This article supersedes a previous paper titled “Merger Mechanisms” by Brusco, Lopomo, and Viswanathan. We are grateful to two referees and the associate editor for many comments that helped us to improve the article. We also gratefully acknowledge comments by Audra Boone, Tracy Lewis, Harold Mulherin, Jaideep Roy, participants in the Third International Conference on Game Theory in Mumbai, India, the Winter meetings of the Econometric Society, 2004, the conference on Auctions and Market Design, Milan 2003, and seminars at Rutgers University, Universitat Autònoma de Barcelona, Università Statale di Milano-Bicocca, Duke University, and Università Cattolica di Milano. Please address correspondence to: Giuseppe Lopomo, Fuqua School of Business, Duke University, Box 90120, Durham, NC 27708-0120, U.S.A. E-mail: glopomo@duke.edu.
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EFFICIENT MECHANISMS FOR MERGERS AND ACQUISITIONS†
Article first published online: 17 JUL 2007
DOI: 10.1111/j.1468-2354.2007.00452.x
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How to Cite
Brusco, S., Lopomo, G., Robinson, . D. T. and Viswanathan, S. (2007), EFFICIENT MECHANISMS FOR MERGERS AND ACQUISITIONS. International Economic Review, 48: 995–1035. doi: 10.1111/j.1468-2354.2007.00452.x
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Manuscript received May 2005; revised April 2007.
Publication History
- Issue published online: 17 JUL 2007
- Article first published online: 17 JUL 2007
- Abstract
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We characterize incentive-efficient merger outcomes when payments can be made both in cash and stock. Each firm has private information about both its stand-alone value and a component of the (possibly negative) potential synergies. We study two cases: when transfers can, and cannot, be made contingent on the value of any new firm. When they can, we show that redistributing shares of any nonmerging firm generates information rents and provides necessary and sufficient conditions for the implementability of efficient merger rules. When they cannot, private information undermines efficiency more when it concerns stand-alone values than synergies. Here, acquisitions emerge as optimal mechanisms.