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The Covid-19 pandemic has sparked hope that firm digitalisation will result in long-lasting reductions in mobility and related carbon emissions via the use of working from home and online services. In this study, we quantify the extent to which firm digitalisation can be associated with changes in mobility during the Covid-19 crisis in Germany, both when strong restrictions were in place and after the restrictions were lifted. To this end, we employ a novel text-mining approach to measure digitalisation based on firm websites. We aggregate our firm digitalisation indicator at the district level and link it to changes in mobility between January 2020 and December 2022. Our results indicate that districts with a higher level of firm digitalisation experienced a stronger reduction in mobility during the first two years of the pandemic. However, mobility almost came back to pre-crisis levels after most restrictions were lifted, suggesting that environmental improvements are not long-lasting.

We examine the deep roots of preferences for vaccination against COVID-19, moving beyond proximate factors which can only account for part of the observable heterogeneity in the willingness to get vaccinated. Our model on experience-based learning predicts that exposure to past disruptive crises increases individuals' willingness to acquire and take a promising remedy when new crises occur. Using micro-level data on vaccination preferences for individuals from 19 countries, we find strong evidence for our prediction. We investigate the role of competing vaccines exploiting original geocoded survey data from Russia. Consistent with our theory, past crisis experience decreases vaccination willingness when individuals have learned to distrust the effectiveness of government administered remedies.

Changes in people’s behavior during the COVID-19 pandemic can be regarded as the result of two types of effects: the “intervention effect” (changes resulting from government orders or requests for people to change their behavior) and the “information effect” (voluntary changes in people’s behavior based on information about the pandemic). Using mobile location data to construct a stay-at-home measure for different age groups, we examine how the intervention and information effects differ across age groups. Our main findings are as follows. First, the age profile of the intervention effect of the state of emergency declaration in April and May 2020 shows that the degree to which people refrained from going out was smaller for older age groups, who are at a higher risk of serious illness and death, than for younger age groups. Second, the age profile of the information effect shows that, unlike the intervention effect, the degree to which people stayed at home tended to increase with age for weekends and holidays. Thus, while Acemoglu et al. (2020) proposed targeted lockdowns requiring stricter lockdown policies for the oldest group in order to protect those at a high risk of serious illness and death, our findings suggest that Japan’s government intervention had a very different effect in that it primarily reduced outings by the young, and what led to the quarantining of older groups at higher risk instead was people’s voluntary response to information about the pandemic. Third, the information effect has been on a downward trend since the summer of 2020. While this trend applies to all age groups, it is relatively more pronounced among the young, so that the age profile of the information effect remains upward sloping, suggesting that people’s response to information about the pandemic is commensurate with their risk of serious illness and death.

In this article, we examine the expectations of the economic outlook, fear of the future, and behavioural change during the first Covid-19 wave, for three European countries (Spain, the United Kingdom, and Italy) that have been severely hit. We use a novel dataset that we collected to monitor the three countries during the crisis. As outcome variables, we used expectations (e.g., economic outlook, labour market situation, recovery), fear (e.g., scenario of new outburst, economic depression, restriction to individual rights and freedom), and behavioural change across the following dimensions: savings, cultural consumption, social capital, and risky behaviour. We provide descriptive evidence that is representative of the population of interest, and we estimate the impact of exposure to shock occurred during the crisis on the same outcome variables, using matching techniques. Our main findings are the following: we detected systematically negative expectations regarding the future and the recovery, majoritarian fears of an economic depression, a new outbreak, and a permanent restriction on freedom, a reduction in saving and in social capital. Exposure to shocks decreased expected job prospects, increased withdrawal from accumulated savings, and reduced contacts with the network relevant to job advancement, whereas it had inconclusive effects over fears. Supplementary Information The online version contains supplementary material available at 10.1007/s11205-021-02697-5.

