In this paper we show that subtle forms of deceit undermine the effectiveness of incentives. We design an experiment in which the principal has an interest in underreporting the true performance difference between the agents in a dynamic tournament. According to the standard approach, rational...

We show theoretically and empirically that executives are paid less for their own firm’s performance and more for their rivals’ performance if an industry’s firms are more commonly owned by the same set of investors. Higher common ownership also leads to higher unconditional total pay. We...

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

This paper investigates the extent to which syndication in financial markets is related to collusive behavior. A group of financiers who have private information regarding their capability of monitoring an entrepreneur must decide whether to provide a loan individually in a competitive fashion,...

We study the accuracy and usefulness of automated (i.e., machine-generated) valuations for illiquid and heterogeneous real assets. We assemble a database of 1.1 million paintings auctioned between 2008 and 2015. We use a popular machine-learning technique - neural networks - to develop a pricing...