UC Berkeley

This dissertation studies topical questions in empirical macroeconomics. What is the long-term aggregate effect of public investments targeting distressed regions? What was the role of demand factors in driving the increase in inflation after the COVID-19 pandemic? What is the impact of balanced budget requirements on local economic activity? From a methodological standpoint, I employ rigorous causal inference techniques borrowed from applied microeconomics to discipline macroeconomic models and derive consistent aggregate results.

In the first chapter, I study the long-term, aggregate effects of regional development programs on industrial production. Between 1950 and 1992, Italy implemented one of the largest regional development programs in history to foster industrialization in its Southern regions. Exploiting three distinct identification strategies, I estimate that the big push substantially increased local manufacturing activity, with gains persisting up to 2011. At the same time, the program shifted production across regions, limiting labor reallocation from the lagging South to the industrialized Center-North. To account for crowding-out effects, I develop a multi-region growth model with public capital and factor mobility, allowing for increasing returns to scale through regional agglomeration economies. Calibrating the model to match my reduced-form estimates, I find that, despite large crowding-out effects, the program induced gains in national industrial production that outweighed its costs. These results document that big push programs can promote cost-effective structural change in distressed regions, but general equilibrium effects substantially mitigate their impact on aggregate output.

In the second chapter, co-authored with Giulia Gitti, we estimate the slope of the Phillips curve before, during, and after COVID. To do so, we exploit panel variation in inflation and unemployment dynamics across US metropolitan statistical areas (MSAs), using a shift-share instrument to isolate demand-driven fluctuations in local unemployment rates. We specify a two-region New-Keynesian model to derive the slope of the aggregate Phillips curve from our MSA-level estimates. We find that the slope of the Phillips curve dropped to zero during the pandemic and more than tripled, relative to the pre-COVID era, from March 2021 onward, reaching its highest level since the mid-1970s. These estimates allow us to quantify the extent to which US post-pandemic inflation is propelled by demand factors. Demand-driven economic recovery explains around 1.4 out of the 5.6 percentage-point increase in all-items inflation observed from March 2021 to September 2022. Had the slope of the Phillips curve not steepened after COVID, the demand contribution to the rise in inflation would have been small and statistically insignificant.

In the third chapter, co-authored with Francesco Filippucci and Simone Valle, we estimate short-term income multipliers stemming from budget balance requirements (BBRs). Fiscal consolidation programs often entail BBRs imposed by central governments on 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 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 is significantly lower than 1.5, the prevailing estimate in the literature.