We analyze maximization of revenue in the dynamic and stochastic knapsack problem where a given capacity needs to be allocated by a given deadline to sequentially arriving agents. Each agent is described by a two-dimensional type that reflects his capacity requirement and his willingness to pay...

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....

Increasingly, algorithms make socially consequential decisions. This makes it crucial to determine when their decisions are discriminatory and how to prevent this outcome. While algorithmic decision-making has proven to be a challenge for traditional anti-discrimination law, there is an...

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....

I investigate whether algorithmic trading (AT) affects voluntary disclosure. I predict that AT's advantage over non-algorithmic investors decreases information acquisition. Because investors are less informed, managers increase disclosure to reduce information asymmetry. I find evidence...