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CORPORATE TAXATION AND FIRM HETEROGENEITY
No full textThis paper explores the differentiated effects of corporate tax changes based on firm characteristics and evaluates the potential impact of a tax system modulated by both firm size and age. Using tax rate variations across U.S. states and comparing adjacent counties across state borders, we find that corporate taxes significantly reduce employment in small and young firms, while having no notable impact on large and older firms. We then develop a model to analyze firm dynamics throughout their life cycle under different tax regimes. Our simulations show that a corporate tax system adjusted by both firm size and age is more effective than one based solely on size (and even more so than a system with a single rate). This approach lightens the tax burden on highly productive young firms and shifts it toward less productive older firms, ultimately boosting employment and welfare without reducing the fiscal surplus
La gestion des catastrophes naturelles : un défi pour les collectivités territoriales
No full texthttps://www.touteconomie.org/node/1987
When and how should an incumbent respond to a potentially disruptive event?
No full textInternational audienceIncumbents can respond to the competitive threat posed by a startup either by external or organic growth. Incumbents may fail do so in due course due to a phenomenon known as “incumbent inertia.” I develop a dynamic model of investment that stresses a new rationale for such inertia. The incumbent may wait even though the option to delay one response is “deep in the money.” This is because the incumbent has to make a choice between several possible responses and is strategically ambivalent about which is best. Such inertia would be bad news for startup valuations if the incumbent delays a lucrative exit for venture capitalists, but good news for consumers if it sustains fiercer competition.<br /
A Diffusion Model-Based Approach to Active Inference
No full textInternational audienceOne of the current challenges in machine learning is the acquisition of generative models to enable decision making in complex, uncertain environments. In Bayesian methods like Active Inference, this requires the estimation of posterior distributions, which is often intractable. Variational Free Energy (VFE) provides a tractable approximation method for this estimation. This paper proposes a novel framework that leverages the expressive power of diffusion models to estimate free energy quickly and efficiently. Our approach, merging concepts from statistical physics, machine learning, and computational neuroscience, aims to improve the estimation of posterior distributions. We establish a theoretical link between active inference and diffusion models, emphasizing their shared strategies for uncertainty management, action selection, and model optimization. We propose using diffusion processes to approximate environmental generative models and employ scorebased guidance for action selection through expected free-energy minimization. Simulations in increasingly complex grid world environments demonstrate the framework's ability to handle partial observability and stochastic transitions, showing enhanced goaldirected behavior and uncertainty resolution compared to traditional methods. This suggests a path toward scalable active inference agents that could reason about uncertainty in real-world contexts, with possible applications to robotics, healthcare, and adaptive control systems
Selective Information Sharing and Group Delusion
No full textAlthough they usually manage to combine information to make well-informed decisions, groups also make mistakes. We investigate experimentally one source of sub-optimal decision-making by groups: the selective and asymmetric sharing of ego-relevant information within teams. We show that good news about one's performance is shared more often with team members than bad news. Asymmetric information sharing combined with the receivers' selection neglect boosts team confidence compared to an unbiased exchange of feedback. Consequently, weaker teams make worse investment decisions in bets whose success depends on the team's ability. The endogenous social exchange of ego-relevant information may foster detrimental group delusion
Public goods and future audiences
No full textInternational audienceIndividuals’ decisions to behave prosocially (or the contrary) can often be observed by other individuals, with no direct connection to them, but who may nevertheless be influenced by them (e.g. through social media). Does knowing that they may be viewed as role models by other, notably younger, people affect the way individuals behave? Does it make them more likely to behave prosocially? We study how participants’ behavior in an experimental public good game is affected when they know that information about their choices and outcomes, together with different sets of information about their identity, will be transmitted the following year to a set of new, unknown, first-year students at the same university. When subjects know their photo, choices and outcomes will be transmitted, they contribute significantly less. We explore different possible explanations and are able to rule out several. We argue that the most convincing are based on non-standard social image concerns (i.e. individuals are not trying to signal prosocial motivations).<br /
Climate change education through the lens of behavioral economics : A systematic review of studies on observed behavior and social norms
No full textInternational audienceWe conduct a systematic review (SR) of the empirical literature on Climate Change Education (CCE) through the lens of behavioral economics. We focus on the effects of educational interventions on actual behaviors or beliefs regarding the prevalence or social acceptability of these behaviors. We identify 86 studies evaluating CCE interventions. Most of them employ pre-post evaluations, which are more susceptible to demand effects and social desirability bias. Almost all report positive effects in terms of pro-environmental outcomes. Only 19 studies look at the effects of CCE on actual behavior (mainly on recycling, trashing or energy saving) or norm-related beliefs. Most interventions involve activities aimed at engaging learners. Others focus on nudges (like stickers or posters). A minority is based on lectures, deliberative discussions, or science-based interactions. The SR reveals important gaps in the literature and potential tensions that can inform future research in behavioral ecological economics.<br /
Incentivizing Exploration With Causal Curiosity as Intrinsic Motivation
No full textInternational audienceReinforcement learning (RL) has shown remarkable success in decision-making tasks but often lacks the ability to decipher and leverage causal relationships in complex environments. This paper introduces a novel "causal model-based reinforcement learning agent" that integrates causal inference with model-based RL to improve exploration and decision-making. Our approach incorporates an intrinsic motivation mechanism based on causal curiosity, quantified by the changes in the agent's internal causal model. We present an algorithm that maintains separate value functions for extrinsic rewards and intrinsic causal discovery, allowing for a balanced exploration of both task-oriented goals and causal structures. Theoretical analysis suggests convergence properties under certain conditions, while empirical results in a blackjack task and structural causal model environments demonstrate improved learning efficiency and strategic decision making compared to standard RL. This work contributes to bridging the gap between reinforcement learning and causal inference
Shockingly Offensive: The Deliberate Use of Slurs in Prosocial Advertising : Can LGBTQIA-Phobic and Sexist Slurs Be Effective for Reshaping Intolerant Attitudes and Behaviors?
No full textInternational audienceVicious discrimination is often experienced by LGBTQIA+ individuals, with the most cited type of discrimination being verbal harassment. This research focuses on the use of negative LGBTQIA-phobic and sexist slurs in social-media marketing advertising. In four experimental studies and two field studies, the authors show that the presence of offensive slurs in social marketing advertisements can provoke shock reactions, leading to higher cognitive elaboration on the target topic. These effects are moderated by social norms and have spillover effects on the intention to change behavior, as well as on the perceived helpfulness of the advertisement. The findings are highly relevant for practitioners seeking to create more poignant prosocial advertisements, but also for researchers who wish to better understand the role of offensiveness in triggering cognitive elaboration.<br /
Natural disasters and voter gratitude: What is the role of prevention policies?
No full textInternational audienceNatural disasters and related prevention policies can affect voter decisions. In this study, we analyze how the occurrence of natural disasters changes voter behavior in municipal elections and how prevention policies can mitigate the impact of such catastrophic events on budget accounts and might potentially be rewarded by citizens in upcoming elections. We exploit original data on French municipalities where incumbents sought re-election between 2008 and 2020. To estimate the probability of re-election at the municipal level in the event of a natural disaster we apply a Heckman model based strategy to avoid selection bias. We find that the occurrence of a natural disaster significantly decreases the chances of re-election of incumbent mayors. However, although we show that natural hazard prevention plans can mitigate the impact of catastrophic events on budget accounts, they are not rewarded by citizens in upcoming elections. The myopia hypothesis is confirmed by our findings: voters reward incumbents for delivering investment spending or decreasing debt but not for investing in disaster preparedness