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.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 27 (2009) Issue (Month): 5 (September) Pages: 592-604 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF
Cited by: (explanations, 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.)