This paper studies the role of observational learning in search markets where buyers do not take the list price as a take-it-or-leave-it offer. Using a unique data from the Beijing housing market, we estimate a structural model in which buyers infer a seller’s reservation value from the...

I propose a flexible non-parametric method using Recurrent Neural Networks (RNN) to estimate a generalized model of expectation formation. This approach does not rely on restrictive assumptions of functional forms and parametric methods yet nests the standard approaches of empirical studies on...

This paper investigates whether aggregate consumer learning together with consumer heterogeneity in price sensitivity could explain why (i) there is a slow diffusion of generic drugs into the market, and (ii) brand-name originators keep increasing their prices over time even after the number of...

Consumers choosing flat-rate contracts tend to have insufficient usage to warrant the cost, particularly for new products. We propose and estimate a Bayesian learning model of tariff and usage choice that explains this "flat-rate bias'' without relying on behavioral misjudgments or...

Information frictions play a central role in the formation of household inflation expectations, but there is no consensus about their origins. We address this question with novel evidence from survey experiments. We document two main findings. First, individuals in lower-inflation contexts have...

This paper revisits the Kareken-Wallace model of exchange rate formation in a two-country overlapping generations world. Following the seminal paper by Arifovic (Journal of Political Economy, 104, 1996, 510-541) we investigate a dynamic version of the model in which agents' decision rules are...

Overbidding in second-price auctions (SPAs) has been shown to be persistent and associated with cognitive ability. We study experimentally to what extent cross-game learning can reduce overbidding in SPAs, taking into account cognitive skills. Employing an order-balanced design, we use...