Philip Cross: A Nobel Prize in economics for flawed foundations

Earlier this month, American economists Robert Hall and Michael Woodford won the Nobel Prize in economics for their work on the “microeconomic foundations of macroeconomic stabilization.” The two do deserve a Nobel, but not for their work on the micro foundations of macro. The idea that macroeconomics could be based on analyzing and aggregating individual behaviour was doomed to fail. The global financial crisis of 2008-9 left no doubt about that. It is a mystery why the Nobel committee overlooked that failure.

Trying to develop micro foundations for macroeconomics was popular among economists in the 1980s and 1990s. Economists obviously understand that economies consist of millions of “agents,” all pursuing some form of self-interest. Yet macroeconomics relied on hoary rules of thumb relating aggregates such as consumption, investment and savings to income, interest rates and other things in an apparently arbitrary and ad hoc way.

“Micro foundations” quickly became the basis for models of the macro economy used by most central banks, including the Bank of Canada. In fact, by 1999 Robert Hall could confidently pronounce that macroeconomics “is now a branch of applied microeconomics.” But it’s a limited form of micro, relying as these models do on the idea of a “representative agent” — essentially treating an entire population of persons or firms as if they act as one.

In a way, criticism of the micro-foundations approach goes back to the ancient Greeks. Aristotle’s “fallacy of composition” showed how mistaken it is to assume that what applies to a part also applies to the whole. The fallacy of composition was popularized in economics by Keynes’s “paradox of thrift”: more savings may be prudent for an individual but can hamper overall economic growth, at least in the short term.

Other Nobel-winning work has shown how difficult it is to “aggregate preferences” in the way macro modellers would like. Kenneth Arrow won the prize in 1972 partly for his “Impossibility Theorem,” which showed that consistent individual preferences can’t necessarily be combined into a consistent “social welfare function.” Similar conclusions from other theorists forced macro modellers to use representative agents.

Preferences are not the only variable that can’t be aggregated without sacrificing accuracy. Macro estimates of how the overall economy substitutes between labour and capital inputs are quite different from micro estimates based on individual firms, partly because the macro estimates capture substitutions across firms as well as within them.

There’s also the problem that individuals interact with one other. As Friedrich Hayek observed, “a society is not a collection of hermits.” People share information, spread rumours and make recommendations — all of which is hard to model.

Ignoring interactions is especially dangerous in financial regulation. Risk models can make individual banks appear safe, but what about systemic risk from other banks? If one bank fails and stops making loans, this can trigger a bank run that lowers the income of people who have borrowed from other banks, putting these banks at risk, too. Risk analysis changes dramatically as you shift from micro to macro. As Nassim Taleb (author of The Black Swan) observed, one person reduces his risk by buying insurance, but if enough people insure themselves at one company, a catastrophic event can render that firm insolvent, leaving customers unprotected. As Taleb put it: “you have the problem of having to buy insurance on the Titanic from someone on the Titanic.”

The 2008-9 financial crisis vividly demonstrated how a loss of confidence can lead to what was quintessentially a run on the entire banking system. A bank run is a “herd phenomenon,” as Milton Friedman said, and herd behaviour cannot be understood by modelling individuals. In the words of legendary bond guru James Grant, “speculation is a social activity… carried on by groups.” As a result, as David Sumpter wrote in The Ten Equations That Rule the World, “all financial mathematicians now know that markets are a combination of signal, noise, and herding.” During the financial crisis, policy-makers who had to rely on them became acutely aware of the deficiencies of central bank macro models based on micro foundations. Former Treasury Secretary Larry Summers concluded that “attempting to place micro foundations under macroeconomics was not something that informed the policy-making process in any important way.”

The micro-foundations approach cannot explain important macroeconomic trends ranging from technological innovation and entrepreneurship — the dominant forces currently boosting the U.S. economy ahead of Canada’s — to the shocks that routinely affect our economy, such as soaring energy prices, financial panics and viral pandemics. As Keynes noted, the biggest challenge for most people is dealing with the economy’s fundamental uncertainty, and that’s something micro foundations can neither explain nor manage.

Philip Cross is a senior fellow at the Macdonald-Laurier Institute.