44 Pages Posted: 22 Dec 2011
Date Written: December 2011
Predatory pricing -- a deliberate strategy of pricing aggressively in order to eliminate competitors -- is one of the more contentious areas of antitrust policy and its existence and efficacy are widely debated. The purpose of this paper is to formally characterize predatory pricing in a modern industry dynamics framework. We endogenize competitive advantage and industry structure through learning-by-doing.
We first show that predation-like behavior arises routinely in our model. Equilibria involving predation-like behavior typically coexist with equilibria involving much less aggressive pricing. To disentangle predatory pricing from mere competition for efficiency on a learning curve we next decompose the equilibrium pricing condition. Our decomposition provides us with a coherent and flexible way to develop alternative characterizations of a firms predatory pricing incentives, some of which are motivated by the existing literature while others are novel. We finally measure the impact of the predatory pricing incentives on industry structure, conduct, and performance. We show that forcing a firm to ignore these incentives in setting its price can have a large impact and that this impact stems from eliminating equilibria with predation-like behavior. Along with the predation-like behavior, however, a fair amount of competition for the market is eliminated. Overall, the distinction between predatory pricing and pricing aggressively to pursue efficiency is closely related to the distinction between the advantage-building and advantage-denying motives that our decomposition of the equilibrium pricing condition isolates and measures.
Keywords: competition policy, industry dynamics, predatory pricing
JEL Classification: C73, L13, L44
Suggested Citation: Suggested Citation
Besanko, David and Doraszelski, Ulrich and Kryukov, Yaroslav, The Economics of Predation: What Drives Pricing When There is Learning-by-Doing? (December 2011). CEPR Discussion Paper No. DP8708. Available at SSRN: https://ssrn.com/abstract=1976050
By C. Benkard
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