Emanuel Vespa

2127 North Hall
University of California
Santa Barbara, CA 93106

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
Institutional Affiliation: University of California at Santa Barbara

NBER Working Papers and Publications

February 2020Estimating Dynamic Games of Oligopolistic Competition: An Experimental Investigation
with Tobias Salz: w26765
We evaluate dynamic oligopoly estimators with laboratory data. Using a stylized en-try/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov-perfect equilibrium (MPE) and use the estimates to predict counterfactual behavior. The concern is that if the Markov assumption was violated one would mispredict counterfactual outcomes. The experimental method allows us to compare predicted behavior for counterfactuals to true counterfactuals implemented as treatments. Our main finding is that counterfactual prediction errors due to collusion are in most cases only modest in size.

Published: Tobias Salz & Emanuel Vespa, 2020. "Estimating dynamic games of oligopolistic competition: an experimental investigation," The RAND Journal of Economics, vol 51(2), pages 447-469.

November 2017Probabilistic States versus Multiple Certainties: The Obstacle of Uncertainty in Contingent Reasoning
with Alejandro Martínez-Marquina, Muriel Niederle: w24030
We propose a new hypothesis, the Power of Certainty, to help explain agents' difficulties in making choices when there are multiple possible payoff-relevant states. In the probabilistic ‘Acquiring-a-Company’ problem an agent submits a price to a firm before knowing whether the firm is of low or high value. We construct a deterministic problem with a low and high value firm, where the agent submits a price that is sent to each firm separately. Subjects are much more likely to use dominant strategies in deterministic than in probabilistic problems, even though computations for profit maximization are identical for risk-neutral agents.

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