Video-chat Studies for Developmental Research

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We use a five-age epidemiological model, combined with 66-sector economic accounting, to address a variety of questions concerning the economic reopening. We calibrate/estimate the model using contact survey data and data on weekly historical individual actions and non-pharmaceutical interventions in the weeks ending March 8 – May 16, 2020. Going forward, we model a decision-maker (governor) as following reopening guidelines like those proposed by the White House and the CDC. The sectoral accounting, combined with information on personal proximity and ability to work from home by sector, make it possible to construct a GDP-to-Risk index of which sectors provide the greatest increment in GDP per marginal increase in R0. Through simulations, we find that: a strong economic reopening is possible; a “smart” reopening, preferencing some sectors over others, makes only modest improvements over a broad reopening; and all this hinges on retaining strong restrictions on non-work social contacts. If non-work contacts – going to bars, shopping without social distancing and masks, large group gatherings, etc. – return only half-way to the pre-COVID-19 baseline, the current decline in deaths reverses leading to a second wave of business closures.

Reopening Scenarios

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COVID-19 convalescent plasma (CCP) therapy is currently a leading treatment for COVID-19. At present, there is a shortage of CCP relative to demand. We develop and analyze a model of centralized CCP allocation that incorporates both donation and distribution. In order to increase CCP supply, we introduce a mechanism that utilizes two incentive schemes, respectively based on principles of “paying it backward” and “paying it forward.” Under the first scheme, CCP donors obtain treatment vouchers that can be transferred to patients of their choosing. Under the latter scheme, patients obtain priority for CCP therapy in exchange for a future pledge to donate CCP if possible. We show that in steady-state, both principles generally increase overall treatment rates for all patients—not just those who are voucher-prioritized or pledged to donate. Our results also hold under certain conditions if a fraction of CCP is reserved for patients who participate in clinical trials. Finally, we examine the implications of pooling blood types on the efficiency and equity of CCP distribution.

Paying It Backward and Forward: Expanding Access to Convalescent Plasma Therapy Through Market Design

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The COVID pandemic found policymakers facing constraints on their ability to react to an exceptionally large negative shock. The current low interest rate environment limits the tools the central bank can use to stabilize the economy, while the large public debt curtails the efficacy of fiscal interventions by inducing expectations of costly fiscal adjustments. Against this background, we study the implications of a coordinated fiscal and monetary strategy aiming at creating a controlled rise of inflation to wear away a targeted fraction of debt. Under this coordinated strategy, the fiscal authority introduces an emergency budget with no provisions on how it will be balanced, while the monetary authority tolerates a temporary increase in inflation to accommodate the emergency budget. In our model the coordinated strategy enhances the efficacy of the fiscal stimulus planned in response to the COVID pandemic and allows the Federal Reserve to correct a prolonged period of below-target inflation. The strategy results in only moderate levels of inflation by separating long-run fiscal sustainability from a short-run policy intervention.

Monetary and Fiscal Policies in Times of Large Debt: Unity is Strength

10.3386/w27102

We study targeted lockdowns in a multi-group SIR model where infection, hospitalization and fatality rates vary between groups—in particular between the “young”, “the middle-aged” and the “old”. Our model enables a tractable quantitative analysis of optimal policy. For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group. Intuitively, a strict and long lockdown for the most vulnerable group both reduces infections and enables less strict lockdowns for the lower-risk groups. We also study the impacts of group distancing, testing and contract tracing, the matching technology and the expected arrival time of a vaccine on optimal policies. Overall, targeted policies that are combined with measures that reduce interactions between groups and increase testing and isolation of the infected can minimize both economic losses and deaths in our model.

Optimal Targeted Lockdowns in a Multi-Group SIR Model

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We propose an index of the adequacy of home environments for protection (HEP) from COVID-19, and we compare our index across developing countries using data for one million sampled households from the latest Demographic and Health Surveys. We find that prevailing WHO recommendations for protection posit unrealistic home environments. 90% of households have inadequate HEP by one or more dimensions considered. 40% do not have a formal health-care facility within 5km. A strong wealth effect is indicated within and between countries. Only 6% of the poorest 40% have an adequate HEP, and the proportion is virtually zero in sub-Saharan Africa.

