Chantal Marlats

I am an assistant professor (maitre de conférences) in economics at Université Panthéon-Assas, Paris II and a researcher fellow at LEMMA.

Since 2022,  I am a junior member at IUF.

My research focuses on dynamic game theory and its applications on R&D and epidemiology. 

 Email: chantal dot marlats at u-paris2 dot fr




Dynamic game theory, learning, epidemiological economics


This paper studies the dynamics of effort provision in teams when there are exogenous observation delays between partners. Agents are engaged in a common project whose duration is uncertain and yields no benefit until one of the agents has completed it. All it takes to complete the project is one success, which can be obtained after the investment of costly effort. An agent learns immediately when he succeeds, but learns whether his partners completed the project only after some exogenous delay. The main insight of the paper is that observation delays induce cyclical effort dynamics in equilibrium: Players alternate between periods in which they exert the maximal effort level and periods in which they make no effort at all. The size of the team has a negative impact on the average equilibrium effort, but a positive one on the players' payoff. Finally, introducing a small observation delay increases the average effort of patient players and makes them complete the project faster in expectation.

We introduce strategic observation into Keller, Rady and Cripps (2005)'s game of experimentation with conclusive breakthroughs. There are two players who must decide when to start and when to stop observation, given that observation is costly and stopping observation is irreversible. We construct a class of symmetric Markov Perfect Equilibria in which, on path, players fully experiment before starting observation, and allocate only a fraction of the resource to the risky arm afterwards. Each 

We analyze the spread of an infectious disease in a population when individuals strategically choose how much time to interact with others. Individuals are either of the severe type or of the asymptomatic type. Only severe types have symptoms when they are infected, and the asymptomatic types can be contagious without knowing it. In the absence of any symptoms, individuals do not know their type and continuously tradeoff the costs and benefits of self-isolation on the basis of their belief of being the severe type. We show that all equilibria of the game involve social interaction, and we characterize the unique equilibrium in which individuals partially self-isolate at each date. We calibrate our model to the COVID-19 pandemic and simulate the dynamics of the epidemic to illustrate the impact of some public policies.

This paper extends the reputation result of Evans and Thomas (Econometrica 65(5):1153–1173, 1997) to stochastic games. Specifically, I analyze reputation effects with two long-lived (but not equally long) players in stochastic games, that is, in games in which the payoffs depend on a state variable and the law of motion for states is a function of the current state and of the players’ actions. The results suggest that reputation effects in stochastic games can be expected if the uninformed player has a weak control of the law motion or if there is no irreversibility. On the contrary, in economic situations with irreversibility and in which the uninformed player’s strong control of the transition, such as the hold-up problems, reputation effects are unlikely to be obtained.

This paper explores the robustness of predictions made in long but finitely repeated games. The robustness approach used in this paper is related to the idea that a modeler may not have absolute faith in his model: The payoff matrix may not remain the same at all dates and may vary temporarily from time to time with an arbitrarily small probability. Therefore, he may require not rejecting an outcome if it is an equilibrium in some game arbitrarily close to the original one. It is shown that the set of feasible and rational payoffs is the (essentially) unique robust equilibrium payoff set when the horizon is sufficiently large. Consequently, cooperation can arise as an equilibrium behavior in a game arbitrarily close to the standard prisoner’s dilemma if the horizon is finite but sufficiently long.

This paper provides assumptions for a limit Folk theorem in stochastic games with finite horizon. In addition to the asymptotic assumptions à la Dutta (J Econ Theory 66:1–32, 1995 ) I present an additional assumption under which the Folk theorem holds in stochastic games when the horizon is long but finite. This assumption says that the limit set of SPE payoffs contains a state invariant payoff vector $w$ and, for each player $i$, another payoff vector that gives less than $w$ to $i$. I present two alternative assumptions, one on a finite truncation of the stochastic game and the other on stage games and on the transition function, that imply this assumption

Working papers

We analyze an epidemiological model in which individuals trade the costs and benefits of social distancing while being uncertain about the dynamics of the epidemic. We characterize the unique symmetric equilibrium and show that uncertainty can be the cause of an additional wave of infections. We calibrate our model to the COVID-19 pandemic and simulate the dynamics of the epidemic to illustrate the impact of uncertainty on social distancing. We show that uncertainty about the epidemic dynamics may be welfare improving, both in terms of fraction of deaths and average payoffs.  

 We analyze a dynamic investment model in which short-lived agents sequentially decide how much to invest in a project of uncertain feasibility. The outcome of the project (success/failure) is observed after a fixed lag. We characterize the unique equilibrium and show that, in contrast with the case without lag, the unique equilibrium dynamics is not in thresholds. If the initial belief is relatively high, investment decreases monotonically as agents become more pessimistic about the feasibility of the innovation. Otherwise, investment is not monotone in the public belief: players alternate periods of no investment and periods of positive, decreasing investment. The reason is that the outcome lag creates competition between a player and her immediate predecessors. A player whose predecessors did not invest may find investment attractive even if she is more pessimistic about the technology than her predecessors. We compare the total investment obtained in this equilibrium with that obtained with an alternative reward scheme where a mediator collects all the information about the players' experiences until some deadline, and splits the payoff between all the players who obtained a success before the deadline.