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Estimating dynamic games of oligopolistic competition: an experimental investigation
Author(s) -
Salz Tobias,
Vespa Emanuel
Publication year - 2020
Publication title -
the rand journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.687
H-Index - 108
eISSN - 1756-2171
pISSN - 0741-6261
DOI - 10.1111/1756-2171.12321
Subject(s) - counterfactual conditional , collusion , counterfactual thinking , oligopoly , markov chain , markov perfect equilibrium , econometrics , economics , structural estimation , competition (biology) , computer science , mathematical economics , cournot competition , microeconomics , nash equilibrium , ecology , philosophy , epistemology , machine learning , biology
We evaluate standard assumptions in the estimation of dynamic oligopoly models with laboratory data. Using an entry/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov‐perfect equilibrium and subsequently predict counterfactual behavior. If behavior was collusive, however, the assumption would be violated and one would mispredict counterfactuals. The laboratory allows us to compare predicted behavior to true counterfactuals implemented as treatments. Our main finding is that prediction errors due to collusion are modest in size. We also document a different deviation from equilibrium behavior (inertia) that can lead to large prediction errors.