Aloisio Araujo (Escola Brasileira de Economia e Finanças)
Gold as hedge against markets colapse
Alain Chateauneuf (Paris School of Economics, Université Paris 1)
On the viability of Choquet pricing
Roberto Corrao (Stanford University)
Nonlinear Fixed Points and Stationarity: Economic Applications (co-authored with Simone Cerreia-Vioglio and Giacomo Lanzani)
We consider the fixed points of nonlinear operators that naturally arise in general equilibrium models and games with endogenous networks, in dynamic programming, in models of opinion dynamics with stubborn agents, and in financial networks. We study limit cases that correspond to high-coordination motives, infinite patience, vanishing stubbornness, and small exposure to the real sector in the applications above. Under monotonicity and continuity assumptions, we provide explicit expressions for the limit fixed points. We show that, under differentiability, the limit fixed point is linear in the initial conditions and characterized by the Jacobian of the operator at any constant vector with an explicit and linear rate of convergence. Without differentiability, but under additional concavity properties, the multiplicity of Jacobians is resolved by a representation of the limit fixed point as a maxmin functional evaluated at the initial conditions. In our applications, we use these results to identify the most GDP damaging sector-specific productivity shocks, to do optimal targeting with endogenous networks, to show the existence and give the formula of the asymptotic value in a class of zero-sum stochastic games with a continuum of actions, to compute a nonlinear version of the eigenvector centrality of agents in networks, to show for what preferences high patience mutes uncertainty aversion, and to identify the risk measures that provide robustness in highly interconnected financial networks.
Pawel Dziewulski (University of Sussex)
On pure altruism (co-authored with Łukasz Woźny)
We revisit the notion of pure altruism and propose a general framework for studying altruistic behaviour across a wide range of economic settings. In our approach, an agent (the parent) is represented by a function that maps the preferences of those they interact with (the descendant) into their own preferences. This representation captures how the parent’s objectives adjust in response to the preferences of others, thereby providing a flexible formalisation of altruistic attitudes. Within this framework, we introduce a natural and robust notion of comparative altruism: one parent is said to be more altruistic than another if, for any possible preferences of the descendant, the former’s choices are always (weakly) preferred by the descendant to the latter’s choices. We characterise this ordering and demonstrate its implications in economic applications. In particular, we show that in problems of charitable giving, under minimal assumptions, a more altruistic parent donates more to the descendant.
Itzhak Gilboa (HEC Paris)
Imagination and Planning (co-authored with Gabrielle Gayer)
We consider a model of case-based planning, where a position is a vector of numbers, and a case is an edge in the directed graph of positions. The planner generates new plans by using cases that are similar to those she has observed in the past. In the benchmark model presented here, similarity is defined by equality of differences (between the target and the source position). We prove a complexity result that shows why planning requires imagination and is not easily done algorithmically. We put this result in the context of learning and expertise in case-based models, distinguishing among information, insight, and imagination.
Michael Greinecker (École Normale Supérieure Paris-Saclay)
Sequential Equilibria in a Class of Infinite Extensive Form Games (co-authored with Martin Meier and Konrad Podczeck)
Sequential equilibrium is one of the most fundamental refinements of Nash equilibrium for games in extensive form but is not defined for extensive-form games in which a player can choose among a continuum of actions. We define a class of infinite extensive form games in which information behaves continuously as a function of past actions and define a natural notion of sequential equilibrium for this class. Sequential equilibria exist in this class and refine Nash equilibria. In standard finite extensive-form games, our definition selects the same strategy profiles as the traditional notion of sequential equilibrium.
Ani Guerdjikova (University of Grenoble Alpes)
How Do You Know What I Mean? Implication and Translation (co-authored with John Quiggin)
When agents entertain distinct perceptions of the word, communication between them will be imprecise. In particular, under differential awareness, an event as described by one agent may find no exact analog in another agent’s subjective understanding. Within this context, it is natural to consider a syntactic model where the agent’s understanding of the world is embodied by a language (i.e., a set of interconnected descriptions of the world). Communication between agents can therefore be understood as a process of translating statements from one language to another. This paper asks how such a translation might arise and how it might be identified by an observer. We show that even if translation between languages is consistent, i.e., preserves logical implications, it need not imply the existence of a joint state-space that embeds the individual models of the two agents. We expose why this failure occurs and provide an axiom that ensures the existence of a joint state spaces which embeds the individual state-spaces.
