Online health information seeking behavior (e-HISB) is becoming increasingly common and the trend has accelerated as a result of the COVID-19 pandemic when individuals strongly relied upon the Internet to stay informed by becoming exposed to a wider array of health information. Despite e-HISB having become a global trend, very few empirical investigations have analyzed its potential influence on healthcare access and individuals' health status. In this paper, we try to fill this gap. We use data from the second SHARE Corona Survey, supplemented with data from the previous 8th wave of SHARE, and estimate a recursive model of e-HISB, healthcare access, and individuals' health status that accounts for individuals' unobserved heterogeneity. Our findings suggest that e-HISB can empower individuals to better understand health concerns, facilitating improved health condition management. However, e-HISB can also trigger a chain reaction, as navigating vast amonts of online health information can heighten fear and anxiety. This increased anxiety may lead to higher utilization of medical services, adversely affecting individuals' perceptions of their health.

A widely held belief is that autocratic governments have been more effective in reducing the movement of people to curb the spread of COVID-19. Using daily information on lockdown measures and geographic mobility across more than 130 countries, we find that autocratic regimes have indeed imposed more stringent lockdowns and relied more on contact tracing. However, we find no evidence that autocratic governments were more effective in reducing travel, and evidence to the contrary: compliance with the lockdown measures taken was higher in countries with democratically accountable governments. Exploring a host of potential mechanisms, we provide suggestive evidence that democratic institutions are associated with attitudes that support collective action, such as mounting a coordinated response to a pandemic.

We report the results of an experiment on willful information avoidance regarding measures to address Covid-19. In the experiment, participants choose between two options, each associated with a contribution to the Corona Fund of the Red Cross USA and a payment to the participant. Depending on the treatment, either the participants' payoff, the donation, both or none of these pieces of information were hidden, but revealable. With this design, we can separate motivated reasons for ignorance from non-motivated reasons, both of which are present in our data. Furthermore, we find evidence of both self-serving and pro-social information avoidance. These behavioral patterns correlate with the subjects' political attitudes: while voters of the Democratic Party are prone to exhibit pro-social information avoidance, Republican voters rather engage in self-serving information avoidance.

This study uses data from a survey of micro, small, and medium enterprises in India to document the impact of Covid-19 containment lockdowns on firms, their responses, and adaptation strategies. We find that the profits and sales declined substantially for the majority of firms. Temporary closures, pay cuts, and temporary lay-offs were the key measures utilized by firms to cope with the shock. Firms did not have adequate liquidity to last beyond six months, albeit the majority expected the pandemic to be over within that period. Micro-enterprises were the most fragile. Using a retrospective panel and matching-based difference-in-differences strategy, we show that exporting firms were able to cushion themselves from the domestic market contractions resulting from the lockdown.

I study the co-evolution between public opinion and party policy in situations of crises by investigating a policy U-turn of a major Austrian right-wing party (FPÖ) during the Covid-19 pandemic. My analysis suggests the existence of both i) a "Downsian" effect, which causes voters to adapt their party preferences based on policy congruence and ii) a "party identification" effect, which causes partisans to realign their policy preferences based on "their" party's platform. Specifically, I use individual-level panel data to show that i) "corona skeptical" voters who did not vote for the FPÖ in the pre-Covid-19 elections of 2019 were more likely to vote for the party after it embraced "corona populism", and ii) beliefs of respondents who declared that they voted for the FPÖ in 2019 diverged from the rest of the population in three out of four health-related dimensions only after the turn, causing them to underestimate the threat posed by Covid-19 compared to the rest of the population. Using aggregate-level panel data, I study whether the turn has produced significant behavioral differences which could be observed in terms of reported cases and deaths per capita. Paradoxically, after the turn the FPÖ vote share is significantly positively correlated with deaths per capita, but not with the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing, which causes a correlation between the number of "corona skeptics" and the share of unreported cases after the turn. I find empirical support for this hypothesis in individual-level data from a Covid-19 prevalence study that involves information about participants' true vs. reported infection status. I finally study a simple heterogeneous mixing epidemiological model and show that a testing bias can indeed explain the apparent paradox of an increase in deaths without an increase in reported cases. My results can, among others, be used to enrich formal analyses regarding the co-evolution between voter and party behavior.

