We investigate the role of information strategy in shifting the purchasing preferences of “green” organic consumers towards a subset of “greener” products that foster adaptation to climate change. We focus on organic pasta, a widely consumed food, to conduct field experiment that involves consumers purchasing on the on-line shop of an Italian organic brand leader. Participants received one of two informational messages about an ancient durum wheat cultivar, renowned for its drought tolerance compared to modern durum wheat. The colloquial message results in 13% increase in the market share of “greener” pasta, despite its price premium. Conversely, the science-based message is effective only among consumers who prioritize environmental sustainability in their organic food purchases and rely on scientific information in their daily lives. Overall effects persist for at least three months and are more pronounced among women, young individuals, and those with higher levels of education. Potential moral licensing is detected among the “greenest” consumers who were already highly engaged.

This paper studies the origins and consequences of online misinformation, conspiracy theories, and fake news on Twitter in the wake of the COVID-19 pandemic in Italy. We map COVID skeptic tweets with the help of a Natural Language Processing pre-training AlBERTo (Polignano et al., 2019). First, we study if the heterogeneity in the COVID skepticism spread across Italian municipalities was related to pre-COVID online fake-news attitudes, local political governments, and other local socio-economic characteristics. We then analyze if Italian municipalities where the mismatch between the rigidity of containment measures vis-à-vis the severity of COVID-19 spread was more significant were more likely to engage in online COVID skepticism. We exploit a unique setting of introducing an economic lockdown during the first wave of the pandemic, which imposed the closure of a set of non-essential businesses and, consequently, exposed local labor markets to different degrees of economic hardship. Finally, we measure to what extent the spread of online COVID fake news was associated with actual differences in the uptake of COVID shots. We find that stringent policies in municipalities less affected by the pandemic caused a significant rise in COVID online skepticism. We also show that COVID skepticism spread on Twitter contributed to vaccine hesitancy, uncovering the potential unintended consequences of stringent and controversial policies not only on public opinion but also on costly health-related choices. While the temporary policy remedy is the legal coercion imposing costs on decisions to opt out of vaccine obligation, accurate management of information biases holds the promise of enabling people to make better choices in their own and public best interest.

We quantify the effects of online vaccine-skepticism spread on vaccine takeup and vaccine-preventable health complications among individuals untargeted by the immunization. We collect the universe of Italian vaccine-related tweets for the 2013-2018 period, label the anti-vax stances through Natural Language Processing, and match them with vaccination coverage and vaccine-preventable hospitalizations data at the most granular level available (municipality and year). We propose a model of opinion dynamics formation on social networks, distinguishing between network formation as a function of homophily and the role of controversialness of vaccine-related topics. With the model and the simulations, we show that pediatric vaccine mandates increased the controversialness of the topic, engendering two opposite clusters that endogenously raised the radicalization of opinions among Twitter users. We then provide a monetary parameter estimate on the effects of vaccine-skeptic online activity for society as a whole and for individuals not- targeted by immunization and overcome the issue of endogenous link formation by proposing an Instrumental Variables approach. We leverage the intransitivity in network connections and the exogeneity in the impact of users’ “friends of friends” to isolate exogenous source of variation for individual vaccine-related stances. We find that a 10 pp increase in the municipality’s anti-vax stance causes a 0.43pp decrease in coverage of the Measles-Mumps-Rubella vaccine, a 2.1 additional hospitalization every 100k residents among individuals untargeted by the immunization (newborns, the immunosuppressed, pregnant women) and an excess expenditure of 7311 euro, representing an 11% increase in health expenses.

We use longitudinal electronic clinical data on a large representative sample of the Italian population to estimate the lifetime profile costs of different BMI classes – normal weight, overweight, and obese (I, II, and III) – in a primary care setting. Our research reveals that obese patients generate the highest cost differential throughout their lives compared to normal weight patients. Moreover, we show that overweight individuals spend less than those with normal weight, primarily due to reduced expenditures beginning in early middle age. Our estimates could serve as a vital benchmark for policymakers looking to prioritize public interventions that address the obesity pandemic while considering the increasing obesity rates projected by the OECD until 2030.

We investigate the heterogeneous effects of daily particular matter (PM) pollution on Italian hospitalizations and their costs. We exploit public transportation strikes as plausibly-exogenous shocks in PM. We find that young individuals, an arguably healthy age group, exhibit economically meaningful responses to changes in air pollution. A higher prevalence of pollution-induced hospitalizations also exists among the elderly, low educated individuals and migrants coming from low income countries. Our results imply a large role for differential avoidance behavior driving heterogeneous marginal effects. PM exposure also affects the intensive margin since pollution-induced hospitalizations are not only more frequent but they are characterized by a higher complexity, generating additional costs.

This article evaluates the impact of two nudges on stimulating the use of doggy bags in restaurants. We run a field experiment at 14 restaurants in the province of Turin (Italy). In the first group of restaurants, we manipulated the descriptive social norm. In a second group we changed the default option - whereby customers asked for the doggy bag - by instead directing the waiter to automatically deliver the doggy bag unless told not to. A third group of restaurants was used as a control with no intervention. We find that the social norm intervention led to a sizeable increase in the use of doggy bags, while the default manipulation had a non-statistically significant impact.

This paper uses a field experiment to estimate behavioral parameters from a structural model of residential adoption of technology. As our model includes both economic and psychological factors, we are able to identify the role of prices, social norms, social pressure, and curiosity on the adoption decision. We find that prices and social norms influence the adoption decision along different margins, opening up the opportunity for economics and psychology to be strong complements in the diffusion process. In addition, welfare estimates from our structural model point to important household heterogeneities: whereas some consumers welcome the opportunity to purchase and learn about the new technology, for others the inconvenience and social pressure of the ask results in negative welfare. As a whole, our findings highlight that the design of optimal technological diffusion policies will require multiple instruments and a recognition of individual household heterogeneities.

The role of environmental information is crucial in driving individuals' environmentally relevant behaviors. The aim of this paper is to shed light on the impact of different sources of information and trust in information providers on four behaviors related to waste management and resource efficiency. In order to consider dynamic effects related to behaviors of different age groups, we adopt a pseudo-panel approach using data from three cross-sectional Eurobarometer surveys. The use of multivariate regression analysis allows us to show the existence of complementarities among “similar” behaviors. Our results suggest that the use of eco-information sources and trust in different providers significantly affect green behaviors of EU citizens towards a ‘truly’ circular economic system.

We test the empirical content of the assumption of preference dependent beliefs using a behavioral model of strategic decision making in which the rankings of individuals over final outcomes in simple games influence their beliefs over the opponent’s behavior. This approach— by analogy with Psychological Game Theory—allows for interdependence between preferences and beliefs but reverses the order of causality. We use existing evidence from a multi-stage experiment in which we first elicit distributional preferences in a Random Dictator Game, then estimate beliefs in a related 2×2  effort game conditional on these preferences. Our structural estimations confirm our working hypothesis on how social preferences shape beliefs: subjects with higher guilt (envy) expect others to put less (more) effort, which reduces the expected difference in payoffs.