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Recent research has shown that social media services create large consumer surplus. Despite their positive impact on economic welfare, concerns are raised about the negative association between social media usage and well-being or performance. However, causal empirical evidence is still scarce. To address this research gap, we conduct a randomized controlled trial among students in which we track participants’ daily digital activities over the course of three quarters of an academic year. In the experiment, we randomly allocate half of the sample to a treatment condition in which social media usage (Facebook, Instagram, and Snapchat) is restricted to a maximum of 10 minutes per day. We find that participants in the treatment group substitute social media for instant messaging and do not decrease their total time spent on digital devices. Contrary to findings from previous correlational studies, we do not find any significant impact of social media usage as it was defined in our study on well-being and academic success. Our results also suggest that antitrust authorities should consider instant messaging and social media services as direct competitors before approving acquisitions.

To prevent the spread of coronavirus disease 2019 (COVID-19), some types of public spaces have been shut down while others remain open. These decisions constitute a judgment about the relative danger and benefits of those locations. Using mobility data from a large sample of smartphones, nationally representative consumer preference surveys, and economic statistics, we measure the relative transmission reduction benefit and social cost of closing 26 categories of US locations. Our categories include types of shops, entertainments, and service providers. We rank categories by their trade-off of social benefits and transmission risk via dominance across 13 dimensions of risk and importance and through composite indexes. We find that, from February to March 2020, there were larger declines in visits to locations that our measures indicate should be closed first.

Despite the availability of multiple safe vaccines, vaccine hesitancy may present a challenge to successful control of the COVID-19 pandemic. As with many human behaviors, people’s vaccine acceptance may be affected by their beliefs about whether others will accept a vaccine (i.e., descriptive norms). However, information about these descriptive norms may have different effects depending on the actual descriptive norm, people’s baseline beliefs, and the relative importance of conformity, social learning, and free-riding. Here, using a pre-registered, randomized experiment ( N  = 484,239) embedded in an international survey (23 countries), we show that accurate information about descriptive norms can increase intentions to accept a vaccine for COVID-19. We find mixed evidence that information on descriptive norms impacts mask wearing intentions and no statistically significant evidence that it impacts intentions to physically distance. The effects on vaccination intentions are largely consistent across the 23 included countries, but are concentrated among people who were otherwise uncertain about accepting a vaccine. Providing normative information in vaccine communications partially corrects individuals’ underestimation of how many other people will accept a vaccine. These results suggest that presenting people with information about the widespread and growing acceptance of COVID-19 vaccines helps to increase vaccination intentions. The authors show that accurate information about descriptive norms can increase intentions to accept a vaccine for COVID-19. They show that these effects are largely consistent in the 23 included countries and are concentrated among people who were otherwise uncertain about accepting a vaccine.

Social distancing is the core policy response to coronavirus disease 2019 (COVID-19). But, as federal, state and local governments begin opening businesses and relaxing shelter-in-place orders worldwide, we lack quantitative evidence on how policies in one region affect mobility and social distancing in other regions and the consequences of uncoordinated regional policies adopted in the presence of such spillovers. To investigate this concern, we combined daily, county-level data on shelter-in-place policies with movement data from over 27 million mobile devices, social network connections among over 220 million Facebook users, daily temperature and precipitation data from 62,000 weather stations, and county-level census data on population demographics to estimate the geographic and social network spillovers created by regional policies across the United States. Our analysis shows that the contact patterns of people in a given region are significantly influenced by the policies and behaviors of people in other, sometimes distant, regions. When just one-third of a state’s social and geographic peer states adopt shelter-in-place policies, it creates a reduction in mobility equal to the state’s own policy decisions. These spillovers are mediated by peer travel and distancing behaviors in those states. A simple analytical model calibrated with our empirical estimates demonstrated that the “loss from anarchy” in uncoordinated state policies is increasing in the number of noncooperating states and the size of social and geographic spillovers. These results suggest a substantial cost of uncoordinated government responses to COVID-19 when people, ideas, and media move across borders.