This paper documents daily compound indicators on physical mobility and sales activity in Switzerland during the Corona crisis. We report several insights from these indicators: The Swiss population substantially reduced its activities already before the shops closed and before the authorities introduced containment policies in mid-March 2020. Activity started to gradually recover from the beginning of April onwards, again substantially before the first phase of the shutdown easing started at the end of April. Low physical mobility during the second half of March and during April likely contributed to the quick fall in new COVID-19 infections since mid-March. The sharp drop in economic activity in consumer-related services during March and April and the gradual recovery in these sectors since May correlate strongly with the reduction and subsequent gradual resurgence of mobility. In addition, while activity within Switzerland was back to normal levels by late June, activity of Swiss residents outside of Switzerland was still below normal., Swiss Journal of Economics and Statistics, 156, ISSN:0303-9692, ISSN:2235-6282

We investigate the relationship between political attitudes and prosociality in a survey of a representative sample of the U.S. population during the first summer of the COVID-19 pandemic. We find that an experimental measure of prosociality correlates positively with adherence to protective behaviors. Liberal political ideology predicts higher levels of protective behavior than conservative ideology, independently of the differences in prosociality across the two groups. Differences between liberals and conservatives are up to 4.4 times smaller in their behaviorthan in judging the government’s crisis management. This result suggests that U.S. Americans are more polarized on ideological than behavioral grounds.

This paper presents the results of a survey exploring the determinants of vacinees' confidence in COVID-19 vaccines and their motivations to become vaccinated. At the threatening rise of the highly infectious Omicron variant, in December 2021, we interviewed people in waiting lines of vaccination centers. Our results identify risk-averse and social-distancing-compliant people as showing high confidence in the vaccine, which motivates them to receive it for reasons of protecting themselves and others. By contrast, policy incentives, such as "3G/2G" restrictions, motivate risktolerant people who opted for vaccination to get access to public areas. Trusting people who regularly vote are little afraid of vaccines' side effects. Our findings offer insights for policymakers in societies and firms that help to tailor policies promoting vaccination based on people's economic preferences

We study the influence of social messages that promote a digital public good, a COVID-19 tracing app. We vary whether subjects receive a digital message from another subject, and, if so, at what cost it came. Observed maximum willingness to invest in sending varies, from 1 cent up to 20 euros. Does this affect receivers' sending behavior? Willingness to invest in sending increases when previously receiving the message. Yet, cost signals have no impact. Thus, grassroots movements can be started at virtually no cost. App-support matters normatively as non-supporters are supposed to be punished in triage.

While the world faces unprecedented COVID-19 case numbers, vaccination rates in many countries are stagnating. A differentiated understanding of the concerns of the unvaccinated population seems urgently needed to design successful communication strategies. We conducted an original survey experiment among 2,100 unvaccinated respondents from Germany where a substantial population share remains unvaccinated. Guided by the elaboration likelihood model, this paper has two objectives: First, it explores by means of a latent class analysis how unvaccinated individuals might be characterised by their attitudes towards COVID-19 vaccination. The results suggest three different subgroups: Vaccination opponents, sceptics and those receptive to be vaccinated. Second, we investigate to what extent (i) communicators (scientists/politicians) can employ (ii) varying types of evidence (none/anecdotal/statistical) to improve vaccination intentions across these subgroups. While vaccination opponents seem largely unreachable, sceptics value information by scientists, particularly if supported by anecdotal evidence. Receptives seem to instead value statistical evidence from politicians.

Access to information via social media is one of the biggest differentiators of public health crises today. During the early stages of the Covid-19 outbreak in January 2020, we conducted an experiment in Wuhan, China to assess the impact of viral social media content on pro-social and trust behaviours and preferences towards risk taking with known and unknown probabilities. Prior to the experiment, participants viewed one of two videos that had been widely and anonymously shared on Chinese social media: a central government leader visiting a local hospital and supermarket, or health care volunteers transiting to Wuhan. In a control condition, participants watched a Neutral video, unrelated to the crisis. Viewing one of the leadership or volunteer videos leads to higher levels of pro-sociality and lesser willingness to take risks in an ambiguous situation relative to the control condition. The leadership video, however, induces lower levels of trust. We provide evidence from two post-experiment surveys that the video’s impact on pro-sociality is modulated by influencing the viewer’s affective emotional state. Supplementary Information The online version contains supplementary material available at 10.1007/s40881-021-00104-w.

International audience; Countries have adopted several measures to control the spread of Covid-19. However, substantial differences remain in terms of performance in controlling the virus, potentially due to heterogeneity in citizen engagement with government measures. Although the literature documents the effects of trust in government on compliance with health restrictions related to the health crisis, little is said about the direct effect of trust in government on managing the Covid-19 crisis, defined as the number of cases and deaths. Drawing on this observation, this paper seeks to analyze the effect of pre-crisis ties, particularly trust in government, on crisis management, proxied by the number of Covid-19 cases and deaths per million population. We examine this question based on a sample of 41 countries for which data are available and using the Ordinary Least Squares (OLS) method. Results reveal that a high level of trust in government predicts better crisis management in terms of relatively low levels of cases and deaths. These results, which successfully pass a series of robustness tests, may vary according to level of contamination and increase with time. This paper, therefore, suggests that building trust between the public and the authorities, essentially governments and citizens, is essential for crisis management, taking the example of the Covid-19 pandemic.