Can the World's Poor Protect Themselves from the New Coronavirus?

MyData vs. COVID-19 calls

In response to the COVID-19 crisis, the MyData community is hosting weekly & bi-weekly calls to showcase the latest human-centric solutions, apps & initiatives.

Jane Greatorex is Senior Tutor, Undergraduate and Graduate Tutor and Director of Studies in Pre-Clinical Medical and Veterinary Sciences at Lucy Cavendish College. She has had a long career in academic and clinical science, specializing in the blood borne viruses and, until September 2017, was responsible for streamlining and improving HIV diagnostic services at Addenbrookes Hospital, Cambridge. As a scientist used to working in high containment laboratories, she was a team leader in Sierra Leone during the Ebola outbreak in 2015 and remains on the list of scientists that may be called upon to respond in the event of a similar occurrence. She remains involved in a number of research projects, specifically exploring the use of next generation sequencing for the identification of resistance mutations in HIV and human herpes viruses. Jane also maintains an active research interest in the Influenza virus, most recently working on the shedding and survival of H1N1v (“swine ‘flu”).

#LucyinLockdown: Viruses, Pandemics and Lessons Learnt with Dr Jane Greatorex

How will COVID-19 shape the future of our cities? What are the most important priorities for our cities as a result of this pandemic? Join experts Richard Florida, Nathalie Des Rosiers, Anita McGahan and Shauna Brail as they discuss cities after COVID with Marcia Young, host of CBC’s World Report.

Cities After Covid

Sparked by the killing of George Floyd in police custody, the 2020 Black Lives Matter protests have brought a new wave of attention to the issue of in­equal­ity within criminal justice. However, many public health officials have warned that mass protests could lead to a reduction in social dis­tanc­ing behavior, spurring a resur­gence of COVID-19. This study uses newly collected data on protests in 315 of the largest U.S. cities to estimate the impacts of mass protests on social dis­tanc­ing and COVID-19 case growth. Event-​study analyses provide strong evidence that net stay-​at-home behavior increased following protest onset, con­sis­tent with the hy­poth­e­sis that non-​protesters’ behavior was sub­stan­tially affected by urban protests. This effect was not fully explained by the im­po­si­tion of city curfews. Estimated effects were generally larger for per­sis­tent protests and those ac­com­pa­nied by media reports of violence. Fur­ther­more, we find no evidence that urban protests reignited COVID-19 case growth during the more than three weeks following protest onset. We conclude that pre­dic­tions of broad negative public health con­se­quences of Black Lives Matter protests were far too narrowly conceived.

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Black Lives Matter Protests, Social Dis­tanc­ing, and COVID-19

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On June 20, 2020, President Donald J. Trump held his first mass campaign rally following the outbreak of COVID-19. Held in Tulsa, Oklahoma, the political gathering attracted 6,000 to 12,000 individuals to the indoor Bank of Oklahoma (BOK) arena. This study is the first to explore the impact of this event on the spread of COVID-19. First, using data from Safegraph Inc, we show that while non-resident visits to census block groups hosting the Trump event grew by approximately 25 percent, there was no decline in net stay-at-home behavior in Tulsa county, reflecting important offsetting behavioral effects. Then, using data on coronavirus cases from the Centers for Disease Control and Prevention (CDC) and a synthetic control design, we find little evidence that COVID-19 case growth grew more rapidly in Tulsa County, its border counties, or in the state of Oklahoma than each’s estimated counterfactual in the three weeks following the campaign rally. Difference-in-differences estimates further provide no evidence that COVID-19 case rates grew faster in counties that drew relatively larger shares of residents to the event. We conclude that offsetting behavioral responses to the rally — including voluntary closures of restaurants and bars in downtown Tulsa, increases in stay-at-home behavior, displacement of usual activities of weekend inflows, and smaller-than-expected crowd attendance — may be important mechanisms.

