers and policymakers. Data can also be used to determine which policies will be most effective at compensating for family disadvantages.

“Data can also be used to determine which policies will be most effective at compensating for family disadvantages.”

The implications of other projects I work on are more direct. For example, I am investigating family- and school-level policies to address issues related to extended and often unanticipated school breaks, such as during the pandemic. I am also using recent advances in big data, digital technology, and behavioral science to help identify cost-effective and potentially scalable interventions that may narrow gaps between students from different socioeconomic backgrounds.

ABB: What ideas are you most excited about pursuing next?

LMP: The COVID-19 pandemic prompted me to reflect deeply on the use of digital technologies in daily life. I would like to understand the new and complex interactions between the rise of digital technologies, changes in family and gender dynamics, and children’s learning opportunities in and out of school. How are these changes redefining the landscape of resource-deprived societies, especially in crisis situations?

To cite one example, digital technologies such as mobile phones, tablets, and other devices to access the internet are providing women with better information and greater access to reproductive health services. This is shaping women’s decision-making power and redefining gender roles. These shifts, together with technology-enabled policies such as remote and flexible work, may affect things like fertility and marital dynamics, which in turn affect children’s outcomes. In addition to narrowing digital skill divides, might technology diffusion reduce inequalities in women’s and children’s lives?

As digital technology becomes more and more prevalent, I want to learn more about its potential to reduce inequality in both families and education systems. I hope this work will lead to policy recommendations that can have a real impact for families and children.