Working papers
Working papers
BACKGROUND
Family resilience foregrounds personal and relational transformations that help families overcome adversity. Yet, why and from whom resilience is required is often overlooked. Economic downturns are exemplary sites to examine these questions.
OBJECTIVE
I study children’s prosocial development and caregiving as an expression of family resilience in households affected by job loss during the Great Recession in Ireland. From a social reproduction perspective, I posit that the demands and capacities for resilience are unequally shared within families, across generations and following a gendered pattern.
METHOD
I rely on cohort data from children’s early years to adolescence (Growing Up in Ireland, 2008-2022) to estimate growth-curve and OLS models for prosocial development and outcomes tied to caregiving.
FINDINGS
Children whose mothers experienced job loss exhibit steeper prosocial development. Girls with younger siblings drive this finding. At age 13, the same group is more likely to share and fulfil caregiving duties. Findings suggest that mothers might have leaned on their children to maintain some paid work after job loss, stimulating their daughters’ prosocial development and involvement in caregiving.
CONTRIBUTION
The study highlights how economic downturns reinforce the gendered and generational underpinnings that bind the paid and unpaid work of family resilience.
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)
Earning More but Less Secure: Unpaid Care, Paid Work, and the Design of Cash Transfers
Adequate or Scandalous? Understanding Non-take-up of Social Security Benefits (NWO XS Grant 2025)
Child Poverty and Well-being: A Child-Centred Perspective (with Yekaterina Chzhen)
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