This paper explores the causal link between the likelihood of re-migration to cities and the perceived threat of contracting COVID-19 using novel data on male reverse migrant workers in India. We find that reverse-migrants who believe there is a significant chance of contracting COVID-19 display a significantly lower likelihood of returning to their urban workplaces, regardless of their duration of migration. On the other hand, longer-duration migrants display a lower perceived chance of contracting COVID-19 than shorter-duration migrants. We also contribute to the migration literature by linking behavioural attributes to the decision to migrate. We find that more impatient individuals display a heightened belief regarding contracting COVID-19 and a higher projected likelihood of returning to work. Finally, we find that while both loss and risk-averse individuals have a lower projected likelihood of returning to urban workplaces, only loss-averse individuals perceive that their chance of contracting COVID-19 is lower.

This paper examines the impacts of emergency cash-transfers on individuals' social distancing behaviour and beliefs about COVID-19. We focus on the impacts of "Auxilio Emergencial" (AE): a large-scale cash-transfer in Brazil targeting low-income individuals who were unemployed or informally employed during the pandemic. To identify causal effects we exploit exogenous variation, arising from the AE design, in individuals' access to the cash-transfer programme. Using data from an online survey, our results suggest that eligibility to the emergency cash transfer led to a reduced likelihood of individuals contracting COVID-19, likely to have been driven by a reduction in working hours. Moreover, the cash transfer seems to have increased perceptions about the seriousness of coronavirus, while also exacerbating misconceptions about the pandemic. These findings indicate effects of emergency cash-transfers in determining individuals' narratives about a pandemic, in enabling social distancing and potentially in reducing the spread of the disease.

We systematically examine the acute impact of exposure to a public health crisis on anti-social behaviour and economic decision-making using unique experimental panel data from China, collected just before the outbreak of COVID-19 and immediately after the first wave was overcome. Exploiting plausibly exogenous geographical variation in virus exposure coupled with a dataset of longitudinal experiments, we show that participants who were more intensely exposed to the virus outbreak became more anti-social than those with lower exposure, while other aspects of economic and social preferences remain largely stable. The finding is robust to multiple hypothesis testing and a similar, yet less pronounced pattern emerges when using alternative measures of virus exposure, reflecting societal concern and sentiment, constructed using social media data. The anti-social response is particularly pronounced for individuals who experienced an increase in depression or negative affect, which highlights the important role of psychological health as a potential mechanism through which the virus outbreak affected behaviour.

Political trust is an important predictor of compliance with government policies, especially in the face of natural disasters or public health emergencies. During the COVID-19 pandemic, for example, multiple studies related political trust to increased compliance with mobility restrictions. Yet these findings come mostly from high-income countries where political trust and wealth correlate positively. In Latin America, both variables correlate negatively, allowing for better testing of competing explanations. Using a difference-in-differences design, we find that in Latin America wealth and, counterintuitively, low political trust predict increased compliance. To understand mechanisms, we decompose political trust and wealth into underlying predictors (social protection, corruption, and education) and reinsert them into the model. While education, as a wealth proxy, predicts decreased mobility across all periods, social protection, which was the strongest predictor of political trust, relates significantly to increased mobility, but only at the beginning of the lockdown prior to distribution of emergency support. This suggests the existence of a public health moral hazard early in the pandemic, whereby citizens who benefited previously from government benefits may have been more risk tolerant in the face of the COVID-19 threat. We interpret these findings within the context of the region's recent "inclusionary turn." Future studies should explore the distinct relationships between political trust, risk perception, and compliance, especially in low- and middle-income countries, and their implications for policy responses to national emergencies.

The negative health effects and mortality caused by the COVID-19 pandemic disproportionately fell upon older and disabled people. Protecting these vulnerable groups has been a key policy priority throughout the pandemic and related vaccination campaigns. Using data from the latest survey of the UK Household Longitudinal Study on COVID-19 we found that people who receive informal care have higher probability of being infected when compared to those not receiving informal care. Further, we found that care recipients who are in the lowest income groups have a higher probability of catching the virus when compared to those in the highest income groups. We also estimated the likelihood of being infected for informal carers versus those who did not provide any care during the pandemic and found no significant differences between these two groups. Our empirical findings suggest that the standard measures introduced with the aim of protecting vulnerable groups, such as closing care homes or prioritising the vaccination of their staff, were not sufficient to avoid the spread of the virus amongst disabled and older people. Informal carers play an important role in the social care sector. As such, protecting vulnerable people by investing in the informal care sector should be a priority for future health policy.

