Non-pharmaceutical interventions adopted by governments to halt the spread of Sars-Cov2 are thought to have non-trivial consequences for the economy. The purpose of this paper is to estimate the economic impact of non-pharmaceutical interventions in Italy, by taking advantage of timing differences in their implementation across regions and employing mobility data to proxy activity. To achieve this, we estimate one-way and two-way fixed effects models on a large sample of Italian provinces. We also isolate a set of well-defined quasi-natural experiments in which one region goes from a lower to a higher tier of restrictions, while a neighbouring region remains in the lower tier, for which we can estimate difference-in-differences and continuous treatment models. Moreover, in order to observe whether the impact of restrictions has changed over time, we split the sample around December 2020 and replicate the analysis in each subsample. Our case studies indicate that an Italian province moving from tier 2 to tier 3 in the system of restrictions can expect a fall in mobility of between 12 and 18 percentage points. Thus, we provide evidence of the negative effects of non-pharmaceutical interventions on economic activity. Finally, we provide some evidence that the effectiveness of NPIs in reducing mobility is likely to reduce over time, which has important policy implications. Our estimations are robust to a number of checks