Did President Trump's Tulsa Rally Reignite COVID-19? Indoor Events and Offsetting Community Effects

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On March 19, 2020, California Governor Gavin Newsom issued Executive Order N-33-20 2020, which required all residents of the state of California to shelter in place for all but essential activities such as grocery shopping, retrieving prescriptions from a pharmacy, or caring for relatives. This shelter-in-place order (SIPO), the first such statewide order issued in the United States, was designed to reduce COVID-19 cases and mortality. While the White House Task Force on the Coronavirus has credited the State of California for taking early action to prevent a statewide COVID-19 outbreak, no study has examined its impact. This study is the first to estimate the effect of SIPO adoption on health. Using daily state-level coronavirus data and a synthetic control research design, we find that California’s statewide SIPO reduced COVID-19 cases by 125.5 to 219.7 per 100,000 population by April 20, one month following the order. We further find that California’s SIPO led to as many as 1,661 fewer COVID-19 deaths during this period. Back-of-the-envelope calculations suggest that there were about 400 job losses per life saved during this short-run post-treatment period.

Did California's Shelter-in-Place Order Work? Early Coronavirus-Related Public Health Effects

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On April 7, 2020, Wisconsin held a major election for state positions and presidential preferences for both major parties. News reports showed pictures of long lines of voters due to fewer polling locations and suggested that the election may further the spread of the SARS-CoV-2 virus. A contact-tracing analysis by the Wisconsin Department of Health Services identified 71 confirmed cases of COVID-19 to in-person voting, but no research has conducted a broader analysis of the extent to which in-person voting increased the number of COVID-19 cases. We use county level data on voting and COVID-19 tests to connect the election to the spread of the SARS-CoV-2 virus. We find a statistically and economically significant association between in-person voting and the spread of COVID-19 two to three weeks after the election. Results indicate that on average a 10% difference in in-person voters per polling location between counties is associated with approximately a 17.7% increase in the positive test rate. Further, extrapolation of estimates from the average county suggests that in-person voting was related to approximately 700 more COVID-19 cases in Wisconsin during the weeks following the election, or about 7.7% of the total number of confirmed cases during the five week post-treatment time period studied.

The Relationship between In-Person Voting and COVID-19: Evidence from the Wisconsin Primary

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In order to understand the impact of the COVID-19 pandemic on higher education, we surveyed approximately 1,500 students at one of the largest public institutions in the United States using an instrument designed to recover the causal impact of the pandemic on students' current and expected outcomes. Results show large negative effects across many dimensions. Due to COVID-19: 13% of students have delayed graduation, 40% lost a job, internship, or a job offer, and 29% expect to earn less at age 35. Moreover, these effects have been highly heterogeneous. One quarter of students increased their study time by more than 4 hours per week due to COVID-19, while another quarter decreased their study time by more than 5 hours per week. This heterogeneity often followed existing socioeconomic divides; lower-income students are 55% more likely to have delayed graduation due to COVID-19 than their higher-income peers. Finally, we show that the economic and health related shocks induced by COVID-19 vary systematically by socioeconomic factors and constitute key mediators in explaining the large (and heterogeneous) effects of the pandemic.

The Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey

10.3386/w27427

We investigate how the coronavirus pandemic affected the demand for online food shopping services using data from the largest agri-food e-commerce platform in Taiwan. We find that an additional confirmed case of COVID-19 increased sales by 5.7% and the number of customers by 4.9%. The demand for grains, fresh fruit and vegetables, and frozen foods increased the most, which benefited small farms over agribusinesses. Online food shopping was highly responsive to COVID-19 media coverage and online content. Because Taiwan did not impose a stay-at-home order, the demand for online food shopping may be similar in other countries after they lift mobility restrictions.

