A Theory of Politeness and Rudeness in Cooperative Communication

Abstract

It is common for one who has information to share it cooperatively with one who needs it. Perhaps surprisingly, this information is often not communicated in the simplest possible way. For example, Standard and Poor's assigns ratings of at least "B-" to 97% of corporate issues, and segments these issues into 16 categories (AAA, AA, AA-, etc.). A full 7 of these 16 categories are devoted to issues with nearly identical default probabilities, leaving only 9 categories to cover the wide variety of default probabilities found in speculative corporate debt. Equally concerning, Yelp restaurant reviews are predominantly positive, with an average of 3.8 stars out of 5. This limits the site's usefulness in distinguishing the highest quality fare. I show that the purpose of a reviewer generates the optimal distribution of reviews. If it is most important to separate great from good, then reviews will tend to be harsh, in the sense that most reviews will be below average. If it is most important to separate bad from worst, then reviews will tend to be polite, in the sense that most reviews will be above average. Importantly, politeness and harshness are emergent properties of the optimal messaging rule. Results are consistent with casual observation, and provide testable implications across a variety of settings, including credit reports, analyst ratings, credit ratings, wine ratings, referee reports, customer reviews, grade inflation, and letters of recommendation.