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We propose an equilibrium theory of data-driven antitrust oversight in which regu-
lators launch investigations on the basis of suspicious bidding patterns and cartels can
adapt to the statistical screens used by regulators. Our main result establishes that
screening for collusion using tests with a low false-positive rate (safe tests) is a robust
improvement over laissez-faire. Safe tests do not create new collusive equilibria, and do
not hurt competitive industries. In addition, safe tests can have strict bite, including
unraveling all collusive equilibria in some settings.
