Dietz Vollrath has a new post that goes a long way toward clarifying the battle lines in the fight over the foundations of growth theory. If you haven’t read it, go read it now, then come back. Any attempt I might make to summarize it here will only add noise. The trilemma he lays out is crystal clear. He acknowledges conversations with Pietro Peretto, who apparently deserves some of the credit for the distilled clarity of the post.

1. Marshallian Intuition One type of reaction involves a recitation of some Marshallian intuition about rents or quasi rents and a request for clarification about what this intuition misses. My suggestion is that if you are stuck, try approaching the problem from a new angle. In this case, a good way to do so is to work through the logic of the proof based on Euler’s Theorem and try to see whether its assumptions fit the example you are considering.

The U.S. Department of Energy employs physics Ph.D.s to manage our nuclear weapons. How would you feel if some of them wrote blog posts saying that it is possible to build a perpetual motion machine? What if they did this to signal their loyalty to some club of physicists? Wouldn’t you wonder why membership in this club was important enough get them say that they do not believe the second law of thermodynamics?

Lucas (2009) makes a misleading claim about models of growth: S1: {adding books} => {no change in growth} David Andolfatto admits that S1 is false and the true statement is {adding books} => {{no change in growth} or {sustained change in growth}}. But he professes not to see why anyone should care that Lucas engages in this type of mathiness; that is, why anyone should care that Lucas makes a misleading verbal statement about the mathematics of growth theory.

The key to understanding mathiness is to recognize how a formal language can interact with natural language. The source code for a computer program has formal statements written in a language like C that will be interpreted by a compiler. It will also have comments and messages written in natural language that will be read by a person. Compared to mathematics, source code is easy to analyze because the statements in the two languages are kept separate.