Despite its long history in antitrust policy, predation remains a poorly understood phenomenon. The main difficulty is in empirically identifying predatory intent. I propose a method for measuring the effect of reputation, whose significance would enable us to infer predatory intents. Maximum likelihood estimation using simulated annealing algorithm is conducted with a sample of US airline markets. The results provide some support for the presence of entrants learning and reputation effect. As an application, I discuss how the outcomes of my empirical model could help analyze such antitrust cases as the American Airlines Case.Predatory reputation Discrete choice model Entry Learning Airline market
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