I am currently working on the following topics:
In this paper, limited attention drives an agent to see the state space as a collection of the events or "small worlds" related to a particular ambience, which we call a state aggregation. This work introduces the model of state aggregation, shows identification of the structure of "small worlds" together with beliefs and utility from the individual demand for assets, and provides comparative statics and revealed preference restrictions.
State Aggregation in Insurance Choices with A. Teperski
Optimizing utility in all states of the world at once might be difficult even for a machine. This paper adds to the behavioral literature by testing models in which the agent aggregates the states together, even though he or she is aware of the entire state space. Different ways of framing objective information may cause agents to aggregate states in predictable ways, which also has a predictable effect on their decisions. Our findings from an experiment suggest the participants respond to the above framing manipulations when asked to choose insurance plans. In addition, the subjects demonstrate event-loving -- the desire to make more similar choices in aggregated states. This finding should not be confused with risk aversion, because such behavior is triggered by the aggregation-inducing frame rather than the natural desire to lower the uncertainty. Our results explain why agencies such as insurance companies use heuristics and the innate confusing nature of contracts to engage consumers in choices that are profitable only for the supplier.
Limited attention and similarity of some of the states of the world together may nudge an agent to perceive the "grand world" as a collection of "small worlds." We use this idea as an explanation for some of the ambiguity paradoxes posed by Machina (2009, 2014) as a challenge to the prominent ambiguity theories.
Comparative Profitability of Product Disclosure Statements with J. Li
We study a model in which an insurance company uses framing of a Product Disclosure Statement (PDS) to influence consumer's choices of insurance plans. PDS represents the structure of the sections that provide the description of the insurance plan's terms and conditions (e.g., "hospital cover," "dental cover," etc.), which is a partition of the state space. Framing of PDS affects how consumers perceive the structure of the problem they face. Our main result concerns the comparison of a PDS with its coarser version. In particular, the firm's profit is greater with a PDS that consists of finer sections for expensive states.
This paper studies how ambiguity affects identification of the state aggregation model -- a model with an agent that combines several states into an event in order to simplify decision-making. We show that the state aggregation is partially identified under Maxmin Expected Utility (MEU) and it is uniquely identified if α-MEU model is used. In addition, we offer testable restrictions of the model.
Identification of Electoral Model and Ballot Stuffing (under revision)
This paper introduces a model of electoral choice that allows for derivation of joint distribution of turnout and voter share from unobservable joint distribution of costs of voting and preferences over candidates. Under a set of mild assumptions, we show non-parametric identification of joint distribution of costs of voting and preferences over candidates from observable data on single elections/referendum. We also offer an extension of the model that helps to identify ballot stuffing type of electoral fraud. In addition, we offer an empirical illustration of the model estimation using 2011 Russian parliamentary election data.