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We study the joint design of nonlinear income and education taxes when the government pursues redistributive objectives. A key feature of our setup is that the ability type of an agent can affect both the costs and benefits of acquiring education. Market remuneration of agents depends on both their innate ability type and their educational choices. Our focus is on the properties of constrained efficient allocations when educational choices are publicly observable at the individual level, but earned income is subject to misreporting. We find that income-misreporting (IM) affects the optimal distortions on income and education and shed light on the reasons for it and mechanisms through which it is done. We show how and why IM strengthens the case for downward distorting the educational choices of low-ability agents. Finally, we find that IM provides another mechanism that makes commodity taxation useful.

The standard model of household behavior predicts that couples cooperate to maximize family income. This paper shows that gender identity norms repre- sent an important friction preventing family income maximization. For identi- fication, we focus on an Italian policy that grants a large tax credit to the main earner in a couple when the second earner reports income below a cutoff. Using new tax returns data, we show large bunching responses at the tax credit cut- off from second earner women, but no response from second earner men. This result suggests that household decisions are not Pareto-efficient when men are the second earner within the couple. Gender differences in bunching mostly emerge after marriage and childbirth, and do not reflect any gender-specific dif- ference in scope for bunching. In support of the view that gender norms drive our results, we find that gender differences in bunching are relatively larger among immigrants coming from more conservative societies, and natives liv- ing in more gender-traditional municipalities. Additionally, these results have important implications for gender inequality: we show that the spouse tax credit persistently limits women’s careers and amplifies the gender income gap.

This paper investigates whether the characteristics of locally elected officials influenced
excess mortality during the COVID-19 pandemic. Using data on Italy—
one of the first countries to be severely affected—we examine whether mayoral
education influenced municipal-level mortality outcomes. We estimate weekly
excess mortality using official death statistics and a Bayesian hierarchical spatiotemporal
model. To address endogeneity in political selection, we implement
a close-election Regression Discontinuity Design. We find that college-educated
mayors significantly reduced mortality during the first wave of the pandemic, by
lowering both the likelihood of excess deaths and the excess mortality rate. These
effects are not observed in the second wave, likely due to policy convergence and
a stronger role played by national and regional institutions. Our design interprets
education as a proxy for broader leadership traits, such as decision-making capacity
under uncertainty. The findings underscore that political selection can have
real demographic consequences, shaping population outcomes during crises.