Early studies show that children might be ‘resilient’ when families navigate economic crises and related job loss. What resilience means is unclear, though, and why and from whom resilience is required has seldom been examined. I theorise children’s prosociality – helping, supporting and comforting others – as a form of transformative resilience. From a social reproduction perspective, I also consider how prosociality imbues and is influenced by caregiving relationships within families. I examine how children’s prosociality/caregiving (unpaid labour) developed in response to parents losing and regaining employment (paid labour) amid the Great Recession in Ireland.
I rely on cohort data from children’s early years to adolescence (Growing Up in Ireland, 2008-2022). I estimate growth-curve and OLS models for prosocial development and outcomes tapping into paid and unpaid labour. Associations with parental job loss are identified net of observables while outlining conditions for causal claims.
Children whose mothers experienced job loss are rated more prosocial than their peers from middle childhood onwards. Girls with younger siblings drive this finding. At age 13, the same group is more likely to provide regular care within the household, while their mothers scale back caregiving and reprise paid work after heightened childcare responsibilities during the crisis.
The study contributes to debates on the formation of prosociality, the intergenerational consequences of job loss, and the household division of labour among adults and children. Findings suggest focusing on if and how families cope with a context unequally structured by (labour) markets and gender norms.
The Sources of Research Variation in Economics (Nick Huntington-Klein, Claus C. Portner, Ian McCarthy, and The Many Economists Collaborative on Researcher Variation)
We use a rigorous three-stage many-analysts design to assess how different researcher decisions — specifically data cleaning, research design, and the interpretation of a policy question — affect the variation in estimated treatment effects. A total of 146 research teams each completed the same causal inference task three times each: first with few constraints, then using a shared research design, and finally with pre-cleaned data in addition to a specified design. We find that even when analyzing the same data, teams reach different conclusions. In the first stage, the interquartile range (IQR) of the reported policy effect was 3.1 percentage points, with substantial outliers. Surprisingly, the second stage, which restricted research design choices, exhibited slightly higher IQR (4.0 percentage points), largely attributable to imperfect adherence to the prescribed protocol. By contrast, the final stage, featuring standardized data cleaning, narrowed variation in estimated effects, achieving an IQR of 2.4 percentage points. Reported sample sizes also displayed significant convergence under more restrictive conditions, with the IQR dropping from 295,187 in the first stage to 29,144 in the second, and effectively zero by the third. Our findings underscore the critical importance of data cleaning in shaping applied microeconomic results and highlight avenues for future replication efforts
Child Penalties and Public Childcare under Fiscal Austerity (with Emanuele Fedeli, Visitinps Fellowship Grant 2023)
Poor Rich Women: Labour Market Effects of De-subsidising Childcare for Households with High Incomes (with Renske Stans and Olivier Marie)
State-Sanctioned Insecurity as a New Social Risk: The Case of Carer's Allowance
Adequate or Scandalous? Understanding Non-take-up of Social Security Benefits
Why Family Income Matters: A Child-centred Perspective