We introduce a three-person redistribution game with preplay communication. Three focal points of the game are derived from different equity standards and Rawls' difference principle. An experimental test confirms our hypothesis that equity in terms of effort-proportionality is not pursued at...

Online interactions are frequently governed by reputation systems that allow users to evaluate each other after an interaction. Effective reputation systems can increase trust and may improve efficiency in market settings. In recent years, however, fake reviews have become increasingly...

This paper studies the ability of markets to alleviate taste-based discrimination in a laboratory experiment. We find that markets significantly reduce discrimination relative to individual choice situations with the same payoff structure and the same social group membership of the trading...

Competitive rewards are often assigned on a regular basis, e.g., in annual salary negotiations or employee-of-the-month schemes. In many settings, this implies that the quality of the competitor varies with earlier outcomes. Using a real-effort experiment, we examine how dishonesty and effort...

This study analyzes whether enabling people to get informed about redistributive consequences is an effective measure to prevent equivalence framing in the domain of voting on redistribution. Utilizing a simplified version of the Meltzer-Richard model, an equivalent frame is induced by letting...

Online interactions are frequently governed by reputation systems that allow users to evaluate each other after an interaction. Effective reputation systems can increase trust and may improve efficiency in market settings. In recent years, however, fake reviews have become increasingly...

We experimentally investigate a finitely repeated public good game with varying partners. Within each period, participants are pairwise matched and contribute simultaneously. Participants are informed about contributions and each participant evaluates her partner's contribution. At the beginning...