Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?
通过博弈模型研究算法带来的更好需求预测如何影响行业合谋的可持续性，发现更好的预测虽然有助于合谋定价，但也增加了企业在高需求时期降价的诱惑，最终可能导致更低价格和更高消费者剩余。
We build a game-theoretic model to examine how better demand forecasting resulting from algorithms, machine learning, and artificial intelligence affects the sustainability of collusion in an industry. We find that, although better forecasting allows colluding firms to better tailor prices to demand conditions, it also increases each firm’s temptation to deviate to a lower price in time periods of high predicted demand. Overall, our research suggests that, despite concerns expressed by policy makers, better forecasting and algorithms can lead to lower prices and higher consumer surplus. This paper was accepted by Joshua Gans, business strategy.