The coronavirus pandemic has created a new kind of culture shock. It has affected essential and highly personal elements of many people’s lives within their own environments. A culture shock of this magnitude has not occurred since WWII. When the pandemic ends, societies will be quite different from what they were in the pre-coronavirus era.
Argentina, Chile, Colombia and Canada have joined a growing list of nations in barring travel to and from the United Kingdom as part of a bid to block a new strain of coronavirus that is sweeping across southeastern England.
The development of contact tracing apps was a promising response to the COVID-19 pandemic, but too few people appear to be using the apps to make them effective. This column offers three economic explanations for non-use: 1) the economic and social costs of quarantine, 2) underestimation of social externalities of app use, and 3) procrastination. It argues for the immediate application of carrots in the form of financial incentives and sticks in the form of regulation to accompany holistic policies that cover education, public campaigns, trust building, accountability, and nudging.
Governments and researchers have been working with an extremely ambitious timetable to provide billions of people with immunity to the new coronavirus. Now, the first vaccines are being distributed, spurring hope that the pandemic’s end is in sight.
The Netherlands has banned flights carrying passengers from the United Kingdom after Dutch authorities found the first case of the new, more infectious coronavirus strain that is circulating in England.
The US Congress appeared poised to vote on Sunday on a $900bn coronavirus aid package after senators struck a late-night compromise to clear one of the final hurdles, a dispute over Federal Reserve pandemic lending authorities.
There is widespread concern about the toll of the pandemic on local economies, but little causal evidence to assess its real costs. This column presents an impact evaluation of the local economic effects of the COVID-19 crisis in Italy, based on a counterfactual application of machine learning algorithms. It documents that, to date, impacts on employment and firms have been dramatically uneven across the Italian territory and spatially uncorrelated with the epidemiological pattern of the first wave. It shows that this heterogeneity is associated with sectoral specialisation, exposure to social aggregation risks, and pre-existing labour market fragilities. Finally, it argues that such diverging local trajectories call for a place-based approach in the policy response to the crisis.