COVID-19 and the Demand for Online Food Shopping Services: Empirical Evidence from Taiwan

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This case study compares the importance of prevailing market factors against that of COVID-19 dynamics and policy responses in explaining the evolution of Eurozone (EZ) sovereign spreads during the first half of 2020. Focusing on daily Eurozone CDS spreads, we adopt a multi-stage econometric approach. First, we estimate a multi-factor model for changes in EZ CDS spreads over the pre-COVID-19 period of January 2014 through June 2019. Then, we apply a synthetic control-type procedure to extrapolate model-implied changes in the CDS from July 2019 through June 2020. We find that the factor model does very well in tracing the realized sovereign spreads over the rest of 2019, but breaks down during the pandemic – diverging substantially in March 2020. In the second stage, focusing specifically on the 2020 period, we find that the March 2020 divergence is well accounted for by COVID-specific risks and associated policies. In particular, mortality outcomes and policy announcements, rather than traditional determinants like fiscal space and systematic risk, drove CDS adjustment over this period. Daily CDS spread widening ceased almost immediately after the ECB announced the PEPP, but the divergence between actual and model-implied changes persisted. This divergence can be traced back to the fact that fiscally secure EZ Core countries saw spreads widen further than implied – comparable to the widening of more fragile countries - as several of the Core countries were hit hard by COVID-19. Taken all together, this points to COVID-19 Dominance: The widening spreads during the pandemic induced by COVID-specific risks and fiscal responses has led to unconventional monetary policies that primarily aim to mitigate the short-run fear of the worst economic outcomes, temporarily pushing away concerns over fiscal risk.

Pandemic Shocks and Fiscal-Monetary Policies in the Eurozone: COVID-19 Dominance During January - June 2020

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The relationship between population health and measures of economic well-being and economic activity is a long standing topic in health economics (Preston, 1975; Cutler, Deaton, and Lleras-Muney, 2006; Ruhm, 2000). The conceptual issues in analyzing the complicated link between health and economic well-being are central to understanding the implications of the COVID-19 epidemic in the United States The public health shock of the epidemic has direct economic impacts, but the mitigation policies governments are using to control the spread of the virus may also damage economic activity. We estimate how state job market conditions respond to state COVID-19 infections and school closures, which are the earliest of the major mitigation policies. Mitigation policies and local epidemiological conditions explain some of the variation in unemployment patterns. However, the historically unprecedented increase in new UI claims during the weeks of March 15-21 and March 22-28 was largely across-the-board and occurred in all states. This suggests most of the economic disruption was driven by the health shock itself. Put differently, it appears that the labor market slowdown was due primarily to a nationwide response to evolving epidemiological conditions and that individual state policies and own epidemiologic situations have had a comparatively modest effect.

Is the Cure Worse than the Problem Itself? Immediate Labor Market Effects of COVID-19 Case Rates and School Closures in the U.S.

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Shelter in place orders (SIPOs) require residents to remain home for all but essential activities such as purchasing food or medicine, caring for others, exercise, or traveling for employment deemed essential. Between March 19 and April 20, 2020, 40 states and the District of Columbia adopted SIPOs. This study explores the impact of SIPOs on health, with particular attention to heterogeneity in their impacts. First, using daily state-level social distancing data from SafeGraph and a difference-in-differences approach, we document that adoption of a SIPO was associated with a 5 to 10 percent increase in the rate at which state residents remained in their homes full-time. Then, using daily state-level coronavirus case data collected by the Centers for Disease Control and Prevention, we find that approximately three weeks following the adoption of a SIPO, cumulative COVID-19 cases fell by 44 percent. Event-study analyses confirm common COVID-19 case trends in the week prior to SIPO adoption and show that SIPO-induced case reductions grew larger over time. However, this average effect masks important heterogeneity across states — early adopters and high population density states appear to reap larger benefits from their SIPOs. Finally, we find that statewide SIPOs were associated with a reduction in coronavirus-related deaths, but estimated mortality effects were imprecisely estimated.

When Do Shelter-in-Place Orders Fight COVID-19 Best? Policy Heterogeneity Across States and Adoption Time

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We analyze the supply-side disruptions associated with Covid-19 across firms and workers. To do so, we exploit differences in the ability of workers across industries to work remotely using data from the American Time Use Survey (ATUS). We find that sectors in which a higher fraction of the workforce is not able to work remotely experienced significantly greater declines in employment, significantly more reductions in expected revenue growth, worse stock market performance, and higher expected likelihood of default. In terms of individual employment outcomes, lower-paid workers, especially female workers with young children, were significantly more affected by these disruptions. Last, we combine these ex-ante heterogeneous industry exposures with daily financial market data to create a stock return portfolio that most closely replicate the supply-side disruptions resulting from the pandemic.

