*This paper was previously titled ‘Merger Clusters during Economic Booms’. We thank Yeon-Koo Che, Tomaso Duso, Ulrike Malmendier, Chrysovalantou Milliou, Marco Ottaviani, Johan Stennek, Burcin Yurtoglu, three anonymous referees as well as participants at ASSET 2005, EARIE 2008, Jornadas de Economia Industrial 2005, and Simposio de Analisis Economico 2005 for comments and criticisms. Paul Heidhues gratefully acknowledges financial support from the Deutsche Forschungsgemeinschaft through SFB TR/15. Jo Seldeslachts gratefully acknowledges financial support from the EC 5th Framework Programme Research Training Network (HPRN-CT-2002-00224) and the Research Network for Innovation and Competition (RNIC).
SCREENING AND MERGER ACTIVITY*
Article first published online: 24 DEC 2010
© 2010 The Authors. The Journal of Industrial Economics © 2010 Blackwell Publishing Ltd. and the Editorial Board of The Journal of Industrial Economics
The Journal of Industrial Economics
Volume 58, Issue 4, pages 794–817, December 2010
How to Cite
BANAL-ESTAÑOL, A., HEIDHUES, P., NITSCHE, R. and SELDESLACHTS, J. (2010), SCREENING AND MERGER ACTIVITY. The Journal of Industrial Economics, 58: 794–817. doi: 10.1111/j.1467-6451.2010.00438.x
- Issue published online: 24 DEC 2010
- Article first published online: 24 DEC 2010
- Merger Waves;
- Defense Tactics;
In our paper, the target of a proposed merger, by setting a reserve price, is able to screen prospective acquirers according to their (expected) ability to generate merger-specific synergies. Both empirical evidence and many merger models suggest that the difference between high and low-synergy mergers becomes smaller during booms. Thus, a target's opportunity cost for sorting out relatively less fitting acquirers increases and, hence, targets screen less tightly during booms, which leads to a hike in merger activity. Our screening mechanism not only predicts that merger activity is intense during booms and subdued during recessions but is also consistent with other stylized facts about takeovers and generates novel testable predictions.