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date: 04 December 2020

Abstract and Keywords

This chapter characterizes screening for collusion as a problem of inference whose essential elements include competitive null hypothesis (H0), a collusive alternative (H1), and an empirical indicator (X) to differentiate between them. Using this framework, the chapter reviews the theoretical and empirical efforts to design screens and finds that screens fail for one of three reasons: (1) the empirical indicator cannot distinguish between H0 and H1; (2) H0 is not indicative of competition or H1 is not indicative of collusion; or (3) the world is neither H0 nor H1. The often underappreciated, second and third conditions imply that before using a screen, the practitioners should make sure that the industry in question “fits” the theoretical model or assumptions on which the screen is based.

Keywords: collusion, screening, screen, Bayesian hypothesis testing, natural experiments, structural modeling

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