My approach relies on using policy evaluation to derive relevant structural parameters, focusing on Labor and Public Economics. My PhD thesis exploits a program for NEETs, an individual learning account, and local budget rules to derive insights on -- respectively -- job search behavior, the elasticities of training supply, and the local spending multiplier.

Job Market Paper

What Do NEETs Need? The Effect of Activation Policies and Cash Transfers

Slides - Draft - French Ministry of Labor policy note - Press

Active and passive labor market policies are often used jointly, but the literature has only evaluated them one conditional on the other. This paper evaluates a flagship French program for disadvantaged youth Not in Employment Education or Training (NEETs) that provided a year of cash transfers and intensive activation measures. I exploit the staggered adoption of the program using a classical event study and a difference-in-differences methodology that extends De Chaisemartin and D'Haultfoeuille (2020) to a setting where individuals enter the population of interest in cohorts. The results highlight a strong positive joint effect of active and passive policies (+21 percentage points in employment, +63% with respect to control) after youths exit the program. During program enrollment, I show that part-time employment decreases in the first semester -- when youths are busy in activation measures -- while in the second semester the decrease is concentrated in income brackets where the cash transfer is phased-out with labor income. This suggests that cash transfers and lock-in from training reduce youth employment, but this is more than compensated by the positive effect of activation measures.

Work in progress

Who Profits from Genearal Training Subsidies? Evidence from a French Individual Learning Account

Joint with E. Corazza

Slides- Draft

Workers could under-invest in general training, hence governments often subsidize lifelong learning. Yet, how effective are subsidies to general training? This paper studies the effect of the French Individual Learning Account (CPF), a scheme endowing all workers with generous training credits to be spent on the training market. We show that the total amount of training undertaken is not significantly affected by the subsidy. This happens because, in equilibrium, more than half of the benefit of the subsidy is captured by training producers through a significant change in prices. Moreover, for every 1% change in the subsidy, producers profits react by 0.17%, but no significant effect on the entry/exit of firms in the training market is observed. Our results can be rationalized with an inelastic demand for training and imperfectly competitive training markets. Under such conditions, subsidies to lifelong learning end up being a simple transfer to training producers and consumers, with no effect on aggregate welfare.

Balanced Budget Requirements and Local Austerity Multipliers

Joint with A. Cerrato and S. Valle


Fiscal consolidation often entails balanced budget requirements (BBRs) for local governments. However, little is known about the effects of BBRs on economic activity, as most quasi-experimental estimates of local fiscal multipliers stem from windfall expansionary shocks. This paper studies the 2013 extension of a BBR to Italian municipalities below 5,000 residents. Tighter rules pushed local governments to increase their net budget surplus by 0.6\%-1\% of local income. Treated municipalities cut capital expenditures, rather than decreasing current expenditures or raising taxes. The estimated multiplier is not statistically different from zero and significantly lower than 1.5, the prevailing estimate in the literature.


Did Covid-19 hit harder in peripheral areas? The case of Italian municipalities

Joint with F. Armillei and T. Fletcher

Published on Economics and Human Biology - Preprint - A previous version circulated as a LOL working paper - Press article.

The first wave of Covid-19 pandemic had a geographically heterogeneous impact even within the most severely hit regions. Exploiting a triple-differences methodology, we find that in Italy Covid-19 hit relatively harder in peripheral areas: the excess mortality in peripheral areas was almost double that of central ones in March 2020 (1.2 additional deaths every 1000 inhabitants). We leverage a rich dataset on Italian municipalities to explore mechanisms behind this gradient. We first show that socio-demographic and economic features at municipal level are highly collinear, making it hard to identify single-variable causal relationships. Using Principal Components Analysis we model excess mortality and show that areas with higher excess mortality have lower income, lower education, larger households, lower trade and higher industrial employments, and older population. Our findings highlight a strong centre-periphery gradient in the harshness of Covid-19, which we believe is also highly relevant from a policy-making standpoint.