We study the spread of SARS-CoV-2 infections and COVID-19 deaths by county poverty level in the US. We first document a U-shaped relationship between county groupings by poverty level and the intensity of coronavirus events defined as either coronavirus infections or COVID-19 related deaths. The U-shaped relationship prevails for counties with high population density while in counties with low population density, poorer counties exhibit much higher numbers in coronavirus cases, both in infections and deaths. Second, we investigate the patterns of coronavirus events following the announcements of state level stay-at-home mandates. We distinguish between four groups of states: First, Second, Third and Late Movers. Among First Moversâ€”also the states with the largest share of infectionsâ€”we observe a decrease in the average number of weekly new cases in rich and poor counties two weeks following the mandate announcement. The average numbers of cases per week in richer counties then quickly converges to the number reported in middle income counties, while the poorer counties show a much slower decrease in coronavirus cases. This pattern is accompanied by a dramatic reduction in mobility in all county groupings. Third, comparing counties in Second and Third Mover states, we show that a few days of delay in non-pharmaceutical interventions (NPIs) results in significantly larger numbers of coronavirus cases compared to states that introduce a mandate quicker. Finally, we use weather shocks as instruments to address endogeneity of the announce
Jung, J, J Manley and V Shrestha (2020), ‘Coronavirus Infections and Deaths by Poverty Status:Time Trends and Patterns‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_390524
We study planned price changes in German firm-level survey data to infer the relative importance of supply and demand during the Covid-19 pandemic. Supply and demand forces coexist, but demand deficiencies dominate in the short run. Quarter-on-quarter producer price inflation is predicted to decline by as much as 1.5 percentage points through August 2020. These results imply a role for demand stimulus policy to buffer the Covid-19 economic crisis.
Balleer, A, S Link, M Menkhoff and P Zorn (2020), ‘Demand or Supply? Price Adjustment during the Covid-19 Pandemic‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_391043
We measure the effect of lockdown policies on employment and GDP across countries using individual- and sector-level data. Employment effects depend on the ability to work from home, which ranges from about half of total employment in rich countries to around 35% in poor countries. This gap reflects differences in occupational composition, self-employment levels, and individual characteristics across countries. GDP effects of lockdown policies also depend on countries' sectoral structure. Losses in poor countries are attenuated by their higher value-added share in essential sectors, notably agriculture. Overall, a realistic lockdown policy implies GDP losses of 20-25% on an annualized basis.
Gottlieb, C, J Grobovsek, M Poschke and F Saltiel (2020), ‘Lockdown accounting‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_391044
We document the magnitudes of and mechanisms behind socioeconomic differences in travel behavior during the COVID-19 pandemic. We focus on King County, Washington, one of the first places in the U.S. where COVID-19 was detected. We leverage novel and rich administrative and survey data on travel volumes, modes, and preferences for different demographic groups. Large average declines in travel, and in public transit use in particular, due to the pandemic and related policy responses mask substantial heterogeneity across socioeconomic groups. Travel intensity declined considerably less among less-educated and lower-income individuals, even after accounting for mode substitution and variation across neighborhoods in the impacts of public transit service reductions. The relative inability of less-educated and lower-income individuals to cease commuting explains at least half of the difference in travel responses across groups.
Brough, R, M Freedman and D Phillips (2020), ‘Understanding Socioeconomic Disparities in Travel Behavior during the COVID-19 Pandemic‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_390525
In response to the surge of Covid-19 cases nations focused on reducing mobility to contain transmission of the virus. This change in mobility patterns can be achieved through two channels; (1) voluntary reductions in mobility due to rising public awareness and (2) explicit social distancing policies imposed by governments. In India, two weeks prior to the national lockdown imposed by the central government on 24th March, state governments had started independently enacting social distancing measures. However, there is little empirical evidence on the efficacy of the initial state-level restrictions, in comparison to the national lockdown. Even fewer studies have commented on the role of public awareness in reducing mobility. This paper contributes by comparing the impact of two policy events on mobility: the first Covid-19 social distancing policy imposed by each state and the imposition of the lockdown. We further explore how the news of the first reported case in a state impacted public awareness. The above effects were estimated by using an event study Difference-in-Differences model with time-varying treatment. Results show that while people did seek information in response to the perception that Covid-19 had â€˜reachedâ€™ their state, they did not reduce out-of-home mobility significantly. However, starting from the second day after the lockdown, time spent in residence increased significantly for each day by 3-4% for the next 21 days. This is in sharp contrast to the insignificant effect of statesâ€™ own first policy on mobility. The intervention of the central government had a much larger and persistent impact on mobility than the initial state-level policies, indicating that a unified, coordinated policy intervention is more effective than isolated, subnational efforts.
Kumar, H and M Nataraj (2020), ‘Mobility reductions in response to Covid-19 in India: Comparing voluntary, state and central responses‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_390526
How should unemployment benefits vary in response to the economic crisis induced by the COVID-19 pandemic? We answer this question by computing the optimal unem- ployment insurance response to the COVID-induced recession. We compare the optimal policy to the provisions under the CARES Act-which substantially expanded unemployment insurance and sparked an ongoing debate over further increases-and several alternative scenarios. We find that it is optimal first to raise unemployment benefits but then to begin lowering them as the economy starts to reopen - despite unemployment remaining high. We also find that the $600 UI supplement payment implemented under CARES was close to the optimal policy. Extending this UI supplement for another six months would hamper the recovery and reduce welfare. On the other hand, a UI extension combined with a re-employment bonus would further increase welfare compared to CARES alone, with only minimal effects on unemployment.
Mitman, K and S Rabinovich (2020), ‘Optimal Unemployment Benefits in the Pandemic‘, COVID Economics 31, CEPR Press, Paris & London. https://cepr.org/publications/covid-economics-issue-31#392514_392907_391045