Strict containment limits the spread of pandemics but is difficult to achieve when people must continue to work to avoid poverty. A new role is emerging for income support: by enabling people to effectively stay home, it can produce substantial health externalities. We examine this issue using data on human mobility and poverty rates in 729 subnational regions of Africa, Latin America and Asia during the first year of COVID-19. We focus on within-country differential mobility changes between higher- and lower-poverty regions. Conditional on country-day fixed effects, shelter-in-place orders decrease work-related mobility significantly less in poorer regions. Emergency income support programs seem to help people to reduce their mobility on average, mitigating the poverty-driven gap in mobility between regions and, hence, regional differences in contagion rates.

This paper uses the COVID-19 pandemic as a case study to investigate the direct and indirect effect of beliefs of others on respondent's own beliefs and on their individual consumer sentiment. In a new online consumer survey with randomized control trials (RCTs) in Thailand and Vietnam, we present randomized subgroups of respondents in both countries with information treatments showing cross-country measures of average beliefs from other surveys. The two countries are interesting cases since Thailand ranks lowest in the cross-country survey on approval rates for the government's reaction to the pandemic, while Vietnam has the highest approval rates. This is our ftrst information treatment, which is on average viewed as good news in Vietnam and as bad news in Thailand. In the second treatment, we show evidence of cross-country average appropriateness ratings of the general public's reaction to the pandemic. This treatment is more symmetric across countries, since both approval rates are relatively similar and lie in the middle of the distribution, rather than in the tails. On average, respondents in our survey view this treatment as neutral. Our results suggest that the information treatments only weakly affect consumer sentiment. We only ftnd signiftcant treatment effects in Vietnam, which suggest that both treatments are viewed as positive news in comparison to the control group. However, consumer sentiment in Vietnam is strongly affected by both treatments when they go against respondents' previously held beliefs.

We propose that crisis experience influences preferences towards COVID-19 vaccination and the speed of vaccination during the initial phase when vaccines became available. We use macro and micro data to empirically investigate our theory and introduce a novel crisis experience index. Evidence based on macro data shows that a one-standard-deviation increase in our new crisis experience index gives rise to around 10 additional administered vaccine doses per 100 citizens (around one standard deviation). Our micro-level analysis provides evidence for a microfoundation of the macro-level results, indicating that the crisis history of countries is positively correlated with preferences towards COVID-19 vaccination. Disentangling socialization effects and experience effects, we find that citizens who have experienced crises during their impressionable years (ages 18–25) have stronger preferences for being vaccinated against COVID-19 than others.

Over the first half of March 2021, the majority of European governments suspended Astrazeneca's Vaxzevria vaccine as a precaution following media reports of rare blood clots. We analyse the impact of the European Medicines Agency's (EMA) March 18th statement assuring the public of the safety of Vaxzevria and the immediate reinstatement of the vaccine by most countries on respondents' intention to get vaccinated. By relying on survey data collected in Luxembourg and neighbouring areas between early March and mid-April, we observe that the willingness to be vaccinated was severely declining in the days preceding the EMA statement. We implement a regression discontinuity design exploiting the time at which respondents completed the survey and find that the vaccine reinstatement substantially restored vaccination intentions.

A clear understanding of community response to government decisions is crucial for policy makers and health officials during the COVID-19 pandemic. In this study, we document the determinants of implementation and compliance with stay-at-home orders in the USA, focusing on trust and social capital. Using cell phone data measuring changes in non-essential trips and average distance traveled, we find that mobility decreases significantly more in high-trust counties than in low-trust counties after the stay-at-home orders are implemented, with larger effects for more stringent orders. We also provide evidence that the estimated effect on post-order compliance is especially large for confidence in the press and governmental institutions, and relatively smaller for confidence in medicine and in science.