Takashi Hayashi (University of Glasgow, Adam Smith business school)
Implementation in Stationary Markov-Perfect Equilibrium (co-authored with Michele Lombardi)
We consider that society cannot just run a static mechanism only once in the initial period and then commit to its solution as an intertemporal plan, even under complete information among agents about their permanent types. We study the implementation of society's policy functions in stationary Markov-perfect equilibrium. We identify a monotonicity condition, a natural but nontrivial stationary recursive extension of Maskin monotonicity. We show that our condition is necessary and also sufficient under a mild regularity condition. We apply our result to a recursive market equilibrium solution for intertemporal trades and the recursive median voter solution for public capital accumulation.
Brian Hill (HEC Paris)
Confidence, consensus and aggregation
This paper develops and defends a new approach to belief aggregation, involving confidence in beliefs. It is axiomatically characterised by a variant of the Pareto condition that enjoins respecting consensuses borne of compromise. Confidence aggregation generalises standard probability aggregation rules—such as linear pooling—whilst avoiding the spurious unanimity issues that have plagued them. It generates the first family of probability aggregation rules that can faithfully accommodate within-person expertise diversity, hence resolving a longstanding challenge. It is dynamically rational, insofar as it commutes with update. Finally, it recovers as special cases both Bayesian and non-Bayesian approaches to model misspecification.
En Hua Hu (Nuffield College, Oxford)
Decision-makers often use procedures to evaluate risky prospects. This paper focuses on the procedure of merging separate outcomes. I offer a procedural foundation for expected utility and models of rank-dependence, betweenness, and complexity aversion. Expected utility is characterized by uniformity and costlessness of the procedure across prospects. Relaxing uniformity characterizes rank-dependence, betweenness, while relaxing costlessness characterizes complexity aversion with support-size and entropy costs.
Ali Khan (Johns Hopkins University)
Keynesian Beauty Contests with Heterogeneous Agents (co-authored with Haomiao Yu and Zhixiang Zhang)
Peter Klibanoff (Kellogg School of Management )
Robust contracting and voluntary disclosure (co-authored with Eran Hanany)
This paper analyzes contracting between a principal and an agent when the principal is uncertain exactly which actions may be feasible for the agent and has a strong desire for robustness (in the worst-case or maxmin sense) of the expected profits generated. A prominent and path-breaking paper in this direction is Carroll (2015), which demonstrates that linear contracts are robustly (worst-case) optimal given uncertainty about an agent’s available actions. What if, when it is in their interest, the agent could choose to disclose that they have access to a particular additional action, and such statements could be verified by the principal? Does this change the form of robustly optimal contracts offered to an agent who either chooses not to disclose or has no additional action to disclose? Are such contracts still linear? We show that the possibility of voluntary disclosure can substantially change the form of robustly optimal contracts. In particular, we show the possibility of and provide sufficient conditions for equilibrium contracts offered following non-disclosure to be non-linear. This equilibrium non-linearity does not always occur. We show that linearity results when there are few publicly-known-to-be-available actions that generate a positive surplus.
Fabio Maccheroni (Università Bocconi)
Disappointment Aversion and Expectiles (co-authored with Fabio Bellini, Tiantian Mao, Ruodu Wang, and Qinyu Wu)
This paper recasts Gul (1991)'s theory of disappointment aversion in a Savage framework, with general outcomes, new explicit axioms of disappointment aversion, and novel explicit representations. These permit broader applications of the theory and better understanding of its decision-theoretic foundations. Our results exploit an unexpected connection of Gul's theory and the econometric framework of Newey and Powell (1987) of asymmetric least square estimation.
Alfonso Maselli (University of Pennsylvania)
Misspecification Averse Preferences
We study a decision maker who approaches a decision problem under uncertainty by formulating a set of plausible probabilistic models of the environment, while being aware that these models are only stylized and incomplete approximations. The decision maker faces two layers of uncertainty. Not only is she uncertain about which model in this set has the best fit (ambiguity), but she is also concerned that the best-fit model itself might be a poor description of the environment (model misspecification). We develop an axiomatic foundation for preferences that capture concerns about these two layers of uncertainty and allow us to compare individuals' degrees of aversion to model misspecification and to ambiguity independently of each other. In other words, these two conceptually distinct behavioral phenomena are captured by independent parameters in our representation and imply different choice patterns.
Illia Pasichnichenko (University of Sussex)
Value of Partial Information (co-authored with Jürgen Eichberger)
Blackwell’s theorem relates the value of information to the “informativeness” of the information structure. His analysis applies to decision makers who are expected utility maximizers and know the information structure of the decision problem. When decision makers do not know the information structure precisely, the signal generating process and the posterior distributions are often only partially known. This paper studies preferences of decision makers with partial knowledge about signals and posterior probability distributions. The partial information approach allows us to relate the value of information to the decision maker’s attitude towards ambiguity. We introduce a new concept of informativeness based on the centroid and prove a theorem in the spirit of Blackwell. Depending on ambiguity attitude the value of information may be negative.
