We build a novel interregional computational input–output model to assess the economic impact of lockdowns in Italy. Lockdowns are modeled as shocks to labor supply, calibrated on regional and sectoral employment data coupled with the prescriptions of government decrees. When estimated on data from the first lockdown, our model closely reproduces the observed economic dynamics during spring 2020. We also show that the model delivers a good out-of-sample performance during fall and winter 2020 and demonstrate that it can be used to analyze counterfactual scenarios.
We extend the regional input-output model for the economic impact assessment of Covid-19 lockdowns in Italy proposed in Reissl et al. (2021) by incorporating the effects of changes in mobility on the level and composition of consumption demand. We estimate the model on sectoral data for 2020 and perform an out-of-sample validation exercise for the first half of 2021, finding that the model performs well. We then evaluate the relative importance of demand-and supply-side factors in determining our simulation results. During the national lockdown of spring 2020 the impacts of supply-side (labor) shocks can account for the vast majority of output losses. In the following stages of the epidemic income and mobility-related effects on final demand play pivotal roles at the aggregate and regional levels, as well as for most sectors. While policies supporting demand may hence be appropriate, their effectiveness may be hampered when demand is chiefly restrained by the mobilityrelated effect, and not by income.
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