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In his 1936 book that would give theoretical support to Franklin D. Roosevelt’s New Deal, the British economist John Maynard Keynes wrote: “The ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood. Indeed the world is ruled by little else.”
The ideas of economists – their models, theories or ideologies – have a profound influence on our daily lives. To give an example: when the monetary policy committee decides whether to lower or raise the interest rate, they do so influenced by a model that predicts the likely effects of the policy change.
But there is not one universal model. Macroeconomists, depending on their school of thought, have different beliefs about how the real world works. Some, like those that propound Real Business Cycle (RBC) theory, argue that business cycle fluctuations are the result of exogenous changes to an economy, and because wages and prices are flexible, there is little that governments can do through fiscal and monetary policy in a downswing.
Others, like New Keynesians, see a greater role for government intervention because of things like sticky wages and prices.
Though these ideological disagreements in macroeconomics are nothing new, one would expect that the competition between these ideas would ultimately lead to a better way to explain what is happening in the world. But this is not the case, and is one of the main reasons the World Bank’s new chief economist, Paul Romer, recently wrote a stinging critique of macroeconomics. “I have observed more than three decades of intellectual regress,” he begins, explaining that macroeconomics has gone down a wrong path and have now reached a dead end.
The basic premise is this: macroeconomists’ increasingly sophisticated models have ignored real-world evidence. Simon Wren-Lewis of Oxford University explains: “If we look at the rise of RBC research a few decades ago, that was only made possible because economists chose to ignore evidence about the nature of unemployment in recessions.”
Why would scholars willingly choose to ignore real-world evidence? “The obvious explanation is ideological,” says Wren-Lewis. “I cannot prove it was ideological, but it is difficult to understand why – in an area which […] suffers from a lack of data – you would choose to develop theories that ignore some of the evidence you have.”
Ironically, this shift came at a time when the rest of the profession, fields like labour economics, development economics and international trade, shifted the other way: from theory to empirics.
To be fair, RBC models have become less popular, replaced by “New Keynesian” models. These ones make more realistic assumptions of the real world, like adding sticky wages, but still share many of the same concerns. Because these new generation models, known as Dynamic Stochastic General Equilibrium (DSGE) models, are “built from the ground up” (in other words, built on microeconomic foundations), they are far more appealing theoretically than the structural models of the previous generation, models that only considered the interlinkages of different macroeconomic variables.
But in practice they turned out to be less than satisfactory: DSGE models require the modeller to make many assumptions about how individual agents behave, and it turns out that this behaviour is difficult to measure, making the assumptions rather subjective. The result is that, though theoretically plausible, the outcome is often far removed from the real-world evidence. Most importantly, forecasts are often far less accurate with DSGE models than with multiple-equation structural models. That is why most reserve banks, including our own, still mostly rely on structural models to help predict the future outcomes of their policy decisions.
So why continue with DSGE models? This is a consequence of the way scholarship works. In a blog post in response to Romer, Narayana Kocherlakota of the University of Rochester writes: “We tend to view research as being the process of posing a question and delivering a pretty precise answer to that question. In this process, machines that can be used by many scholars to generate answers to wide ranges of questions are highly prized. [...] And people who have the mathematical and computational skills to make machines even more powerful, so that they can answer even more questions, are naturally highly valued.”
Yet, if these “answers” increasingly abstract away from reality, we are not much better off than before. Keynes, who developed a new theory when the existing paradigm could not explain the real world anymore, knew this all too well: “Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist.”
For academic macroeconomics to regain its influence, it needs to be, as Kocherlakota writes, “a lot more flexible in our thinking about models and theory, so that they can be firmly grounded in an improved empirical understanding”. This won’t be easy. As Kocherlakota says, it will be “hugely messy work”. Will this generation’s John Maynard Keynes please stand up?
Johan Fourie is associate professor in economics at Stellenbosch University.
This article originally appeared in the 9 February edition of finweek. Buy and download the magazine here.
