We investigate the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem which can be solved using state-of-the-art constrained optimization solvers. Under the assumption that...

We investigate the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem that can be solved using state-of-the-art constrained optimization solvers. Under the assumption that...

The authors examine prominent placement of search engines’ own services and effects on users’ choices. Evaluating a natural experiment in which different results were shown to users who performed similar searches, they find that Google’s prominent placement of its Flight Search service...

This paper offers new empirical evidence about actual Airbnb usage patterns and how they vary across neighborhoods in New York City. We combine unique, census-tract level data from Airbnb with neighborhood asking rent data from Zillow and administrative, census, and social media data on...

We study manipulability of stable matching mechanisms and show that manipulability comparisons are equivalent to preference comparisons: for any agent, a mechanism is more manipulable than another if and only if this agent prefers the latter to the former. In particular, this implies that no two...