Weather, mobility and the evolution of the Covid-19 pandemic

Purpose: The authors investigate the effect of weather and mobility on the spread of the Covid-19 pandemic. Design/methodology/approach: The authors first estimate the effective reproduction number (Rt) as a proxy of the spread of the Covid-19 pandemic and then study the relationship between the latter and weather and mobility in a panel data framework. The authors use US daily infections data between February and September of 2020 at the county level. Findings: The authors find that lower temperatures are associated with a higher Rt, and this effect is greater at temperatures below 0°C. In addition, mobility reductions related to certain types of locations (retail and recreation, transit stations and workplaces) are effective at reducing Rt, but it is an increase in the time spent in parks that most helps reduce the spread of the pandemic. Originality/value: The estimates imply that a 20°C fall in temperature from summer to winter would increase Rt by +0.35, which can be the difference between a well-controlled evolution and explosive behavior of the spread of the virus. Applying these coefficients estimated with US county data to aggregate series from other countries helps explain the resurgence of the pandemic in the Northern Hemisphere during the winter of 2020. The results show that mobility reduction and social distance are best policies to cope with the Covid-19 outbreak. This strong policy lesson will help facing similar outbreaks in the future. [ FROM AUTHOR] Copyright of Journal of Economic Studies is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Can news help measure economic sentiment? An application in COVID-19 times.

We construct a new newspaper-based sentiment indicator for Spain that allows to monitor economic activity in real-time. As opposed to survey-based confidence indicators that are released at the end of the month, our indicator can be constructed on a daily basis. We compare our index with the popular Economic Sentiment Indicator of the European Commission and show that ours performs significantly better in nowcasting the Spanish GDP. Moreover, it proves to be helpful to predict the current COVID-19 recession from an earlier date.