Facing visible strain in dollar funding markets during the Covid-19 pandemic, the Fed lowered the rate on the swap lines it had with five other central banks, and opened new ones in nine other currencies. Some of these were used, some not. We use this variation to show the impact of the swap lines on CIP deviations across currencies. The results confirm the analysis in Bahaj and Reis (2019): the swap lines put a ceiling on CIP rates only around the time of an auction.

Citation

Reis, R and S Bahaj (2020), ‘Central Bank Swap Lines during the COVID-19 Pandemic‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_391014

Social distancing interventions can be effective against epidemics but are potentially detrimental for the economy. Businesses that rely heavily on face-to-face communication or close physical proximity when producing a product or providing a service are particularly vulnerable. There is, however, no systematic evidence on the role of human interactions across different lines of business and about which will be the most limited by social distancing. In this paper we provide theory-based measures of the reliance of US businesses on human interaction, detailed by industry and geographic location. We find that 49 million workers work in occupations that rely heavily on faceto-face communication or require close physical proximity to other workers. Our model suggests that when businesses are forced to reduce worker contacts by half, they need a 12% wage subsidy to compensate for the disruption in communication. Retail, hotels and restaurants, arts and entertainment and schools are the most affected sectors. Our results can help target fiscal assistance to businesses that are most disrupted by social distancing.

Citation

Pető, R and M Koren (2020), ‘Business disruptions from social distancing‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_390369

It is well-known that group testing is an efficient strategy to screen for the presence of a virus. It consists of pooling n individual samples with a single test using RT-PCR. If no individual in the group is infected, the group test is negative. Thus, a single test may reveal this crucial information. We show how group testing can be optimised in three applications to multiply the power of tests against Covid-19: Estimating virus prevalence to measure the evolution of the pandemic, bringing negative groups back to work to exit the current lockdown, and testing for individual infectious status to treat sick people. For an infection level around 2%, group testing could multiply the power of testing by a factor of 20. The implementation of this strategy in the short run requires limited investments and could bypass the current immense shortage of testing capacity.

It is well-known that group testing is an efficient strategy to screen for the presence of a virus. It consists of pooling n individual samples with a single test using RT-PCR. If no individual in the group is infected, the group test is negative. Thus, a single test may reveal this crucial information. We show how group testing can be optimised in three applications to multiply the power of tests against Covid-19: Estimating virus prevalence to measure the evolution of the pandemic, bringing negative groups back to work to exit the current lockdown, and testing for individual infectious status to treat sick people. For an infection level around 2%, group testing could multiply the power of testing by a factor of 20. The implementation of this strategy in the short run requires limited investments and could bypass the current immense shortage of testing capacity.

Citation

Gossner, O and C Gollier (2020), ‘Group Testing against COVID-19‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_390370

This study quantifies the economic effect of a possible lockdown of Tokyo to prevent the spread of Covid-19. The negative effect of the lockdown may propagate to other regions through supply chains because of a shortage of supply and demand. Applying an agent-based model to the actual supply chains of nearly 1.6 million firms in Japan, we simulate what would happen to production activities outside Tokyo when production activities that are not essential to citizens’ survival in Tokyo were shut down for a certain period. We find that when Tokyo is locked down for a month, the indirect effect on other regions would be twice as large as the direct effect on Tokyo, leading to a total production loss of 27 trillion yen in Japan, or 5.3% of its annual GDP. Although the shut down in Tokyo accounts for 21% of the total production in Japan, the lockdown would result in a reduction in the daily production in Japan of 86% in a month.

Citation

Todo, Y and H Inoue (2020), ‘The propagation of the economic impact through supply chains: The case of a mega-city lockdown against the spread of COVID-19‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_390371

How many jobs can be carried out without putting workers at risk of contracting Covid-19? And how many of these jobs can be activated as soon as the most severe restrictions to mobility will be lifted? To which extent do these jobs belong to the chain involved in the war against Covid-19? In this paper, we aim to provide preliminary answers to these questions drawing on the case of Italy, the first Western country to be hit by the pandemic.

Citation

Caiumi, A, M Paccagnella and T Boeri (2020), ‘Mitigating the work-security trade-off‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_391015

I use a dynamic stochastic general equilibrium model to study the effects of the 2019-20 coronavirus pandemic in the US. The pandemic is modelled as a large negative shock to the utility of consumption of contact-intensive services. General equilibrium forces propagate this negative shock to the nonservices and financial sectors, triggering a deep recession. I use a calibrated version of the model to analyse different types of fiscal policies: (i) government purchases, (ii) income tax cuts, (iii) unemployment insurance benefits, (iv) unconditional transfers, and (v) liquidity assistance to service firms. I find that UI benefits are the most effective tool to stabilize income for borrowers, who are hit the hardest, while savers favour unconditional transfers. Liquidity assistance programs are effective if the policy objective is to stabilize employment in the affected sector.

Citation

Faria-e-Castro, M (2020), ‘Fiscal Policy during a Pandemic‘, COVID Economics 2, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-2#392514_392878_390372