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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.

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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.

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We use survey data to study how trust in government and consensus for the pandemic policy response vary with the propensity for altruistic punishment in Italy, the early epicenter of the pandemic. Approval for the management of the crisis decreases with the size of the penalties that individuals would like to see enforced for lockdown violations. People supporting stronger punishment are more likely to consider the government's reaction to the pandemic as insufficient. However, after the establishment of tougher sanctions for risky behaviors, we observe a sudden flip in support for the government. Higher amounts of the desired fines become associated with a higher probability of considering the COVID policy response as too extreme, lower trust in government, and lower confidence in the truthfulness of the officially provided information. These results suggest that lockdowns entail a political cost that helps explain why democracies may adopt epidemiologically suboptimal policies.

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In March 2021, Italian health authorities suspended the Vaxzevria vaccine (VA) for 4 days over reports of very rare blood disorders among recipients. We exploit the quasi-experimental setting arising from this break to study the drivers of vaccine hesitancy. Before the suspension, the VA vaccination trend followed the same pattern as Pfizer-Biontech (PB). After the suspension, VA and PB injections started to diverge, with VA daily decreasing by almost 60 doses per 100,000 inhabitants for the following 3 weeks. The resulting vaccination rate was 60 percent lower than the value that would have stemmed from the VA pre-suspension pattern. We show that the slowdown was weaker and less persistent in regions with higher COVID penetration and steadier and more pronounced in regions displaying greater attention to vaccine side effects as detected through Google searches. The public's interest in vaccine adverse events negatively correlates with COVID cases and deaths across regions.

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Evidence is growing that forms of incivility-e.g. aggressive and disrespectful behaviors, harassment, hate speech and outrageous claims-are spreading in the population of social networking sites' (SNS) users. Online social networks such as Facebook allow users to regularly interact with known and unknown others, who can behave either politely or rudely. This leads individuals not only to learn and adopt successful strategies for using the site, but also to condition their own behavior on that of others. Using a mean field approach, we define anevolutionary game framework to analyse the dynamics of civil and uncivil ways of interaction in online social networks and their consequences for collective welfare. Agents can choose to interact with others-politely or rudely-in SNS, or to opt out from online social networks to protect themselves from incivility. We find that, when the initial share of the population of polite users reaches a critical level, civility becomes generalized if its payoff increases more than that of incivility with the spreading of politeness in online interactions. Otherwise, the spreading of self-protective behaviors to cope with online incivility can lead the economyto non-socially optimal stationary states. JEL Codes: C61, C73, D85, O33, Z13. PsycINFO Codes: 2240, 2750.

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This paper presents the first empirical assessment of the causal relationship between social capital and health in Italy. The analysis draws on the 2000 wave of the Multipurpose Survey on Household conducted by the Italian Institute of Statistics on a representative sample of the population (n=46,868). Our measure of social capital is the frequency of meetings with friends. Based on IV and bivariate probit estimates, we find that individuals who meet friends every day or more time times a week are approximately 11-16% more likely to report good health.

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We test the relationship between happiness and self-rated health in Italy. The analysis relies on a unique dataset collected through the administration of a questionnaire to a representative sample (n = 817) of the population of the Italian Province of Trento in March 2011. Based on probit regressions and instrumental variables estimates, we find that happiness is strongly correlated with perceived good health, after controlling for a number of relevant socio-economic phenomena. Health inequalities based on income, work status and education are relatively contained with respect to the rest of Italy. As expected, this scales down the role of social relationships.

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The public health literature on the detrimental effects of social isolation has shown that the quantity of social connections is positively correlated with individual health. Drawing on pooled cross-sectional data, we test this hypothesis on a representative sample of the Italian population. Our findings show that, in addition to the quantity of interactions, it is their quality--as measured by subjective satisfaction derived from relationships with friends--that works as the best predictor of self-reported health. The frequency of meetings with friends is significantly and positively correlated with good health in all regressions. However, when we add our measure of the quality of relationships to the probit equations, the statistical significance of "quantitative" measures is scaled down. Satisfaction with relationships with friends exhibits a positive and highly significant coefficient. Results of the multivariate probit analysis point out the potential role of unobservable variables suggesting the existence of endogeneity problems which require further investigation. We point out the existence of health disparities based on socio-economic status. There is a higher probability that poorer and less educated individuals report poor health conditions. The risk is even higher for unemployed and retired workers. This paper contributes to the literature in two substantive dimensions. This is the first empirical study of the relationship between social interactions and health in Italy. Second, we add to previous empirical studies by taking into account not only the frequency of various kinds of meetings but also indicators of their "quality", as measured by agents' subjective satisfaction with their social participation. The reliability of the analysis also benefits from the uniqueness and comprehensiveness of our dataset, which tries to overcome a structural deficiency in Italian data by merging information on agents' behaviours and perceptions with data on household income.

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