Working Remotely and the Supply-side Impact of Covid-19

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Motivated by reports in the media suggesting unequal access to Covid-19 testing across incomes, we analyze zip-code level data on the number of Covid-19 tests, test results, and income per capita in New York City. We find that the number of tests administered is evenly distributed across income levels. In particular, the test distribution across income levels is significantly more egalitarian than the distribution of income itself: The ten percent of the city's population living in the richest zip codes received 11 percent of the Covid-19 tests and 29 percent of the city's income. The ten percent of the city's population living in the poorest zip codes received 10 percent of the tests but only 4 percent of the city's income. At the same time, we find significant disparity in the fraction of tests that come back negative for the Covid-19 disease across income levels: moving from the poorest zip codes to the richest zip codes is associated with an increase in the fraction of negative Covid-19 test results from 38 to 65 percent.

Covid-19: Testing Inequality in New York City

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The Covid-19 Pandemic has led to changes in consumer expenditure patterns that can introduce significant bias in the measurement of inflation. I use data collected from credit and debit transactions in the US to update the official basket weights and estimate the impact on the Consumer Price Index (CPI). I find that the Covid inflation rate is higher than the official CPI in the US, for both headline and core indices. I also find similar results with Covid baskets in 10 out of 16 additional countries. The difference is significant and growing over time, as social-distancing rules and behaviors are making consumers spend relatively more on food and other categories with rising inflation, and relatively less on transportation and other categories experiencing significant deflation.

Inflation with Covid Consumption Baskets

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What will be political legacy of the Coronavirus pandemic? We find that epidemic exposure in an individual’s “impressionable years” (ages 18 to 25) has a persistent negative effect on confidence in political institutions and leaders. We find similar negative effects on confidence in public health systems, suggesting that the loss of confidence in political leadership and institutions is associated with healthcare-related policies at the time of the epidemic. In line with this argument, our results are mostly driven by individuals who experienced epidemics under weak governments with less capacity to act against the epidemic, disappointing their citizens. We provide evidence of this mechanism by showing that weak governments took longer to introduce policy interventions in response to the COVID-19 outbreak. These results imply that the Coronavirus may leave behind a long-lasting political scar on the current young generation (“Generation Z”).

The Political Scar of Epidemics

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We provide a model of endogenous asset price spirals and severe aggregate demand contractions following a large real (non-financial) shock. The key mechanism stems from the drop in the wealth share of the economy's risk-tolerant agents: as a recessionary shock hits the economy, their wealth declines and their leverage rises endogenously, causing them to o­ oad some risky assets. When monetary policy is unconstrained, it can offset the decline in risk tolerance with an interest rate cut that boosts the market's Sharpe ratio. However, if the interest rate policy is constrained, new contractionary feedbacks arise: recessionary shocks not only lead to reduced risk tolerance but also to further asset price and output drops, which feed the risk-off episode and trigger a downward loop. When pre-shock leverage ratios are high, multiple equilibria are possible, including one where risk-tolerant agents go bankrupt. A large-scale asset purchases (LSAPs) policy can be highly effective in this environment, as it reverses the downward asset price spiral. In an extension, we show how corporate debt overhang problems exacerbate our mechanism. The Covid-19 shock and the large response by all the major central banks provide a vivid illustration of the environment we seek to capture.

A Model of Asset Price Spirals and Aggregate Demand Amplification of a "Covid-19" Shock

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This note develops a framework for thinking about the following question: What is the maximum amount of consumption that a utilitarian welfare function would be willing to trade off to avoid the deaths associated with the pandemic? The answer depends crucially on the mortality rate associated with the coronavirus. If the mortality rate averages 0.81%, taken from the Imperial College London study, our answer is 41% of one year's consumption. If the mortality rate instead averages 0.44% across age groups, our answer is 28%.

