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WORKING PAPERS





Unrealistic Expectations and Misguided LearningAbstract:

We explore the learning process and behavior of an individual with unrealistically high expectations about ability ("overconfidence") when outcomes also depend on an external fundamental that affects the optimal action. Moving beyond existing results in the literature, we show that the agent's belief regarding the fundamental converges under weak conditions. Furthermore, we identify a broad class of situations in which "learning" about the fundamental is self-defeating: it leads the individual systematically away from the correct belief and toward lower performance. Due to her overconfidence, the agent -- even if initially correct -- becomes too pessimistic about the fundamental. As she adjusts her behavior in response, she lowers outcomes and hence becomes even more pessimistic about the fundamental, perpetuating the misdirected learning. The greater is the loss from choosing a suboptimal action, the further the agent's action ends up from optimal. We argue that the decision situations in question are common in economic settings, including delegation, organizational, public-policy, and labor-leisure choices. We partially characterize environments in which self-defeating learning occurs, and show that the decisionmaker is indistinguishable from a rational agent if, and in some cases only if, a specific non-identifiability condition is satisfied. In contrast to an overconfident agent, an underconfident agent's misdirected learning is self-limiting and therefore not very harmful.


Joint with Paul Heidhues and Philipp Strack. Updated January 2016.





Cursed Financial InnovationAbstract:

We analyze the welfare properties of derivative securities that profit-maximizing issuers offer to investors who have inferior information and neglect the information content of the offer. To capture the markets for structured securities and exotic exchange-traded funds, we assume that issuers can choose both the underlying asset and the form of the security. An issuer's optimal security induces investors to bet on unlikely market movements, creating both excess risk taking and undersaving. Giving more information to the issuer leads it to choose an underlying asset on which its information is more extreme, exacerbating both effects and hence lowering social welfare. Furthermore, providing inferior and noisy additional information to investors also lowers welfare because the security is then written on an underlying asset about which the information is misleading. If the issuer can base its security on a combination of underlying assets, it optimally creates a "custom-designed" index to maximize its informational advantage and minimize risk, minimizing investor and social welfare. Restricting the set of underlying assets -- a kind of standardization -- increases welfare by preventing the issuer from systematically selling a security with extreme or misleading information. Once this policy is adopted, increasing investor information becomes beneficial.


Joint with Péter Kondor. Updated August 2015.





Naivete-Based DiscriminationAbstract:

We study the welfare effects of naivete-based discrimination, the practice of conditioning offers on external information about consumers' naivete. Using a simple reduced-form model, we delineate three qualitatively distinct cases based on the "distortionary impact" of naivete -- the extent to which the exploitation of naive consumers distorts trades with different types of consumers. If the distortionary impact is homogenous across naive and sophisticated consumers, then under an arguably weak and empirically testable condition, naivete-based discrimination lowers total welfare. In contrast, if the distortionary impact arises only for trades with sophisticated consumers, then perfect naivete-based discrimination maximizes social welfare, although imperfect discrimination often lowers welfare. And if the distortionary impact arises only for trades with naive consumers, then naivete-based discrimination has no effect on welfare. We identify applications for each of these cases. In our primary example, a credit market with present-biased borrowers, firms lend more than socially optimal to increase the amount of interest naive borrowers unexpectedly pay, creating a homogenous distortion. The condition for naivete-based discrimination to lower welfare is then weaker than prudence. We discuss how to combine our results with empirical findings to determine whether naivete-based discrimination is welfare-decreasing in other settings.


Joint with Paul Heidhues. Updated October 2015.