We propose a novel methodology for nonparametric identification of first-price auction models with independent private values, which accommodates auction-specific unobserved heterogeneity and bidder asymmetries, based on recent results from the econometric literature on nonclassical measurement...

This paper (1) presents a general model of online price competition, (2) shows how to structurally estimate the underlying parameters of the model when the number of competing firms is unknown or in dispute, (3) estimates these parameters based on UK data for personal digital assistants, and (4)...

How do people learn? We assess, in a distribution-free manner, subjects' learning and choice rules in dynamic two-armed bandit (probabilistic reversal learning) experiments. To aid in identification and estimation, we use auxiliary measures of subjects' beliefs, in the form of their...

We present a method for estimating Markov dynamic models with unobserved state variables which can be serially correlated over time. We focus on the case where all the model variables have discrete support. Our estimator is simple to compute because it is noniterative, and involves only...