Trading Off Consumption and COVID-19 Deaths

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We study disruptions in debt markets during the COVID-19 crisis. The safer end of the credit spectrum experienced significant losses that are hard to fully reconcile with standard default or risk premium channels. Corporate bonds traded at a large discount to their corresponding CDS, and this basis widened most for safer bonds. Liquid bond ETFs traded at a large discount to their NAV, more so for Treasuries, municipal bonds, and investment-grade corporate than high-yield corporate. These facts suggest investors tried to sell safer, more liquid securities to raise cash. These disruptions disappeared nearly as fast as they appeared. We trace this recovery back to the unprecedented actions the Fed took to purchase corporate bonds rather than its interventions in extending credit. The March 23rd announcement to buy investment-grade debt boosted prices and lowered bond spreads (particularly at shorter maturities and the safer end of investment-grade) while having virtually no effect on high-yield debt. April 9th, in contrast, had a large effect on both investment-grade and high-yield, even for the riskier end of high yield which would only indirectly benefit from the policy. These facts highlight the importance of financial frictions early on in the crisis, but also challenge existing theories of these frictions.

When Selling Becomes Viral: Disruptions in Debt Markets in the COVID-19 Crisis and the Fed's Response

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We correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states and counties. We also find that a higher share of people not working, and thus not commuting either because they are elderly, children or unemployed, is correlated with higher death rates. Counties with higher home values, higher summer temperatures, and lower winter temperatures have higher death rates. Contrary to past work, we do not find a correlation between pollution and death rates. Also importantly, we do not find that death rates are correlated with obesity rates, ICU beds per capita, or poverty rates. Finally, our model that looks within states yields estimates of how a given state's death rate compares to other states after controlling for the variables included in our model; this may be interpreted as a measure of how states are doing relative to others. We find that death rates in the Northeast are substantially higher compared to other states, even when we control for the four sets of variables above. Death rates are also statistically significantly higher in Michigan, Louisiana, Iowa, Indiana, and Colorado. California's death rate is the lowest across all states.

What Does and Does Not Correlate with COVID-19 Death Rates

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Emerging economies are characterized by an extremely high prevalence of informality, small-firm employment and jobs not fit for working from home. These features factor into how the COVID-19 crisis has affected the economy. We develop a framework that, based on accounting identities and actual data, quantifies potential job and income losses during the crisis and recovery for economies with different economic organization structures. Our analysis incorporates differential exposure of jobs across categories of firm-size and formality status, as well as sectors and occupations. We account for the direct supply shock caused by lockdowns, the idiosyncratic demand shock suffered by sectors that rely on high contact with their costumers, the transmission of both shocks through IO linkages, and the overall aggregate demand effect derived from these shocks. Applying our framework to data for Colombia, which exhibits an employment distribution similar to that of other emerging market countries, in particular Latin America, we find that well over 50% of jobs are at risk in the initial stages of the crisis. Because informal jobs and those not fit for telework are at higher risk, this number goes down to 33% if the US employment distribution is imposed on the Colombian data. As the crisis deepens, the risk of unemployment grows. However, informality rebounds quickly in the recovery, an employment at risk is quickly reduced to 20% of the baseline, all concentrated in formal jobs. Our findings point to the importance of action to maintain formal matches from dissolving, given their scarcity and rebuilding difficulty, while protecting the poor and the informal via income transfers

EMEs and COVID-19: Shutting Down in a World of Informal and Tiny Firms

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We study the effects of negative supply shocks and shocks to the composition of final demand on aggregate output in a disaggregated neoclassical model with multiple sectors, factors, and input-output linkages. We show how nonlinearities associated with complementarities in consumption and production amplify the effect of negative supply shocks by creating supply bottlenecks and disrupting supply chain networks. These nonlinearities are particularly potent when the shocks are more heterogeneous as the worst-affected sectors drag down the other sectors. Nonlinearities are strengthened when changes in preferences lead households to tilt the composition of their demand towards the crippled sectors directly and indirectly through their supply chains. And nonlinearities are further intensified when factors cannot easily be reallocated across sectors to reinforce weak links. A quantitative investigation suggests that nonlinearities may amplify the impact of the Covid-19 shock by between 10\%-100\%, depending on the horizon of analysis and the exact size of the shocks.

