Assistant Professor, Indian Statistical Institute, Delhi
Primary Research Interests: Rational Inattention, Game Theory, Political & Development Economics
Assistant Professor, Indian Statistical Institute, Delhi
Primary Research Interests: Rational Inattention, Game Theory, Political & Development Economics
Procuring Unverifiable Information (with Elias Tsakas & Mark Voorneveld). Mathematics of Operations Research (2025)
We study settings where information in the form of Bayesian signals is acquired by an expert on behalf of a principal. Information acquisition is costly for the expert, and crucially not verifiable by the principal. The expert is compensated by the principal with a menu of state-contingent payments. We provide a full characterization of the set of all menus that implement (resp., strictly implement) each signal. Moreover, we provide a closed-form characterization for the expected cost for the cheapest such menu, which we call proxy cost of the signal. Surprisingly, in general, the proxy cost is neither increasing in the Blackwell order, nor posterior-separable, even when the expert’s cost function is posterior-separable itself. Subsequently, we study the full agency problem (by introducing a downstream decision), thus endogenizing the signal. We show that there is always an optimal signal that can be strictly implemented, meaning that it is without loss of generality to exogenously restrict attention to strict implementation. As a result, similarly to Bayesian persuasion, the complexity of the principal’s optimal signal is bounded by the cardinality of the state space. Finally, we present some applications of interest.
Sequential Search with Flexible Information (with Pavel Ilinov, Andrei Matveenko, Elias Tsakas & Mark Voorneveld)
We consider a model of sequential search in which an agent (the employer) has to choose one alternative (a candidate) from a finite set. A key feature of our model is that the employer is not restricted to specific forms of information acquisition, i.e., she is free to endogenously choose any interview for each candidate that arrives. Our main characterization result shows that the employer's unique optimal strategy is to offer a gradually easier interview to later candidates. Remarkably, even if the number of candidates grows arbitrarily large, the probability of hiring a good candidate is bounded away from 1. Then, we show that only in some extreme pathological cases the candidates are treated equally in terms of the total probability of being hired; in fact, in most settings of applied interest, the first candidate seems to be favored. Finally, if we characterize a wide range of cases where the employer prefers to start by interviewing ex ante worse candidates.
Designing Efficient Public Good Contribution Game: An Institutional Edits Approach (with Leonard Wantchekon & Mark Voorneveld)
What is the effect of deliberation on public goods contributions? We consider a multiple public goods contribution game where players have different preferences over the set of public goods. We assume that deliberation allows players to express their opinions to others and form groups before making their contribution. A group allows the players to pool their preferences and contributions. Imposing a stability condition on the groups, we consider the set of Nash equilibria of this game and find that many inefficient equilibria (such as no contribution) of the underlying game are removed through such a process. Our work rationalizes the findings of work in political and development economics (López‐Moctezuma, Gabriel, et al.) and psychology (Kragt, et al.)
Learning from Experiments: Information Acquisition and Agency (with Leonard Wantchekon & Mark Voorneveld)
We consider the problem of deciding to adopt a policy if evidence exists from another environment. We assume that evidence is characterized by two independent dimensions. The first dimension represents the heterogeneity in payoffs when conditions for the policy to succeed are met. The second dimension determines the heterogeneity in payoffs that arises because of different contexts. The decision maker is rationally inattentive and investigates the two dimensions sequentially. We first provide relationships between the beliefs about the first dimension and the information acquisition in the second dimension. We then show how the information acquisition strategy changes when the sensitivity of the payoffs with respect to the second dimension changes. Finally, we provide conditions under which the DM chooses to acquire information about the first dimension alone.
Rational Inattention and Search with Recall (with Pavel Ilinov, Andrei Matveenko, Elias Tsakas & Mark Voorneveld)
Distorted Beliefs, Pluralistic Ignorance, and Social Norms Persistence: an Application to Chhaupadi in Nepal (with Cristina Clerici)
We study how the high symbolic value associated with certain social norms induces individuals to hold distorted beliefs resulting in pluralistic ignorance and norms' persistence. The literature on social identity often assumes or derives conditions for conformity in behavior: individuals derive utility by minimizing the distance between their own compliance to a social norm and the average compliance of their respective group members. The underlying assumption is that, in expectation, individuals have a correct assessment of the average compliance. We assume that individuals also ascribe a symbolic value to the norm, and we allow endogenous noise in the agents' perceptions about others' actions. We show that this modification results in individuals exhibiting pluralistic ignorance, the phenomenon whereby they systematically make mistakes about the true average compliance level. We then examine the consequences that some policy prescriptions, such as fines/subsidies and availability of information, have on norms’ persistence. We apply the model to chhaupadi, a harmful menstruation-related practice in Nepal.
Information Design in Manipulable Interviews (with Pervesh Anthwal & Ankush Garg)
We study a game of information design in the context of an interview. A designer chooses a state-dependent information structure (a question), a sender manipulates the signal probabilities (by framing arguments), and a receiver who is naive and only observes the designer's information structure but not the manipulation. We characterize the equilibrium of this game and show that if an informative question is optimal, then it is fully informative. The beliefs of the designer, however, may remain bounded away from certainty because of manipulation.