Papers Submitted
Abstract:
We discuss the identification and estimation
of discrete games of complete information.
Following Bresnahan and Reiss (1990, 1991), a
discrete game is a generalization of a
standard discrete choice model where utility
depends on the actions of other players.
Using recent algorithms to compute all
of the Nash equilibria to a game, we propose
simulation-based estimators for static,
discrete games. With appropriate exclusion
restrictions about how covariates enter into
payoffs and influence equilibrium selection,
the model is identified with only weak
parametric assumptions. Monte Carlo evidence
demonstrates that the estimator can perform
well in moderately-sized samples. As an
application, we study the strategic decision
of firms in spatially-separated markets to
establish a presence on the Internet.