Gross domestic product (GDP) and derived metrics such as productivity have been central to our understanding of economic progress and well-being. In principle, changes in consumer surplus provide a superior, and more direct, measure of changes in well-being, especially for digital goods. In practice, these alternatives have been difficult to quantify. We explore the potential of massive online choice experiments to measure consumer surplus. We illustrate this technique via several empirical examples which quantify the valuations of popular digital goods and categories. Our examples include incentive-compatible discrete-choice experiments where online and laboratory participants receive monetary compensation if and only if they forgo goods for predefined periods. For example, the median user needed a compensation of about $48 to forgo Facebook for 1 mo. Our overall analyses reveal that digital goods have created large gains in well-being that are not reflected in conventional measures of GDP and productivity. By periodically querying a large, representative sample of goods and services, including those which are not priced in existing markets, changes in consumer surplus and other new measures of well-being derived from these online choice experiments have the potential for providing cost-effective supplements to the existing national income and product accounts.

Benzell et al discuss the need to reduce the transmission risk of COVID-19 to boost business value. Starting business meetings with a handshake, laughing with friends in a bustling restaurant, or squeezing onto a crowded commuter train: Before the coronavirus pandemic, these were the completely unremarkable events of everyday life. But in the absence of an effective vaccine or test-and-trace system, these activities now carry deadly risks. Naturally, individuals, businesses, and governments have taken dramatic actions to reduce the number of social interactions to prevent the spread of COVID-19 and a deepening of the pandemic. Reducing social contact to slow the spread of the virus has had a major impact on the US economy, but not all businesses have been equally affected. Some companies provide better trade-offs. Those offering more social and economic importance per social interaction that poses potential risks face less government regulation and a smaller reduction in visits from fearful customers. Governments, businesses, and individuals should seek to maximize the bang for their buck from social interactions. And organizations that can boost their value-risk trade-offs are even in a position to benefit from the crisis.

During the COVID-19 pandemic, deaths per case in the United States decreased from 7.46% in April 2020 to 1.76% in April 2021. One mechanism that could explain this decline is a learning effect associated with testing of new treatments by hospitals. Hospitals that participated in clinical trials developed better organizational capabilities to diagnose and treat COVID-19 patients. Simultaneously, hospitals used health information technologies (IT) that integrated health information across healthcare providers to facilitate greater learning and sharing of best practices. Using US county-level data on clinical trial participation, use of health IT, and COVID-19 cases and deaths, we show that hospitals in counties that participated in clinical trials, and those with greater IT capabilities, exhibited a lower rate of COVID-19 deaths. Consistent with the learning effect hypothesis, counties with greater hospital IT capabilities performed relatively better at treating COVID-19 patients several months into the pandemic. Counties with hospitals that participated in COVID-19 clinical trials also learned faster, with the learning effect of clinical trials being moderated by hospital health IT capability. We posit that clinical trials and use of health IT systems can help hospitals to achieve lower mortality rates in the long run by enhancing learning effects.

Policy and communication responses to COVID-19 can benefit from better understanding of people’s baseline and resulting beliefs, behaviours and norms. From July 2020 to March 2021, we fielded a global survey on these topics in 67 countries yielding over 2 million responses. This paper provides an overview of the motivation behind the survey design, details the sampling and weighting designed to make the results representative of populations of interest and presents some insights learned from the survey. Several studies have already used the survey data to analyse risk perception, attitudes towards mask wearing and other preventive behaviours, as well as trust in information sources across communities worldwide. This resource can open new areas of enquiry in public health, communication and economic policy by leveraging large-scale, rich survey datasets on beliefs, behaviours and norms during a global pandemic.This Resource describes the data from a survey on COVID-19 related behaviours, beliefs and norms. From July 2020 to March 2021, the authors fielded a global survey on people’s baseline beliefs, behaviours and norms related to COVID-19 in 67 countries, yielding over 2 million responses.