Working papers
Working papers
Child Penalties and Public Childcare Shortages under Fiscal Austerity (with Emanuele Fedeli, working paper available here)
There is ample debate on whether and for whom policies might affect the child penalty in women’s earnings. Here we link it to local fiscal rules affecting public childcare provisions. We rely on Italian administrative data on private employees complemented by municipal budgets, and combine a regression discontinuity design with event studies.
We find that municipalities subjected to fiscal austerity face relative shortages driven by fewer daycare slots and (accepted) applications. The effects of these shortages are mostly null, except for women with higher earnings in Italy’s otherwise ‘daycare-rich’ Centre. There, child penalties increase by up to a quarter, as shortages are compensated via shorter weeks and part-time employment. When public childcare is lacking, some women use more parental leave, but without incurring in further earnings losses. Attending to income and geographical disparities might be crucial to understand and remedy gendered economic inequalities spurred by shortages and otherwise limited daycare.
Linking Household Incomes to Youth Well-Being: An Analysis of Youth-Reported Deprivation and Caregiving with Growing Up in Australia (with Yekaterina Chzhen and Gerry Redmond)
Access to Social Security Benefits amid Reforms and Scandals (with Nicolás Soler)
Poor Rich Parents: Labour Market Effects of De-Subsidising Childcare for Households with High Incomes (with Olivier Marie)
Wealth Inequalities and the Emotional Labour of Parenting
Growing Up after a Recession: Layoffs, Housing Insecurity and Child Well-Being in the Long Run
The Sources of Research Variation in Economics (many-analysts project led by Nick Huntington-Klein and Claus C. Portner; NBER Working Paper available here, forthcoming in Journal of Economic Perspectives)
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