We explore impacts of the pandemic crisis and associated restrictions to economic activity on paid and unpaid work for men and women in the UK. Using data from the Covid-19 supplement of Understanding Society, we find evidence that labour market outcomes of men and women were roughly equally affected at the extensive margin, as measured by the incidence of job loss or furloughing, but if anything women suffered smaller losses at the intensive margin, experiencing slightly smaller changes in hours and earnings. Within the household, women provided on average a larger share of increased childcare needs, but in an important share of households fathers became the primary childcare providers. These distributional consequences of the pandemic may be important to understand its inequality legacy over the longer term.
Hupkau, C and B Petrongolo (2020), ‘Work, care and gender during the covid-19 crisis‘, COVID Economics 54, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-54#392514_392930_391055
Using currently available data we develop a benchmark scenario that finds that a publicly-imposed social distancing rule to curb the spread of COVID-19 ought to be implemented for 12 weeks. Â We also identify alternative scenarios where the shorter duration social distancing programs seen throughout the United States may be efficient. Â Our approach is novel in that it accounts for uncertainty in transmission of the disease and the potential for permanent economic effects of social distancing rules. The social distancing rule is treated as an asset whose benefit is uncertain due to the inability to predict the evolution of the disease. The novel features of our approach allow us to draw two conclusions about the efficient timing of public social distancing programs in response to COVID-19. Â First, uncertainty in transmission leads to a risk premium that creates a modest incentive to delay closing and reopening the economy. Â Second, hysteresis in economic impacts of social distancing leads to hysteresis in the efficient time to reopen the economy. Â Because reopening results in a second wave of infections that may be worse than expected and social distancing rules create permanent economic impacts, it is efficient to delay reopening the economy longer than suggested by benefit-cost analyses of social distancing programs. Â In our benchmark scenario, this bias results in reopening 27 days too soon.
Finnoff, D and C Sims (2020), ‘Uncertainty, hysteresis and lockdowns‘, COVID Economics 54, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-54#392514_392930_390651
We document the transmission of social distancing practices from the United States to Mexico along migrant networks during the early 2020 Covid-19 pandemic. Using data on pre-existing migrant connections between Mexican and U.S. locations and mobile-phone tracking data revealing social distancing behavior, we find larger declines in mobility in Mexican regions whose emigrants live in U.S. locations with stronger social distancing practices. We rule out confounding pre-trends and use a variety of controls and an instrumental variables strategy based on U.S. stay-at-home orders to rule out the potential influence of disease transmission and migrant sorting between similar locations. Given this evidence, we conclude that our findings represent the effect of information transmission between Mexican migrants living in the U.S. and residents of their home locations in Mexico. Our results demonstrate the importance of personal connections when policymakers seek to change fundamental social behaviors.
Caballero, M, B Kovak and Y Tian (2020), ‘Social Learning along International Migrant Networks‘, COVID Economics 54, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-54#392514_392930_390652
We document large-scale urban flight in the United States in the wake of the COVID-19 pandemic. Populations that flee are disproportionately younger, whiter, and wealthier. Regions that saw migrant influx experience greater subsequent COVID-19 case growth, suggesting that urban flight was a vector of disease spread. Urban residents fled to socially connected areas, consistent with the notion that individuals were sheltering with friends and family or in second homes. The association of migration and subsequent case growth persists when instrumenting for migration with social networks, pointing to a causal association.
Coven, J, A Gupta and I Yao (2020), ‘Urban Flight Seeded the COVID-19 Pandemic Across the United States‘, COVID Economics 54, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-54#392514_392930_390653
We use data from Google Trends to predict the effect of the COVID-19 pandemic on future births in the United States. Â First, we show that periods of above-normal search volume for Google keywords relating to conception and pregnancy in US states are associated with higher numbers of births in the following months. Excess searches for unemployment keywords have the opposite effect. Â Second, by employing simple statistical learning techniques, we demonstrate that including information on keyword search volumes in prediction models significantly improves forecast accuracy over a number of cross-validation criteria. Third, we use data on Google searches during the COVID-19 pandemic to predict changes in aggregate fertility rates in the United States at the state level through February 2021. Â Our analysis suggests that between November 2020 and February 2021, monthly US births will drop sharply by approximately 15%. Â For context, this would be a 50% larger decline than that following the Great Recession of 2008-2009, and similar in magnitude to the declines following the Spanish Flu pandemic of 1918-1919 and the Great Depression. Â Finally, we find heterogeneous effects of the COVID-19 pandemic across different types of mothers. Â Women with less than a college education, as well as Black or African American women, are predicted to have larger declines in fertility due to COVID-19. Â This finding is consistent with elevated caseloads of COVID-19 in low-income and minority neighborhoods, as well as with evidence suggesting larger economic impacts of the crisis among such households.
Chen, W, S Lohmann and J Wilde (2020), ‘COVID-19 and the Future of US Fertility: What Can We Learn from Google?‘, COVID Economics 54, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-54#392514_392930_390654