I am currently working on the following topics:
Framing and Insurance Choices with A. Teperski and K. Atalay - revise and resubmit at Journal of Risk and Insurance
How objective information is presented should not affect a rational decision-maker; however, in practice, it often does. This paper studies the impact of the framing of contingencies on insurance choices. We presented two groups of lab participants with differently framed insurance tasks. The treatment group received the description of the insurance plan with the states bundled, whereas the control group received the description of the states separately. We discover that the distribution of the insurance premium paid was identical in both groups, likely a result of mental accounting. However, the actual choices of the insurance plans were significantly diverse: On average, the treatment group bought more similar amounts of insurance in each of the framed states than did the control group.
In insurance industry, product disclosure statements (PDSs) consist of descriptions of uncertain contingencies by the insurance plans (e.g.,"hospital coverage", "dental coverage", etc.) and are often very different. In this paper, we model PDSs as information partitions of the state space, which can influence how a consumer perceives the structure of her choice problem and hence her deductible choices. We study a model of an insurance company that aims to promote profit by designing the framing of its PDS. We compare the company's profits under two PDSs, one of which is coarser than the other. Our main results show that under simple conditions, the PDS consisting of finer partitions of the more expensive states is more profitable.
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.
This paper introduces a structural model of electoral choice and ballot stuffing that allows for derivation of the joint distribution of turnout and voter share from the unobservable joint distribution of the costs of voting and preferences over candidates. We assume availability of a "clean" subset of data that provides us with the following results: if political preferences are heterogenous across the country, we are able to identify the density of ballot stuffing at any polling station of interest. If political preferences are rather homogenous, we are able to identify the bounds on average ballot stuffing. We also provide corresponding semi-parametric estimators, which are based on kernel density estimation. In addition, this paper offers an empirical illustration of the model estimation using the 2011 Russia parliamentary election data.