We present a dynamic quantity setting game, where players may continuously adjust their quantity targets, but incur convex adjustment costs when they do so. These costs allow players to use quantity targets as a partial commitment device. We show that the equilibrium path of such a game is...

Experimental subjects allocate $10,000 across four S&P 500 index funds. Subject rewards depend on the chosen portfolio's subsequent return. Because the investments are not actually intermediated by the fund companies, portfolio returns are unbundled from non-portfolio services. The optimal...

We analyze the role of benchmarks in over-the-counter markets subject to search frictions. The publication of a benchmark can, under conditions, raise total social surplus by (i) increasing the volume of beneficial trade, (ii) facilitating more efficient trade matching between dealers and...

We present and experimentally test a mechanism that provides a simple, natural, low cost, and realistic solution to the problem of compliance with socially determined efficient actions, such as contributing to a public good. We note that small self-governing organizations often place enforcement...

This paper compares two methods to encourage socially optimal provision of a public good. We compare the efficacy of vigilante justice, as represented by peer-to-peer punishment, to delegated policing, as represented by the "hired gun" mechanism, to deter free riding and improve group welfare....

Previous findings on punishment have focused on environments in which the outcomes are known with certainty. In this paper, we conduct experiments to investigate how punishment affects cooperation in a two-person stochastic prisoner's dilemma environment where each person can decide whether or...

We seed noisy information to members of a real-world social network to study how information diffusion and information aggregation jointly shape social learning. Our environment features substantial social learning. We show that learning occurs via diffusion which is highly imperfect: signals...