Our study investigates the potential impact that COVID-19 and lockdown restrictions may have had on drug utilization and the role of patient age and education in reshaping it. We focused on patients affected by diabetes mellitus, who are likely to suffer a higher degree of morbidity and mortality due to COVID-19. We used a bi-monthly administrative panel dataset from January 2019 to December 2020 from Liguria (Italy), one of the regions with the highest number of individuals over the age of 65 in Europe. The results demonstrated that, after the initial shock, when patients tried to increase their personal stock of drugs to overcome the risk of possible additional barriers generated by the coronavirus, the hoarding effect almost disappeared. Adherence has drastically reduced during the COVID-19 pandemic and has never reached pre-COVID levels again. Older and poorly educated patients seem to have suffered more from the restrictions imposed by the lockdown and fear of contagion and they may be the ideal target group when considering possible policy interventions to improve adherence.

Longevity expectations (LE) are subjective assessments of future health status that can influence a number of individual health protective decisions. This is especially true during a pandemic such as COVID-19, as the risk of ill health depends more than ever on such protective decisions. This paper examines the causal effect of LE on some protective health behaviors and a number of decisions regarding forgoing health care using individual differences in LE. We use data from the Survey of Health Ageing and Retirement in Europe, and we draw on an instrumental variable strategy exploiting individual level information on parental age at death. Consistent with the hypothesis, we find that individuals, exhibiting higher expected longevity, are more likely to engage in protective behaviours, and are less likely to forgo medical treatment. We estimate that a one standard deviation increase in LE increases the probability to comply always with social distancing by 0.6%, to meet people less often by 0.4% and decreases the probability to forgo any medical treatment by 0.6%. Our estimates vary depending on supply side restrictions influencing the availability of health care, as well as individual characteristics such as their gender and the presence of pre-existing health conditions.

We show that compensation measures aimed at improving the fairness of a crisis policy response can unintendedly nudge compliance with emergency rules. We combine information on the distribution of relief funds across Italian municipalities during the novel coronavirus pandemic with data tracking citizens' movements through mobile devices and navigation systems. To assess the impact of transfers on compliance, we exploit a sharp kink schedule in the allocation of funds. The empirical analysis provides evidence that compliance increased with transfers, suggesting that the observance of emergency rules also depends on the fairness of the pandemic policy response.

This study investigates how the COVID-19 outbreak has shaped the volatility spillover between oil and Gulf Cooperation Council (GCC) stock markets. Contagion analysis is conducted by implementing a vector error correction (VECM) asymmetric BEKK model, wherein both cointegration and asymmetric features are considered. Financial market uncertainty caused by the recent health crisis is captured using Baker et al.'s (2020) newly developed infectious disease tracker. Our results indicate a significant discrepancy in the GCC group, as shock and volatility linkages between oil and equities are more apparent for some countries but not for others. The estimated VECM-asymmetric BEKK model reveals cross-market asymmetric spillover effects only in Kuwait, Qatar, and Saudi Arabia. We report that the global pandemic has strongly affected crude oil market volatility, while the GCC region seems to be less affected by the emergence of the new infectious disease. Our findings underscore the diversification opportunities offered by Gulf equity markets to international investors.

COVID-19 outbreaks at nursing homes during the recent pandemic have received ample media coverage and may have lasting negative impacts on individuals' perception of nursing homes. We argue that this could have sizable and persistent implications for savings and long-term care policies. Our theoretical model predicts that higher nursing home aversion should induce higher savings and stronger support for policies subsidizing home care. Based on a survey of Canadians aged 50 to 69, we document that higher nursing home aversion is widespread: 72% of respondents are less inclined to enter a nursing home because of the pandemic. Consistent with our model, we find that these respondents are more likely to have higher intended savings for old age because of the pandemic. We also find that they are more likely to strongly support home care subsidies.

We build an evolutionary game-theoretic model of the interaction between policymakers and experts in shaping the policy response to the COVID-19 pandemic. Players' decisions concern two alternative strategies of pandemic management: a "hard" approach, enforcing potentially unpopular measures such as strict confinement orders, and a "soft" approach, based upon voluntary and short-lived social distancing. Policymakers' decisions may also rely upon expert advice. Unlike experts, policymakers are sensitive to a public consensus incentive that makes lifting restrictions as soon as possible especially desirable. This incentive may conflict with the overall goal of mitigating the effects of the pandemic, leading to a typical policy dilemma. We show that the selection of strategies may be path-dependent, as their initial distribution is a crucial driver of players' choices. Contingent on cultural factors and the epidemiological conditions, steady states in which both types of players unanimously endorse the strict strategy can coexist with others where experts and policymakers agree on the soft strategy, depending on the initial conditions. The model can also lead to attractive asymmetric equilibria where experts and policymakers endorse different strategies, or to cyclical dynamics where the shares of adoption of strategies oscillate indefinitely around a mixed strategy equilibrium. This multiplicity of equilibria can explain the coexistence of contrasting pandemic countermeasures observed across countries in the first wave of the outbreak. Our results suggest that cross-country differences in the COVID-19 policy response need not be the effect of poor decision making. Instead, they can endogenously result from the interplay between policymakers and experts incentives under the local social, cultural and epidemiological conditions.

