The economics of predation: What drives pricing when there is learning-by-doing?
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 characterizes predatory pricing in a modern industry dynamics framework. We endogenize competitive advantage and industry structure through learning-by-doing. We show that we can isolate and measure a firm’s predatory incentives by decomposing the equilibrium pricing condition. Our decomposition maps into existing economic definitions of predation and provides us with a coherent and flexible way to develop alternative characterizations of a firm’s predatory incentives. We ask three interrelated questions. First, when does predation-like behavior arise? Second, what drives pricing and, in particular, how can we separate predatory incentives for pricing aggressively from efficiency-enhancing incentives for pricing aggressively in order to move further down the learning curve? Third, what is the impact of predatory incentives on industry structure, conduct, and performance? We find that predation-like behavior arises for wide range of parametrizations, and our decomposition-based definitions are successful in isolating predatory incentives in the sense that eliminating them leads to improvements in long-term measures of market structure, conduct and performance. It also appears that consumers might be valuing short-term benefits of low predatory price more than the cost of future monopolization.