Better understanding whether and how communities respond to government decisions is crucial for policy makers and health officials in response to the COVID-19 pandemic. In this study, we document the socioeconomic determinants of COVID-19 stay-at-home orders' compliance in the U.S. Using cell phone data measuring changes in average distance traveled and non-essential visitation, we find that: stay-at-home orders reduce mobility by about 8­–10 percentage points; high-trust counties decrease their mobility significantly more than low-trust counties post-lockdown; and counties with relatively more self-declared democrats decrease significantly more their mobility. We also provide evidence that the estimated eeffct on compliance post-lockdown is especially large for trust in the press, and relatively smaller for trust in science, medicine or government.

Es wird ein liberaler Ansatz zum Umgang mit der aktuellen Corona-Pandemie vorgestellt, der mehr auf individuellen Entscheidungen und Eigenverantwortung setzt als auf staatliche Vorgaben und Zwang, die weder besonders effektiv noch effizient sind. Die Anwendung dieses Ansatzes wird für zahlreiche Unterthemen skizziert und diskutiert, es werden allerdings auch mögliche Grenzen benannt. A liberal approach to dealing with the current coronavirus pandemic is presented, which relies more on individual decisions and personal responsibility than on state requirements and coercion that are neither particularly effective nor efficient. The application of this approach is outlined and discussed for numerous sub-topics, but possible limits are also named.

Dieser Bericht beschreibt die Impfbereitschaft und Akzeptanz einer Impfpflicht gegen Covid-19 in Juni und Juli 2020 in Deutschland auf Basis einer Teilstichprobe (SOEP-CoV) des Sozioökonomischen Panels, die zum Themenkomplex Covid-19 befragt wurde. SOEP-CoV beinhaltete auch Fragen zur Impfbereitschaft und zur Akzeptanz einer Impfpflicht gegen Covid-19. Das wichtigste Ergebnis unserer Studie ist, dass sich rund 70 Prozent der Erwachsenen in Deutschland freiwillig gegen das Corona- Virus impfen lassen würden, so ein Impfstoff ohne nennenswerte Nebenwirkungen vorhanden wäre. Gegen bzw. für eine generelle Impfpflicht gegen das Virus spricht sich jeweils eine Hälfte der Befragten aus. Dabei ist die Zustimmungsrate zur Impfpflicht bei denjenigen, die sich freiwillig impfen lassen würden, mit rund 60 Prozent deutlich höher als bei denjenigen, die sich nicht freiwillig impfen lassen würden, unter denen sie nur 27 Prozent beträgt.

This paper explores the relationship between Covid-19 infection rates, race, and type of work. We focus on three U.S. cities-Chicago, New York, and Philadelphia-allowing us to exploit zip code-level variation in infection rates and testing rates over time, while controlling for a variety of neighborhood demographic characteristics. We find that neighborhoods with higher Black and Hispanic population shares, and neighborhoods with higher shares of workers in high-social contact jobs within essential businesses, had disproportionately higher Covid-19 infection rates, even after applying our testing and demographic controls. These higher rates coincide with citywide peak infection rates, suggesting an amplified response for these groups. Local variation in type of work accounts for relatively little of the variation in infection rates by race. Additional evidence for Arizona, Florida, and Texas also shows amplified infection rates for these groups around statewide peak infection rates, despite their peaks occurring months after the cities in our main sample. Evidence from these states also shows higher infection rates among high-social contact workers in nonessential businesses that coincides with a more aggressive reopening of these businesses.

Elections may take place in precarious environments that even pose health risks. I consider the case of Bavaria, where close to ten million people were asked to vote in the municipal elections on March 15 of 2020, to quantify the toll of elections in a pandemic. Despite declaring a state of emergency on the very next day, two weeks later, Bavaria had left behind any other German state in terms of COVID-19 infections and deaths per capita. Using district-level health, demographic, and economic data, I find that at least 3,700 or 15% of the cumulative increase in positive test results between March 15 and April 4 are explained by a dummy variable for Bavaria. Across Bavarian districts, a 1% increase in voter participation is associated with an additional 13.6 positive tests and 1.2 deaths per 100,000 inhabitants over the following three weeks.

To fight the spread of Covid-19, many countries implemented unprecedented social distancing policies. This is the first paper that uses an event-study approach to examine the effects of the German social distancing policies on (a) individual behavior and (b) the spread of the epidemic. Combining administrative health data and cell phone data, we find that the policies, first, heavily reduced citizens’ mobility and, second, strongly contained the epidemic. In comparison to a benchmark without social distancing, within three weeks, the policies avoided 84% of the potential Covid-19 cases (point estimate: 499.3K) and 66% of the potential fatalities (5.4K).

