Challenges in Merger Simulation Analysis
In this paper, we share our experience with merger simulations using a Random Coefficient Logit model on the demand side and assuming a static Bertrand game on the supply side. Drawing largely from our work in Knittel and Metaxoglou (2008), we show that different demand estimates obtained from different combinations of optimization algorithms and starting values lead to substantial differences in post-merger market outcomes using metrics such as industry profits, and change in consumer welfare and prices.
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Volume (Year): 101 (2011)
Issue (Month): 3 (May)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Aviv Nevo, 2003. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Microeconomics 0303006, EconWPA.
- Aviv Nevo, 2000. "A Practitioner's Guide to Estimation of Random-Coefficients Logit Models of Demand," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 9(4), pages 513-548, December.
- Jean-Pierre H. Dubé & Jeremy T. Fox & Che-Lin Su, 2009. "Improving the Numerical Performance of BLP Static and Dynamic Discrete Choice Random Coefficients Demand Estimation," NBER Working Papers 14991, National Bureau of Economic Research, Inc.
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