Working papers

Abstract During the Covid-19 pandemic, the Omicron wave was notable for its highly transmissible and contagious variant of concern, coinciding with the availability of a vaccine that has been rolled out well earlier. In this paper, we address two key questions. First, we seek todesign a simple epidemiological model that can best capture the dynamics of Omicron infections. We demonstrate that combining the SIRDand SISD models provides an adequate solution. The second question examines the benefits of vaccination, in terms of both economicactivity and lives saved, once the model is implemented. Our results show that without vaccination, the human cost would have been fivetimes higher, and production losses would have doubled, due to stricter con- finement measures and a higher death toll. We also quantify the cost of vaccine hesitancy at more than 8,000 extra deaths.
Keywords Compartment models, COVID-19, Omicron wave, Vaccination benefit, Vaccine hesitation
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Abstract Modern society is increasingly polarized, even on purely factual questions, despite greater access to information than ever. In a model of sequential sociallearning, I study the impact ofmotivated reasoningon information aggregation. This is a belief formation process in which agents trade-off accuracy against ideological convenience. I find that even Bayesian agents only learn in very highly connected networks, where agents have arbitrarily large neighborhoods asymptotically. This is driven by the fact that motivated agents sometimes reject information that can be inferred from their neighbors’ actions when it refutes their desired beliefs. Observing any finite neighborhood, there is always some probability that all of an agent’s neighbors will have disregarded information thus. Moreover, I establish thatconsensus, where all agents eventually choose the same action, is only possible with relatively uninformative private signals and low levels of motivated reasoning.
Keywords Social Learning, Motivated Reasoning, Networks, Polarization
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Abstract Models of social learning conventionally assume that all actions are visible, whereas in reality, we can often choose whether or not to advertise our choices. Inthis paper, I study a model of sequential social learning in which social agents choose whether or not to let successors see their action, only wanting to do so if they are sufficiently confident in their choice (they are timid), and noise agents act randomly. I find that in sparse networks, this produces a form of unravelling to the effect that noise agents are overrepresented. This can damage learning to an arbitrary extent if social agents are sufficiently timid. In dense networks, however, no such unravelling occurs, and the combination of noise and timidity can facilitate complete learning even with bounded beliefs.
Keywords Sequential Social Learning, Endogenous Social Networks, Network Theory, Information Economics
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Abstract The expansion of intermittent electricity increases supply variability and requires greater flexibility from consumers. This results in welfare losses for these agents, which can nevertheless be mitigated by energy storage. Our model analyzes these welfare consequences in the context of short-term variability in renewable energy given fixed dispatchable and storage capacities. We explore an optimal control problem that determines a welfare-maximizing electricity consumption path by adjusting dispatchable and stored energy throughout the short-term production cycle of renewables. This optimization problem identifies three regimes (no storage and active storage, with or without capacity constraints) and provides the associated consumer welfare over this cycle. Under all three regimes, a certain degree of consumer flexibility is part of the optimal solution and entails welfare losses. Active storage reduces these losses but cannot eliminate them completely due to the energy conversion losses induced by this activity. However, when storage capacity is constrained, a proactive adjustment of this capacity can offset the losses.
Keywords Optimal control, Welfare analysis, Electricity consumption, Energy storage, Intermittent renewable
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Abstract The 2014 Automatic Exchange of Information (AEoI) represents the most comprehensive global effort to combat tax evasion by enabling cross-border information exchange on financial assets. We examine how this policy shifted offshore investment behavior. While the AEoI mandates reporting of financial assets, it excludes real estate holdings. Using administrative data on UK real estate purchases by foreign companies, we show that offshore users substituted financial assets for real estate in response to the new transparency regime. Our findings suggest that real estate assets now account for a growing share of offshore portfolios, partly due to their exclusion from the AEoI.
Keywords Hidden Wealth, Real estate, Tax Enforcement
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Abstract Prior work finds that individuals are often less prosocial when they can exploit uncertainty as an excuse. In contrast to prior work that largely explores the relevance of excuses in the gain domain, this paper investigates the relevance of excuses in both the loss and gain domains. In our laboratory experiment, participants evaluated risky payoffs for themselves and their partners in either the gain or loss domain, with or without interpersonal trade-offs. We found that participants exhibited excuse-driven risk behaviors in both domains. We also documented significant individual heterogeneity in the degree of excuses, influenced by factors such as individuals’ risk preferences, beliefs about others’ risk preferences, and the size of the risk.We present a self-signaling model that incorporates self-image concerns to explain our experimental findings. We show that excuse-driven risk behavior arises because people misattribute their selfish behavior to risk preferences rather than a reduced level of altruism.
Keywords Risk preferences, Self-image, Misattribution, Experiment, Prosocial behavior
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Abstract In this paper, we examine the determinants of investor money flows in sustainable mutual funds. Owing to differences in preferences, we posit that ESG investors are more sensitive to mutual fund financial attributes than impact investors are. Using a dataset of 840 actively managed European sustainable equity funds for the period 2018–2025, we find that fund flows are significantly more sensitive to past performance for ESG funds than for impact funds. Our empirical results are in line with impact investor specificity among sustainable investors: the first invest for ESG values, whereas the latter invest with ESG values. Our findings are robust to alternative sustainable classifications, geographical investment areas, investor types and time sampling.
Keywords Impact investing, Mutual funds, Investor behavior, Cash flows
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Abstract Political campaigns influence how voters prioritize issues, which in turn impacts electoral outcomes. In this paper, we study how candidates’ communication shapes which issues prevail during the campaign, through which mechanisms, and to what extent. We develop an electoral competition model with two candidates, each endowed with exogenous platforms and characteristics. Candidates allocate strategically their communication time across two issues to maximize their expected vote shares. We find that when one candidate holds similar comparative advantages on both issues, the disadvantaged candidate communicate on a single issue to saturate the campaign with one topic and then increases the randomness of the election. The advantaged candidate has the opposite incentive and communicate on both issues, creating an asymmetry in the campaign. We show that in some cases, the campaign can become entirely centered on a single issue.
Keywords Electoral competition, Communication time, Priming
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Abstract This paper considers the dynamics of pollution and sustainable growth in a context where the detrimental effects of pollution on total factor productivity can push the economy to a point of collapse. With environmental policy constrained by tax revenues, we investigate how the proximity to collapse -distance to the end -influences the balance between mitigation and adaptation spending. We show that adaptation policies are recommended when pollution intensity is high, whereas mitigation policies may be more effective when pollution intensity is low. Financing these policies by a carbon tax is more effective than an income tax. Examining the welfare of present and future generations, we reveal that the trade-off between mitigation and adaptation does not align across generations: while current generations may prefer adaptation, future generations tend to benefit more from mitigation.
Keywords Environmental policy, Fiscal policy, Sustainability, Environmental damage
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Abstract Between 1954 and 1998, the tobacco industry funded more than 1,900 research projects at a total cost of $355 million, on topics such as the roles of heredity and nutrition in cancer. Even though legitimate, this research was intended to divert attention from the harmful effects of tobacco. We provide the first formal analysis of such diversion research. We show that special interests may have strong incentives to affect the scientific agenda, even when the research itself is unbiased. This form of scientific lobbying yields large welfare losses and raises concerns about the private funding of research.
Keywords Scientific Uncertainty, Scientific lobbying, Private research funding
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