Research papers

Below each economics paper you can find keywords describing its topic.
My math research appears at the bottom of this page.

In Economics: 

Bargaining with Endogenous Learning (job market paper)
[download pdf] [online appendix]
Keywords: dynamic bargaining, learning, endogenous information search, endogenous exploitation, strategic option value

Abstract

​I study a dynamic bargaining game in which a buyer can choose to learn privately about her valuation of the good. Information generation takes time and is endogenous. After learning, the buyer can disclose verifiable evidence of her valuation to the seller. Examples include venture capital negotiations or procurement of new technologies, which feature significant delay due to endogenous costly learning. If learning is costless, the buyer receives informational rents only if period-length is small enough. If learning is costly, she receives informational rents for any period-length. In stationary equilibria with mixed pricing the buyer waits until she can acquire the information and exercise the associated strategic option. Nevertheless, there are stationary equilibria with pure pricing that feature vanishing delay and payoffs close to efficiency, even if learning is costly. If period-length is small enough, all stationary equilibria feature non-extreme prices and payoffs. The analysis quantifies the potential inefficiency from costly learning, from the endogenous delay and allows for comparative statics.

 

Dynamic Information Design with Diminishing Sensitivity over News (with Kevin He)
[download pdf]
Keywords: information design, diminishing sensitivity, non-instrumental information, cheap talk

Abstract

A benevolent sender communicates non-instrumental information over time to a Bayesian receiver who experiences gain-loss utility over changes in beliefs (“news utility”). We show how to compute the optimal dynamic information structure for arbitrary news-utility functions. With diminishing sensitivity over the magnitude of news, one-shot resolution of uncertainty is strictly suboptimal under commonly used functional forms. Information structures that deliver bad news gradually are never optimal. We identify additional conditions that imply the sender optimally releases good news in small pieces but bad news in one clump. When the sender lacks commitment power, diminishing sensitivity leads to a credibility problem for good-news messages. Without loss aversion, the babbling equilibrium is essentially unique. More loss-averse receivers may enjoy higher equilibrium news-utility, contrary to the commitment case. We discuss applications to media competition and game shows.

 

Identification and Welfare Analysis in Sequential Sampling Models (with Yi-Hsuan Lin)
[download pdf]
Keywords: sequential sampling, stochastic choice, identification, welfare

Abstract

Consider an agent or a population of homogeneous agents who privately learn information about a payoff-relevant uncertain state of the world through a technology of sequential experiments. We consider two distinct cases of costly experimentation. In the first case, the agents discount future payoffs geometrically. In the second, they pay a constant flow cost of time. Suppose the analyst observes the joint distribution over chosen action and decision time. We show that such random choice data uniquely identify the discount factor in the first case and the cost of time in the second case, besides identifying the agents’ prior and taste. Moreover, we show how an outside observer with access to this random choice data can conduct welfare analysis despite being oblivious of the technology of sequential experiments the agents are using. Our results highlight the usefulness of decision time in choice data.

 

Optimal Stopping with General Risk Preferences
revise and resubmit at Mathematics of Operations Research
[download pdf]
Keywords: optimal stopping, risk preferences, naive, sophisticated, diffusions

Abstract

We give a full characterization of the continuation and stopping regions of optimal stopping of (time-homogeneous) diffusions for an agent with a general risk preference. We consider separately the case of a naive agent who is unaware of the possible time inconsistency in her behavior and the case of a sophisticated agent who is fully aware of such an inconsistency. We apply our general results to characterize optimal stopping behavior among several distinct classes of non-Expected Utility risk preference models. We also show that although some specific models related to probability weighting may exhibit extreme behavior in the sense of naive agents always continuing with positive probability or sophisticated agents never starting, many other risk preference models do not lead to such extreme behavior.

 

Mechanism Design with News Utility
[download pdf] [online appendix]
Keywords: Bayesian mechanism design, news utility, dynamic inconsistency, auctions

Abstract

An agent with news utility cares about changes in her beliefs over consumption and money. We study the implications of news utility and loss aversion for the design of Bayesian mechanisms, in both one-agent and multi-agent settings. News utility leads to dynamic inconsistency, thus introducing a novel design variable available for the designer: the timeline of the implementation of the mechanism. We give general results about the optimal design of the timeline, in addition to illustrating how news utility changes other well-known classical results from the theory of Bayesian mechanism design.

 

Costly Information and Random Choice (with Yi-Hsuan Lin)
[download pdf] [supplementary material]
Keywords: stochastic choice, information acquisition, impatience

Abstract

Consider an agent who decides whether to employ an information structure to learn about a payoff-relevant state of the world before making a decision. Information is costly either because (1) the agent has to wait a fixed amount of time for the availability of the information structure and is impatient, or because (2) she has to pay a fixed and menu-independent cost to use the information structure. For each menu of options the analyst observes random choice from the menu and whether the agent acquires the information. We give an axiomatic characterization of when this random choice is consistent with either of the cases (1) or (2) and show how the analyst can identify the information structure the agent can employ, and respectively, discount factor or additive costs.

 

Dynamic Random Subjective Expected Utility
[download pdf] [online appendix]
Keywords: stochastic choice, subjective expected utility, misspecified learning, dynamic models of behavior

Abstract

Dynamic Random Subjective Expected Utility (DR-SEU) allows to model choice data observed from an agent or a population of agents whose tastes and beliefs about objective payoff-relevant states can evolve stochastically. Our observable, the augmented Stochastic Choice Function (aSCF), allows for a direct test of whether the agents' beliefs reflect the true data-generating process conditional on their private information as well as identification of the possibly incorrect beliefs. We give an axiomatic characterization of when an agent satisfies the model, both in static and dynamic settings. We also prove natural comparative static results on the degree of belief incorrectness as well as on the speed of learning about taste.

 

Static and Dynamic Consistency of Preferences in Optimal Stopping Problems
[download pdf]
Keywords: dynamic consistency axiom, expected utility, continuous time

Abstract

Suppose an agent with a static risk preference faces prize processes given by regular diffusions and decides when to stop the process and consume the prize. We show that the agent satisfies dynamic consistency of preferences if and only if she is an Expected Utility agent. This extends a classical result from [Hammond (1988)] and [Gul, Lantto (1990)] to a continuous-time setup in which the classical proof techniques do not apply, because the `decision trees' the agent faces are not the usual discrete-time, finite-horizon lottery trees. 

 

In Mathematics: 

Math Ph.D. abstract

Green Function of a Random Walk in a Cone (with Vitali Wachtel)
[arxiv]

Invariance Principles for Random Walks in Cones (with Vitali Wachtel)
accepted for publication at Stochastic Processes and their Applications
[arxiv]

Random Walks in Cones: the Case of Non-zero Drift
Stochastic Processes and their Applications, 124(4), 1503-1518, April 2014

On Harmonic Functions of Killed Random Walks in Convex Cones
Electronic Communications in Probability, 19, paper no. 80, 1-10