Litigation Settlement and Collusion
AbstractPrivate enforcement of regulatory policy is a significant feature of many government-sponsored contests, such as procurements. Although private enforcement is supposed to promote social welfare, we show that competitors can use it to achieve collusive outcomes. In a noncooperative duopoly setting, we show that the threat of litigation, and the possibility of settlement can dramatically affect ex ante competition in the relevant market. Essentially, the settlement process provides a legal mechanism for the exchange of side-payments, while the possibility of a court decision provides the plaintiff with a credible threat against the defendant so as to avert cheating. The result does not require repeated play, ex ante contracts, or other commitment devices. In the federal procurement context, we show that our results are robust to alterations in the court remedy, bargaining power of the litigants, and many other factors. Copyright 1994, the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Bibliographic InfoArticle provided by MIT Press in its journal Quarterly Journal of Economics.
Volume (Year): 109 (1994)
Issue (Month): 1 (February)
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- Adriana Breccia & Hector Salgado-Banda, 2006. "Competing or Colluding in a Stochastic Environment," Computing in Economics and Finance 2006 423, Society for Computational Economics.
- Anton, James J. & Brusco, Sandro & Lopomo, Giuseppe, 2010.
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- Kou Zonglai & Zhang Jian, 2007. "Endogenous licensing in cumulative innovation," Psychometrika, Springer, vol. 2(3), pages 424-457, July.
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- James J. Anton & Sandro Brusco & Giuseppe Lopomo, 2007. "Coordination in Split-Award Auctions with Uncertain Scale Economies: Theory and Data," Department of Economics Working Papers 07-02, Stony Brook University, Department of Economics.
- Adriana Breccia & Hector Salgado-Banda, 2005. "Competing or Colluding in a Stochastic Framework," Birkbeck Working Papers in Economics and Finance 0504, Birkbeck, Department of Economics, Mathematics & Statistics.
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