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Deciding Between Competition and Collusion

Deciding Between Competition and Collusion We develop an approach to identify and test for bid rigging in procurement auctions. First, we introduce a general auction model with asymmetric bidders. Second, we study the problem of identification in our model. We state a set of conditions that are both necessary and sufficient for a distribution of bids to be generated by a model with competitive bidding. Third, we discuss how to elicit a prior distribution over a firm's structural cost parameters from industry experts. Given this prior distribution, we use Bayes's theorem to compare competitive and collusive models of industry equilibrium. Finally, we apply our methodology to a data set of bidding by construction firms in the Midwest. The techniques we propose are not computationally demanding, use flexible functional forms, and can be programmed using most standard statistical packages. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Review of Economics and Statistics MIT Press

Deciding Between Competition and Collusion

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References (48)

Publisher
MIT Press
Copyright
© 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology
ISSN
0034-6535
eISSN
1530-9142
DOI
10.1162/003465303772815871
Publisher site
See Article on Publisher Site

Abstract

We develop an approach to identify and test for bid rigging in procurement auctions. First, we introduce a general auction model with asymmetric bidders. Second, we study the problem of identification in our model. We state a set of conditions that are both necessary and sufficient for a distribution of bids to be generated by a model with competitive bidding. Third, we discuss how to elicit a prior distribution over a firm's structural cost parameters from industry experts. Given this prior distribution, we use Bayes's theorem to compare competitive and collusive models of industry equilibrium. Finally, we apply our methodology to a data set of bidding by construction firms in the Midwest. The techniques we propose are not computationally demanding, use flexible functional forms, and can be programmed using most standard statistical packages.

Journal

The Review of Economics and StatisticsMIT Press

Published: Nov 1, 2003

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