Nonlinear Production Networks with an Application to the Covid-19 Crisis

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This paper examines the impact of the social distancing policies states adopted between March and April of 2020 in response to the COVID-19 epidemic. These actions, together with voluntary social distancing, appear to have reduced the rate of new COVID-19 cases and deaths, but raised concerns about the costs experienced by workers and businesses. Estimates from difference-in-difference models that leverage cross-state variation in the timing of business closures and stay-at-home mandates suggest that the employment rate fell by about 1.7 percentage points for every extra 10 days that a state experienced a stay-at-home mandate during the period March 12-April 12, 2020; select business closure laws were associated with similar employment effects.

Effects of Social Distancing Policy on Labor Market Outcomes

"95% of all decision making is unconscious." It's such a common refrain, but is it true? What does it even mean for a decision to be unconscious? What about an unconscious influence? Professor David Shanks sheds light on these topics and discusses money priming, whether sex really sells, and why grocery stores put the bakery by the entrance.

Unconscious influences on behaviour: Fact or fiction?

Marcus Rashford has called on the government to reverse a decision not to provide free school meal vouchers during the summer, saying that "the system isn't built for families like mine to succeed".

Marcus Rashford calls for government free school meals U-turn

First up this week, Staff Writer Meredith Wadman talks with host Sarah Crespi about how male sex hormones may play a role in higher levels of severe coronavirus infections in men. New support for this idea comes from a study showing high levels of male pattern baldness in hospitalized COVID-19 patients. Read all our coronavirus coverage. Next, Jason Qian, a Ph.D. student in the systems biology department at Harvard Medical School, joins Sarah to talk about an object-tracking system that uses bacterial spores engineered with unique DNA barcodes. The inactivated spores can be sprayed on anything from lettuce, to wood, to sand and later be scraped off and read out using a CRISPR-based detection system. Spraying these DNA-based identifiers on such things as vegetables could help trace foodborne illnesses back to their source. Read a related commentary piece. 

Why men may have more severe COVID-19 symptoms, and using bacteria to track contaminated food

Journalism in Crisis

The impact of COVID-19 on the American Media How do we as citizens and news consumers navigate the complexities of our current media landscape? And what has the coronavirus meant for journalists, media companies and where we get our news and information from? Our expert panel will make sense of the present, and look ahead to the future.

10.1140/epjds/s13688-020-00235-w

The United Nations Sustainable Development Goals (SDGs) are a global consensus on the world’s most pressing challenges. They come with a set of 232 indicators against which countries should regularly monitor their progress, ensuring that everyone is represented in up-to-date data that can be used to make decisions to improve people’s lives. However, existing data sources to measure progress on the SDGs are often outdated or lacking appropriate disaggregation. We evaluate the value that anonymous, publicly accessible advertising data from Facebook can provide in mapping socio-economic development in two low and middle income countries, the Philippines and India. Concretely, we show that audience estimates of how many Facebook users in a given location use particular device types, such as Android vs. iOS devices, or particular connection types, such as 2G vs. 4G, provide strong signals for modeling regional variation in the Wealth Index (WI), derived from the Demographic and Health Survey (DHS). We further show that, surprisingly, the predictive power of these digital connectivity features is roughly equal at both the high and low ends of the WI spectrum. Finally we show how such data can be used to create gender-disaggregated predictions, but that these predictions only appear plausible in contexts with gender equal Facebook usage, such as the Philippines, but not in contexts with large gender Facebook gaps, such as India.

Mapping socioeconomic indicators using social media advertising data

The best way for the EU to spend its €750bn fund

After an epic EU summit, the €750bn facility to aid members worst hit by the pandemic is almost in hand, lacking only formal ratification. Its fraught negotiations centred on issues such as the split between loans and grants, approval procedures, and the rule of law. Lost in the fray, though, was a basic question: what kind of spending specifically promotes long-term recovery best?

Research shows entrenched partisanship between Leavers and Remainers in response to the British government’s efforts to control the pandemic

Op-Ed: How Brexit tribalism has influenced attitudes toward COVID-19 in Britain