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We investigate the impact of COVID-19 on tourism expenditures by analyzing survey data collected from participants of one of the major amateur cycling races in Italy—the Nove Colli. We gathered information from different types of participants (tourists, residents, day-trippers) about their travel expenses, accommodation, food and beverage, and side goods such as sports equipment. The survey covers three race editions: pre-COVID-19 in 2016, post-lockdown in 2021, and post-COVID-19 in 2022, for a total of 2734 respondents. Using a quasi-difference-in-differences approach, we find a significant increase in total tourism expenditures due to COVID-19, primarily driven by a substantial increase in side goods expenses, which more than doubled the rise in food and beverage expenses. This result can be partly explained through revenge spending as a form of compensatory consumption behavior and inform policy-makers on how individuals' spending patterns may change in the aftermath of an exogenous shock. [ABSTRACT FROM AUTHOR]

This paper addresses an area of growing concerns for laboratory researchers: is subjects' behaviour affected by prior experiences in laboratory experiments? We address the question with a large and highly diverse international dataset and an operationalisation strategy that allows our findings to cohere with previous work while shedding new light on future research. The findings presented in this article are drawn from original data gathered as part of one of the largest tax compliance experiments ever conducted, involving more than 3,000 participants in six countries, across 16 different laboratories. Our results reveal that subjects' behaviour correlates with their past experimental experiences, in a way that could bias results and compromise a study's external validity. However, this change in behaviour due to experiences occurs only after subjects have participated in at least two previous laboratory experiments. The findings have implications not just for tax compliance research, but for allocation experiments more generally and for participant recruitment particularly. [ABSTRACT FROM AUTHOR]

This is the second of two companion papers that discuss accidents caused by robots. In the first paper (Guerra et al., 2021), we presented the novel problems posed by robot accidents, and assessed the related legal approaches and institutional opportunities. In this paper, we build on the previous analysis to consider a novel liability regime, which we refer to as 'manufacturer residual liability' rule. This makes operators and victims liable for accidents due to their negligence – hence, incentivizing them to act diligently; and makes manufacturers residually liable for non-negligent accidents – hence, incentivizing them to make optimal investments in R&D for robots' safety. In turn, this rule will bring down the price of safer robots, driving unsafe technology out of the market. Thanks to the percolation effect of residual liability, operators will also be incentivized to adopt optimal activity levels in robots' usage. [ABSTRACT FROM AUTHOR]

Tort models assume symmetry in the behavior of injurers and victims when faced by a threat of liability and a risk of harm without compensation, respectively. This assumption has never been empirically validated. Using a novel experimental design, we study the behavior of injurers and victims when facing symmetric accident risks. Experimental results provide qualified support for the symmetric behavior hypothesis. [ABSTRACT FROM AUTHOR]

In robot torts, robots carry out activities that are partially controlled by a human operator. Several legal and economic scholars across the world have argued for the need to rethink legal remedies as we apply them to robot torts. Yet, to date, there exists no general formulation of liability in case of robot accidents, and the proposed solutions differ across jurisdictions. We proceed in our research with a set of two companion papers. In this paper, we present the novel problems posed by robot accidents, and assess the legal challenges and institutional prospects that policymakers face in the regulation of robot torts. In the companion paper, we build on the present analysis and use an economic model to propose a new liability regime which blends negligence-based rules and strict manufacturer liability rules to create optimal incentives for robot torts. [ABSTRACT FROM AUTHOR]