This paper explores the evolution of inequality of opportunity in the prevalence of chronic diseases along the life cycle and across different birth cohorts for individuals aged 50 or older and residing in 13 European countries. We adopt an ex-ante parametric approach and rely on the dissimilarity index as our reference inequality metric. In addition to a commonly used set of circumstances, we pay particular attention to the role of adverse early-life conditions, such as the experience of harm and the quality of the relationship with parents. In order to quantify the relative importance of each circumstance, we apply the Shapley inequality decomposition method. Our results suggest that inequality of opportunity in health is not stable over the life cycle - it is generally lower at younger ages and then monotonically increases. Moreover, it varies between different birth cohorts and is generally higher for younger individuals than for older age groups. Finally, the contribution of adverse early life conditions ranges between 25% and 45%, which is comparable to the share of socio-economic circumstances but significantly higher than the relative contribution of other demographic characteristics, especially at younger ages.

Did individuals' experiences with the harms of the COVID-19 pandemic influence their attitudes towards safety-net programs? To assess this question, we combine rich information about county-level impacts and individual-level perceptions of the early pandemic, repeated measurements of attitudes towards safety-net expansion, and pre-pandemic measurements of related political attitudes. Individuals facing higher county-level impact or greater perceived risks are more likely to support long-term expansions to unemployment insurance and government-provided healthcare when surveyed in June 2020. These differences persist across time, with experiences in the early months of the pandemic remaining strongly predictive of attitudes towards safety-net expansion in early 2021.

Using two large-scale surveys among households, we examine the drivers of public trust in banks, insurance companies, BigTechs, and other people in the United States and the Netherlands, and analyse whether the COVID-19 pandemic has affected public trust. Our results suggest that the COVID-19 pandemic did not have much effect on trust in financial institutions in the US and the Netherlands. However, trust in BigTechs and trust in other people declined in both countries, especially in the US. Our regression results show that the relationship between respondents' characteristics and (changes in) trust differs across the US and the Netherlands. However, for both countries we find evidence that individuals with poor health have lower levels of trust than healthy people, and that trust among poor-health respondents dropped more during the pandemic. Furthermore, trust in other people is positively related to trust in banks, insurance companies, and BigTechs.

Natural disasters raise challenging trade-offs between public health safety and inalienable rights like the active involvement in political choices through voting. We exploit a quasi-experimental setting provided by multiple ballots across regions and municipalities during the Italian 2020 elections to estimate the effect of voters' turnout on the spread of COVID-19. By employing an event-study design with a two-stage Control Function strategy, we find that post-poll new COVID infections increased by an average of 1.1% for each additional percentage point of turnout. Based on these estimates and real political events, we also show through a simulation that in-person voting during a high-infection regime may have a large impact on public health outcomes, more than doubling new infections, deaths and hospitalizations. These findings suggest that policy-makers' responses to natural disasters should be flexible and contingent to the emergency severity, in order to minimize social costs for citizens.

This paper studies the formation and the spread of crisis-driven racial animus during the coronavirus pandemic. Exploiting plausibly exogenous variation in the timing of the first COVID-19 diagnosis across US areas, we find that the first local case leads to an immediate increase in local anti-Asian animus, as measured by Google searches and Twitter posts that include a commonly used derogatory racial epithet. This rise in animus specifically targets Asians and mainly comes from users who use the epithet for the first time. These first-time ch-word users are more likely to have expressed animosity against non-Asian minorities in the past, and their interaction with other anti-Asian individuals predicts the timing of their first ch-word tweets. Moreover, online animosity and offline hate incidents against Asians both increase with the salience of the connection between China and COVID-19; while the increase in racial animus is not associated with the local economic impact of the pandemic. Finally, the pandemic-driven racial animus we documented may persist beyond the duration of the pandemic, as most racist tweets do not explicitly mention the virus.