What can we learn from Italy? Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures.

A new paper published in the Journal of Population Economics investigates for the Italian case how to identify the pandemic early in “dirty” data and how to measure the success of lockdowns.

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Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures

Luca Bonacini, Giovanni Gallo & Fabrizio Patriarca

Journal of Population Economics (2020), published ONLINE FIRST. PDF free accessible.
Based on GLO Discussion Paper No. 534, 2020

GLO Fellow Fabrizio Patriarca

Author Abstract: Identifying structural breaks in the dynamics of COVID-19 contagion is crucial to promptly assess policies and evaluate the effectiveness of lockdown measures. However, official data record infections after a critical and unpredictable delay. Moreover, people react to the health risks of the virus and also anticipate lockdowns. All of this makes it complex to quickly and accurately detect changing patterns in the virus’s infection dynamic. We propose a machine learning procedure to identify structural breaks in the time series of COVID-19 cases. We consider the case of Italy, an early-affected country that was unprepared for the situation, and detect the dates of structural breaks induced by three national lockdowns so as to evaluate their effects and identify some related policy issues. The strong but significantly delayed effect of the first lockdown suggests a relevant announcement effect. In contrast, the last lockdown had significantly less impact. The proposed methodology is robust as a real-time procedure for early detection of the structural breaks: the impact of the first two lockdowns could have been correctly identified just the day after they actually occurred.

More from the GLO Coronavirus Cluster

Access to the newly published complete Volume 33, Issue 4, October 2020.

Yun Qiu, Xi Chen & Wei Shi, Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China
Journal of Population Economics 33, 1127–1172 (2020). OPEN ACCESS

Fabio Milani: COVID-19 outbreak, social response, and early economic effects: A global VAR analysis of cross-country interdependencies. Journal of Population Economics, (2020). https://doi.org/10.1007/s00148-020-00792-4


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