Understanding the effectiveness of social distancing on the spread of COVID-19 is crucial to justify economically costly social distancing measures. We present a case study focusing on the three Scandinavian countries. Whereas Denmark and Norway imposed relatively strict measures, Sweden follows an extraordinarily lenient approach. We use an event-study approach in which Sweden serves as a counterfactual to Denmark/Norway to estimate the measures' effectiveness. We estimate that in the counterfactual in which Denmark/Norway implemented Sweden's more lenient measures the number of hospitalizations would have peaked between around 15-20 days later. The peak number of hospitalizations in Denmark (Norway) would have been 133 (231) percent higher, and the peak number of ICU patients would have increased by 107 (140) percent.

Der Beitrag vermittelt einem wissenschaftlich gebildeten Publikum diesseits der medienüblichen Virologinnen den Mechanismus epidemiologischer Modelle. Daneben wird die Politik in einem epidemiologischen Standardmodell endogenisiert und die zentrale Hypothese anhand von RKI-Daten überprüft. Es zeigt sich, dass durch die Erweiterung des SIR-Modells um eine politische Feedback-Schleife eine "zweite Welle" endogen enstehen kann. Eine vorläufige empirische Analyse deutet auf eine gewisse Plausbilität des postulierten Mechanismus hin.

Mit einem um die Behandlungskapazität des Gesundheitssystems erweiterten epidemiologischen SIRD-Modell werden Mechanismen und Dynamik einer Virusepidemie wie Corona anhand von stilisierten politischen Reaktionsmustern (Ignore, Shutdown, Ignore-Shutdown-Relax) simuliert. Ferner werden aus dem Modell Lehren für die statistische Analyse von Corona gezogen, wie die Aussagekraft publizierter Verdopplungszeiten und Reproduktionszahlen. Die Dunkelziffer unbestätigter Fälle und die im Epidemieverlauf variable Genauigkeit von medizinischen Infektionstests werden diskutiert. Zur Messung der medizinischen Kosten von Corona sowie für regionale und internationale Vergleiche wird ein Schadensindex der verlorenen Lebenszeit vorgeschlagen. Zuletzt geht die Arbeit kurz auf die ökonomischen Kosten von Corona in Deutschland ein. Using an epidemiological SIRD model, extended by treatment capacity of the health care system, mechanisms and dynamics of a virus epidemic such as Corona are simulated by means of stylized political reaction patterns (Ignore, Shutdown, Ignore-Shutdown-Relax). Moreover, lessons will be drawn from the model for statistical analysis of corona, such as the significance of published doubling times and reproduction rates. The (dark) figure of unconfirmed cases and the accuracy of medical infection tests, which varies during the course of an epidemic, will be addressed. To measure the medical costs of corona, as well as for regional and international comparisons, an index of lost lifetime is proposed. Finally, the paper briefly discusses the economic costs of corona in Germany.

We study how intentions to comply with the self-isolation restrictions introduced in Italy to mitigate the COVID-19 epidemic respond to the length of their possible extension. Based on a survey of a representative sample of Italian residents (N=894), we find that respondents who are positively surprised by a given hypothetical extension (i.e. the extension is shorter than what they expected) are more willing to increase their self-isolation. In contrast, negative surprises (extensions longer than expected) are associated with a lower willingness to comply. In a context where individual compliance has collective benefits, but full enforcement is costly and controversial, communication and persuasion have a fundamental role. Our findings provide insights to public authorities on how to announce lockdown measures and manage people's expectations.

In March 2020, shelter-in-place and social-distancing policies have been enforced or recommended all over the world to fight the COVID-19 pandemic. However, strict containment is hardly achievable in low-income countries, as large parts of population are forced to continue income-generating activities to escape extreme poverty or hunger. To assess the trade-off between poverty and a higher risk of catching COVID-19, we use regional mobility to work and poverty rates across 241 regions of 9 countries from Latin America and Africa. With a difference-in-difference approach around the time of lockdown announcements, we measure the differential time variation in work mobility between high and low-poverty regions. We find that the degree of work mobility reduction is significantly driven by the intensity of poverty. Consistently, human movements vary significantly more between poverty levels when it come to work rather than less vital activities. We also estimate how higher poverty rates translate into a faster spread of COVID-19 cases through the channel of work mobility.

