I’ve been reading an article by Joseph Stiglitz whose title made it sound very promising: Rethinking Macroeconomics: What Failed And How To Repair It. His work on how information asymmetries and uncertainty shape institutions and markets make Stiglitz a strong candidate for setting out a new approach to macroeconomics. And it’s needed. Standard macro has failed, even though many macroeconomists who have invested so much in their human capital are understandably reluctant to agree. Even with modifications such as heterogeneous agents (ie people who are not all identical) and, the standard Dynamic Stochastic General Equilibrium model is not an empirically or theoretically useful representation of an economy.
I was disappointed with the Stiglitz article, however. It’s powerful as a critique, weaker on what to put in place of the standard model, although Stiglitz rightly identifies the institutional reality of money and banking, and credit markets, as essential missing elements. (Non-economists may be surprised to learn that banking does not feature as such in conventional macro models, which are indeed highly abstract).
An alternative tack which some of the most brilliant economists around think is most promising is to look at the complexity models used by physicists and biologists. Paul Ormerod’sis a great introduction to this approach, and I’m about to start Alan Kirman’s Andy Haldane at the Bank of England and Robert May have written in Nature about this modelling strategy as well. I’ve just been having another look at John McMillan’s . It’s a terrific book which looks at the institutions and detailed operations of many specific markets. He too concludes that the complexity approach is the right one at the macro scale, adding:
“The economic system has an additional layer of complexity: its components are people, who react intelligently to it and even reshape it.”
McMillan very sensibly notes that: “[Markets] have impressive achievements; they can also work badly. Whether any particular market works well or not depends on its design.”
Economics has a rapidly improving understanding of market design principles at the sub-macro scale. But this still leaves a huge modelling gap at the aggregate level. Until some future Nobel winner comes up with an alternative workhorse macro model that can be described readily in academic papers and taught to students, whether it is a complexity model or not, we will be stuck with the standard DSGE approach. Nor is it clear to me at what level of aggregation one has to switch from the tools of the market design approach to the tools of analysing complex systems. That is the problem of macroeconomics: not only how should we do macroeconomics, but also where does the boundary between micro and macro lie?
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