Behind the Model: A Constructive Critique of Economic Modeling.

• Author: Gordon, Peter
• Position: Book review

Behind the Model: A Constructive Critique of Economic Modeling

By Peter Spiegler

New York: Cambridge University Press, 2015.

Pp. X, 221. $35.99 paperback.

On November 5, 2008, the Telegraph famously reported, "During a briefing by academics at the London School of Economics on the turmoil on the international markets the Queen asked: 'Why did nobody notice it?'" Good question. Since then, many economists and others have responded. What is wrong with (macro)economics? Actually, the question should be, What is wrong with the modeling economists do? Peter Spiegler takes up this issue in Behind the Model: A Constructive Critique of Economic Modeling. The book's cover shows a square peg forced into a round whole. Spiegler wonderfully addresses the problem.

To be clear, this is not a critique along the lines of the one made by Deirdre McCloskey, that standard economic modeling ("Max U" is her preferred label for what she calls "Samuelsonian" economics) is sterile and not able to address the "big" questions--for example, How is it that some nations are poor and some comparatively rich? Today's mainstream economics, heavily engaged in mathematical economics, steers clear of these interesting questions because it has nothing to say about how cultures evolve or how we adopted "bourgeois virtues."

Others have worried that economics took a wrong turn, going the way of physics. Spiegler poses the mismatch question ("between the principles discerned by the scientist and the phenomenon under investigation" [p. 10]) early in the book. Physicists model how particles interact. But particles do not have mood swings that baffle us.

Spiegler addresses mainstream economics on its own terms. He begins with the point made by Milton Friedman some years ago that models are best judged by their predictions. That's not good enough, writes the author; we would learn too little about the validity of relations ("paths") inside the black box. How would we identify the important causal factors? Are the models that economists adopt plausible and proper metaphors? Spiegler refines this question with great care.

He looks at conventional mathematical modeling by economists, noting that it requires two transitions ("apt representations," "correspondences") between ordinary language and mathematical language ("twice crossing a significant linguistic divide" [p. 47]). The mathematical language is metaphorical. Are the mathematical models economists work with appropriate...