While degraded trust and cohesion within a country are often shown to have large socioeconomic impacts, they can also have dramatic consequences when compliance is required for collective survival. We illustrate this point in the context of the COVID-19 crisis. Policy responses all over the world aim to reduce social interaction and limit contagion. Using data on human mobility and political trust at regional level in Europe, we examine whether the compliance to these containment policies depends on the level of trust in policy makers prior to the crisis. Using a double difference approach around the time of lockdown announcements, we find that high-trust regions decrease their mobility related to non-necessary activities significantly more than low-trust regions. We also exploit country and time variation in treatment using the daily strictness of national policies. The efficiency of policy stringency in terms of mobility reduction significantly increases with trust. The trust effect is nonlinear and increases with the degree of stringency. We assess how the impact of trust on mobility potentially translates in terms of mortality growth rate.

This study examines the effects of oil supply and global demand shocks on the volatility of commodity prices in the metal and agricultural commodity markets using the SVAR model. The empirical evidence is based on real time daily closing international commodity prices covering the period 2 December 2019 to 1 October 2020. The findings are presented in cumulative impulse responses and variance decompositions. The former is utilized to examine the accumulated influence of structural shocks on the volatility of agricultural and metal commodities whereas the latter reflect the share of variation in the volatility of each commodity arising from each structural shock. Various patterns are provided on how metal and agricultural commodity prices have been influenced by the COVID-19 pandemic. Policy implications are discussed.

The Covid-19 outbreak has led to extensive declines in international commodity prices. The outbreak as well as measures fashioned to contain it has been weighing down on global supply chains and commodity prices. The pandemic has been accompanied with unprecedented shock that has disrupted both the demand and supply of commodities. In view of the widespread global impact of Covid-19, this paper analyses the impact of the outbreak on global commodity prices with particular emphasis on the energy, agricultural and metals and materials sectors using international global prices and indices to trend the movements. In the wake of oil price war and dampened oil demand, the energy sector was the most hit with 15% average monthly decline in energy indices between December 2019 and April 2020. Oil recorded its largest one-month plunge on record in March. Movements in coal indices showed more resilience to the pandemic compared to crude oil and natural gas. Base metals were the most affected sector after energy with -3.49% average monthly changes in indices between December 2019 and April 2020. Of the major base metals and minerals, aluminum appears less affected by the outbreak compared to copper and zinc. In contrast, precious metals prices and indices remain stable and is the only commodity sector with positive monthly average change (1.99%) during the period. Gold prices maintained steady gains while silver and platinum prices followed a similar but weaker trend. The agricultural commodity indices largely maintained strong upward movement but plummeted at monthly average of 0.89% between December 2019 and April 2020. Grains and cereals proved more resilient to Covid-19 pandemic compared to timber, beverages, raw materials, and oils & meals.

This study assesses the incidence of the Covid-19 pandemic on poverty levels in 50 African countries by employing the PovcalNet computational tool for poverty monitoring. The empirical evidence is based on: (i) Pre Covid-19 macroeconomic projections of October 2019 and revised macroeconomic projections of April 2020 and (ii) three poverty thresholds, notably, US$1.90, US$3.20, and US$5.50 per day for the extreme, middle and higher poverty lines. The following main findings are established. First, the extreme poverty line of US$1.90 per day has increased by US$0.1 per day while the middle poverty line and the higher line have increased by US0.19$ and US0.32$, respectively. Second, the poverty headcount has increased to 35.85% for the US1.90$ poverty line, 57.55% for the US3.20$ per day poverty line and 76.42% for the higher poverty line (US5.5$ per day). Third, the corresponding additional percentage points in poverty headcount ratio are: (i) an increase of 2.09% for the poverty thresholds of US1.90$ per day and US3.2$ per day, corresponding to 28, 140, 345 and 26, 418, 200 million, respectively of the new poor in absolute terms and (ii) a boost of 1.78% for the higher poverty line of US5.5$ per day, corresponding to 19, 062, 643 million of the new poor. Fourth, country-specific tendencies are also provided for more targeted policy implications.

We estimate the economic impact of South Korea's targeted responses to the first large-scale COVID-19 cluster in Seoul. We find that foot traffic and retail sales decreased only within a 300 meter radius of the cluster and recovered to its pre-outbreak level after four weeks. The reductions appear to be driven by temporary business closures rather than the risk avoidance behavior of the citizens. Our results imply that less intense, but more targeted COVID-19 interventions, such as pin-pointed, temporary closures of businesses, can be a low-cost alternative after lifting strict social distancing measures.