Econ Papers Daily / 期刊论文
筛选适应性卡特尔
Screening Adaptive Cartels
摘要
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.
中文摘要
我们提出了一种数据驱动反垄断监管的均衡理论，其中监管机构基于可疑投标模式发起调查，而卡特尔组织能够适应监管机构使用的统计筛查手段。我们的主要结论表明，采用低误报率（安全检验）的合谋筛查方法，相较于自由放任政策具有稳健的改进效果。安全检验既不会催生新的合谋均衡，也不会损害竞争性行业。此外，安全检验具有严格约束力，在某些情境下甚至能瓦解所有合谋均衡。