Best of times … Worst of times … Macro and reality
Syed Nasir Ershad
Books and printed words were considered to be flawless and correct beyond doubt. But they are not. There are basically four different activities that all go by the name of macroeconomics. They actually have relatively little to do with each other. It is better to understand the differences between them to avoid confusion.
The first type of macroeconomics is what is heard in a lot of casual discussions. It often revolves around the ideas of dead sages like Friedrich Hayek, Hyman Minsky and John Maynard Keynes. It doesn’t involve formal models, but it does usually contain a hefty dose of political ideology.
The second is finance macro. This consists of private-sector economists and consultants who try to read the tea leaves on interest rates, unemployment, inflation and other indicators in order to predict the future of asset prices (usually bond prices). It mostly uses simple math, though advanced forecasting models are sometimes employed. It always includes a hefty dose of personal guesswork.
The third is academic macro. This traditionally involves professors making toy models of the economy – since the early ’80s, these have almost exclusively been DSGE (dynamic stochastic general equilibrium) models. Though academics soberly insist that the models describe the deep structure of the economy, based on the behavior of individual consumers and businesses, most people outside the discipline who take one look at these models immediately think they’re kind of a joke. They contain so many unrealistic assumptions that they probably have little chance of capturing reality. Their forecasting performance is abysmal. Some of their core elements are clearly broken. Any rigorous statistical tests tend to reject these models instantly, because they always include a hefty dose of fantasy.
The fourth type is Central Bank macro. The Central Banks generally use an eclectic approach, involving both data and models. Sometimes the models are of the DSGE type, sometimes not. They take data from many different sources, instead of the few familiar numbers like unemployment and inflation, and analyzing the information in a bunch of different ways. And it inevitably contains a hefty dose of judgment.
Perhaps the academic macro has basically failed the other three. Because academic macro models are so out of touch with reality, people in causal discussions cannot refer to academic research to help make their points. Instead, they have to turn back to the old masters, who were at least describing a world that had some passing resemblance to the economy we observe in our daily lives.
And because academic macro is so useless for forecasting – including predicting the results of policy changes – the financial industry cannot use it for practical purposes. Fortunately, this may be changing. Some of the main pillars of modern academic macro theory are now being challenged. The idea of ‘rational expectations’ which says that people on average use the correct mental model of the economy when they make their decisions, is being challenged by top professors, and many are looking at alternatives.
But that’s just the beginning – far deeper changes may be in the offing. Some people argue to abandon DSGE models, saying that they have not worked. They suggest that the new macroeconomics will focus on empirics and falsification – in other words, looking at reality instead of making highly imaginative assumptions about it. They also say that macro will be fertilized by other disciplines, such as psychology and sociology, and will incorporate elements of behavioral economics.
As originally conceived, macro is about explaining national-level data series like employment, output and prices. Eventually, economists realized that to explain those things, they would need to understand the smaller pieces of the economy, such as consumer behavior or competition between companies. At first, they just imagined or postulated how these elements worked – that’s the core of DSGE. Economists now realize that consumers and businesses behave in ways that are much more complicated and difficult to understand. So there has been increased interest in what is called ‘macro-focused micro’ – studies of businesses, competition, markets and individual behavior that have relevance for macro even though they were not traditionally included in the field. Examples of this would include studies of business dynamism, price adjustment, financial bubbles and differences between workers.