Evan Piermont (Royal Holloway, University of London)
Unintended Consequences: Updating Causal Models (co-authored with Joe Halpern and Marie-Louise Vierø)
We propose a model of belief updating within the context of structural causal models. In particular, an agent entertains a probabilistic belief about the causal relationship between different variables, and observes the outcome of interventions on those variables. The agent updates her belief in the face of these observations. When the agent's initial beliefs are consistent with what she observes, this updating is standard; however, when her beliefs are unable to explain what she observes, the agent must expand or otherwise alter the causal relationships she considers. We employ this model in a exploration/exploration framework whereby the agent can directly choose the interventions she observes. We analyze when the agent's beliefs converge on the true causal structure.
Luciano Pomatto (California Institut of Technology)
Modeling information acquisition via f-divergence and duality (co-authored with Alexander Boeldel and Tommaso Denti)
We introduce a new cost function over experiments, f-information, based on the theory of multivariate statistical divergences, that generalizes Sims’s classic model of rational inattention as well as the class of posterior-separable cost functions. We characterize its behavioral predictions by deriving optimality conditions that extend those of Matějka and McKay (2015) and Caplin, Dean, and Leahy (2019) beyond mutual information. Using these tools, we study the implications of f-information in a number of canonical decision problems. A strength of the framework is that it can be analyzed using familiar methods of microeconomics: convex duality and the Arrow-Pratt approach to expected utility.
John Quah (National University of Singapore)
The Median Voter and Sincere Voting (co-authored with Gregorio Curello and Bruno Strulovici)
It is well-known that in a setting where voters have single peaked preferences over alternatives defined on a one-dimensional space, the median voter’s preference is decisive. However, in many plausible environments, voters decide among alternatives with multi-dimensional characteristics. We generalize the notion of a median voter to such multi-dimensional settings and show that under a natural multi-stage voting protocol, the median voter’s preferred alternative is also the eventual outcome of the vote. Furthermore, this outcome is robust to whether agents vote sincerely, strategically, or switch between these decision rules.
Alyssa Rusonik (HEC Paris)
The Evolving Credibility of Stories
In this project, I develop a framework for studying narratives. I propose a novel methodology which leverages LLM capabilities to extract individual stories from a corpus of texts, creating a database of stories. Stories are compared, via a notion of semantic similarity which respects story-structure, and then agglomerated into narratives. Preliminary results attesting to the capabilities of the methodology in the context of inflation-related narratives will be furnished, along with proposed directions for future research. Accompanying theoretical conjectures, and the empirical hypotheses they generate, will also be discussed.
Norio Takeoka (Hitotsubashi University)
A Dynamic Theory of Preference for Flexibility
We consider an agent who faces dynamic decision problems and anticipates nonstationary and persistent shocks to risk and time preferences. Taking a preference for infinite-horizon consumption problems as a primitive, we introduce a recursive utility representation that captures the agent's preference for flexibility. In the representation, the agent's anticipation of preference shocks is modeled as an infinite higher-order belief. The characterization of this representation is based on axioms that reflect the agent's anticipation about future preferences in terms of attitudes toward flexibility and intertemporal trade-offs. While the belief in this representation is not uniquely determined in general, it becomes generically unique under a normalization of consumption utilities. Furthermore, the belief remains invariant under a common scaling of consumption utilities.
Marie-Louise Vierø (Aarhus University)
Measurements of Attitudes toward Unawareness (co-authored with Edi Karni)
Decisions under uncertainty may result in new, unanticipated, consequences. Decision makers may be aware of being unaware of possible consequences of their decisions and take it into account when choosing among alternative courses of action. Decision makers' attitudes toward encountering unanticipated consequences is reflected in their choice behavior. This paper proposes, for the first time, measures of the attitudes toward unawareness, thereby filling a lacuna in the literature on decision making under uncertainty and awareness of unawareness.
Mu Zhang (University of Michigan)
Preferences for Risk, Intertemporal Substitution, and Temporal Resolution of Risk (co-authored with Shaowei Ke)
We show that an unintended consequence of the independence and recursivity axioms in dynamic settings is that preferences for risk and intertemporal substitution fully determine the preference for temporal resolution of risk. We relax these axioms and characterize a utility representation that combines Kreps and Porteus (1978) with a function capturing what the decision maker learns about the future from present risk resolution. We analyze its properties and show how to apply it to dynamic optimization problems. As an example, we revisit the equity premium puzzle, showing that our model helps resolve it, while maintaining a reasonably low timing premium.