Assessing the Economic Effects of Lockdowns in Italy: A Dynamic Input-Output Approach
Assessing the Economic Effects of Lockdowns in Italy: A Dynamic Input-Output Approach
复制标题
评估意大利封锁的经济影响：动态投入产出法
DOI：
10.2139/ssrn.3778996
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
A. Roventini
中科院分区：
文献类型：
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作者：
Severin Reissl;Alessandro Caiani;F. Lamperti;M. Guerini;Fabio Vanni;G. Fagiolo;Tommaso Ferraresi;Leonardo Ghezzi;M. Napoletano;A. Roventini
许多国家在COVID-19疫情后实施了前所未有的封锁措施，因此需要评估其经济成本的工具。为此，我们提出了一种新的动态投入产出模型框架，我们应用于封锁在意大利的经济影响的估计。封锁措施被视为对可用劳动力供应的冲击，根据区域和部门就业数据以及强制关闭特定行业的总理法令的规定进行校准。我们使用意大利各地区的投入产出表，根据2020年春季首次封锁的数据估算模型，然后进行模拟，以评估区域和部门影响。我们发现，尽管我们的框架很简单，但该模型能够再现大多数行业在封锁引发的低迷和随后的复苏期间观察到的动态。这种匹配经验数据的能力也被一个小的样本外预测工作所证实。我们随后亦模拟于2020年秋季及冬季实施的第二套“软性”封锁措施，以评估其影响，并将其与第一套“硬性”封锁措施进行比较。整体而言，我们相信，我们的框架的简单性和简约性使其适合为不同封锁措施的经济影响提供快速和合理准确的评估。
The unprecedented lockdown measures implemented by many countries in the wake of the COVID-19 pandemic have created a need for tools to assess their economic costs. For this purpose, we present a novel dynamic input-output modelling framework which we apply to an estimation of the economic impact of lockdowns in Italy. Lockdown measures are treated as shocks to available labor supply, being calibrated on regional and sectoral employment data coupled with the prescriptions of the prime ministerial decrees mandating the closure of specific industries. Using input-output tables for the Italian regions, we estimate the model on data from the first lockdown during spring 2020 and then simulate it to assess the regional and sectoral impacts. We find that, despite the simplicity of our framework, the model is able to reproduce the observed dynamics during the lockdown-induced downturn and subsequent recovery fairly closely for most sectors. This ability to match the empirical data is also confirmed by a small out-of-sample forecasting exercise. We subsequently also simulate the second set of ‘softer’ lockdown measures implemented during autumn and winter of 2020 in order to evaluate their impact and compare them to the first, ‘hard’ lockdown. Overall, we believe the simplicity and parsimony of our framework make it suitable for providing quick and reasonably accurate evaluations of the economic effects of different lockdown measures.