Paul Romer says
Ultimately, the test of the model is its correspondence with the world. If we use certain frameworks, you can understand a much richer set of facts about the world. Growth is a difficult area to work because you’re addressing questions about the very long run, so you don’t have an abundance of data. You’re trying to invoke evidence from history over the very long run. We needed to come up with a way to think about all of these facts about the broad sweep of human history.
Math can be a very clear, concise, effective way to communicate ideas. What I saw in some of the people I was criticizing for mathiness was an almost obstinate adherence to positions, and then a use of any kind of mathematical argument that would support that position. What was missing was one of the characteristics of good science, which is to say “Well, given these new arguments, I may have been wrong before.”
Pointer from Mark Thoma.
Earlier, a reader’s comment brought me to Itzhak Gilboa’s review of a book by Mary Morgan.
Clearly, there are many instances in which economic analysis yields qualitative predictions, providing robust insights that allow us to predict trends, compare economic systems, and so forth. Yet, economics is not considered to be a successful science when quantitative predictions are concerned.
There is, however, another view of economics, by which it can have other successes: it is a field of enquiry whose goal is to critique reasoning about economic phenomena
This is an idea with chewing on. The purpose of a model, either theoretical or empirical, is not to provide a definitive “correspondence with the world,” as Romer would have it. Rather, it is to point out possibilities that deserve the attention of economists and those interested in economic policy.
>>You’re trying to invoke evidence from history
I think Romer employs the term evidence for what Hayek terms as patterns. The paradigm makes all the difference. An analysis at higher abstract levels introduces unknown unknowns,
*Evidence* is at best a partial equation, several underlying dependencies remain unknown. Strangely, Romer does realize that there is not an abundance of data.
I think Romer is being facile when he talks about “correspondence with the world.” Economic reality is difficult to observe and measure. We don’t have clean labs.
Take the minimum wage. Theory and common sense give us the Law of Demand. Suppose a dataset reveals no relationship at all. Does correspondence with the world mean we should reject the Law of Demand?
Reason can critique reason but is tautology without empirics.
Among bloggers, I think that Nick Rowe is an exemplar of this alternative approach to modeling. He is daily writing down models, — even absurdly simple models — to isolate important concepts or draw attention to critical relationships. To criticize him for failing at “correspondence with the world” would be to forego a chance to deepen one’s understanding. It is very nice to see Gilboa articulate the position.