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Merger Simulation: A Simplified Approach with New Applications


Roy J. Epstein


Independent

Daniel L. Rubinfeld


University of California at Berkeley - School of Law; NYU Law School; National Bureau of Economic Research (NBER)


Antitrust Law Journal, December 2001

Abstract:     
Merger simulation is growing in importance as a tool to evaluate the unilateral competitive effects of mergers. This paper offers a relatively non-technical description of the principles of merger simulation. In addition, it introduces PCAIDS, a new and highly flexible "calibrated-demand" merger simulation methodology that is based on a simplified version of AIDS. PCAIDS can be implemented on a conventional spreadsheet using market shares and two price elasticities; scanner or transaction-level data are not required. The paper offers some applications of merger simulation with PCAIDS that include comparisons with other simulation models. It also shows how PCAIDS can be applied to the analysis of efficiencies, divestiture, and product repositioning/entry. Finally, the paper offers an analysis of the Merger Guidelines safeharbors. A detailed mathematical appendix is included.

Keywords: Antitrust, merger simulation, unilateral effects, empirical methods

JEL Classification: L40

Accepted Paper Series


Date posted: November 28, 2001  

Suggested Citation

Epstein, Roy J. and Rubinfeld, Daniel L., Merger Simulation: A Simplified Approach with New Applications. Antitrust Law Journal, December 2001. Available at SSRN: http://ssrn.com/abstract=291222

Contact Information

Roy J. Epstein
Independent ( email )
34 Cushing Ave.
Belmont, 02478
Daniel L. Rubinfeld (Contact Author)
University of California at Berkeley - School of Law ( email )
Boalt Hall
Berkeley, CA 94720-7200
United States
(510) 642-1959 (Phone)
(510) 642-3767 (Fax)
HOME PAGE: http://www.law.berkeley.edu/faculty/rubinfeldd
NYU Law School ( email )
44 West Fourth Street, Suite 9-53
New York, NY 10012-1126
United States
(212) 992 8834 (Phone)
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Feedback to SSRN (Beta)


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