Home > Uncategorized > Why not make macroeconomics a science?

Why not make macroeconomics a science?

from Lars Syll

The trouble is, too many theorists — especially in the mainstream of the discipline — have drifted far from the real world. Their ambition has been to build mathematically elegant and internally consistent models of the economy, even if that requires wholly unrealistic assumptions. Granted, just as maps have to simplify complex terrain, theoretical models must ignore aspects of reality to be any use. But there’s a line between simplification and gross distortion, and modern macroeconomics has crossed it.

64f5d94d9836c6a09b5d2009f0d4634a845bb2d7ba56bbaa16176c2fd0e958c0Before the 2008 financial crisis, for example, the standard models more or less ignored finance. No banks, no indebtedness, no leverage. As a result, they couldn’t make sense of the worst global recession since the 1930s …

Given such spectacular failures, you’d think the profession would have gone back to the drawing board. It hasn’t …

Whenever an economist says “in our model,” beware. Demand to know what assumptions the model makes, and question those assumptions as severely as the theorists test for valid inference — because valid inference from bogus assumptions is useless. Where possible, and in the same spirit, pay closest attention to empirical and historical research.

In just about every branch of science, theoretical research has been crucial to achieving breakthroughs. In macroeconomics, it has held progress back. To stop the discipline fading into irrelevance, this will have to change.

Bloomberg View Editorial Board

The editors of Bloomberg View are, of course, absolutely right.

Unfortunately, there are many kinds of useless ‘post-real’ economics held in high regard within the mainstream economics establishment today. Few — if any — are less deserved than the macroeconomic theory/method called calibration. 

In physics it may possibly not be straining credulity too much to model processes as ergodic – where time and history do not really matter – but in social and historical sciences it is obviously ridiculous. If societies and economies were ergodic worlds, why do econometricians fervently discuss things such as structural breaks and regime shifts? That they do is an indication of the unrealisticness of treating open systems as analyzable with ergodic concepts.

The future is not reducible to a known set of prospects. It is not like sitting at the roulette table and calculating what the future outcomes of spinning the wheel will be. Reading Lucas, Sargent, Prescott, Kydland and other calibrationists one comes to think of Robert Clower’s apt remark that

much economics is so far removed from anything that remotely resembles the real world that it’s often difficult for economists to take their own subject seriously.

Or as Paul Romer put it in his masterful attack on ‘post-real’ economics last year:

Math cannot establish the truth value of a fact. Never has. Never will.

So instead of assuming calibration and rational expectations to be right, one ought to confront the hypothesis with the available evidence. It is not enough to construct models. Anyone can construct models. To be seriously interesting, models have to come with an aim. They have to have an intended use. If the intention of calibration and rational expectations  is to help us explain real economies, it has to be evaluated from that perspective. A model or hypothesis without a specific applicability is not really deserving our interest.

Without strong evidence all kinds of absurd claims and nonsense may pretend to be science. We have to demand more of a justification than rather watered-down version of “anything goes” when it comes to rationality postulates. If one proposes rational expectations one also has to support its underlying assumptions. None is given, which makes it rather puzzling how rational expectations has become the standard modeling assumption made in much of modern macroeconomics. Perhaps the reason is that economists often mistake mathematical beauty for truth.

But I think another reason is that calibration economists are not particularly interested in empirical examinations of how real choices and decisions are made in real economies. In the hands of Lucas, Prescott and Sargent, rational expectations has been transformed from an – in principle – testable hypothesis to an irrefutable proposition. Believing in a set of irrefutable propositions may be comfortable – like religious convictions or ideological dogmas – but it is not  science.

So where does this all lead us? What is the trouble ahead for economics? Putting a sticky-price DSGE lipstick on the calibrationists’ Real Business Cycle pig sure won’t do. Neither will just looking the other way and pretend it’s raining. The biggest problem in macroeconomics today is that macroeconomists don’t care about facts. As long as they can build consistent mathematical models they’re happy. If the consistency is applicable to the real-world doesn’t seem to bother them.

If macroeconomic models – no matter of what ilk –  build on microfoundational assumptions of representative actors, rational expectations, market clearing and equilibrium, and we know that real people and markets cannot be expected to obey these assumptions, the warrants for supposing that conclusions or hypothesis of causally relevant mechanisms or regularities can be bridged, are obviously non-justifiable. Trying to represent real-world target systems with models flagrantly at odds with reality is futile. And if those models are New Classical Real Business Cycle calibrations  or ‘New Keynesian’ makes very little difference.

No matter how brilliantly silly DSGE models mainstream macroeconomists come up with, they do not help us working with the fundamental issues of modern economies. Using that kind of models only confirms Robert Gordon‘s  dictum that today

rigor competes with relevance in macroeconomic and monetary theory, and in some lines of development macro and monetary theorists, like many of their colleagues in micro theory, seem to consider relevance to be more or less irrelevant.

As the Bloomberg View editors say — “this will have to change.” Until then we have to continue  wonder what is the raison d’être of macroeconomics if it has nothing to say about the real world and the economic problems out there?

  1. February 9, 2017 at 11:47 pm
    • February 10, 2017 at 6:38 pm

      From your reference:

      Although I have seen induction presented as though it were a logical process, it is not. It is a process of recognition, or cognition. It is the perception of a pattern of some kind in the available observations: certain animals are seen migrating and soon after the weather turns colder; the sun rises at regular intervals from a certain part of the horizon; high levels of debt tend to be followed by a market crash.

      The description of such a perceived pattern, or of what might cause the pattern, comprises a hypothesis: some animals move to warmer places ahead of winter; the sun goes round the Earth at a steady rate on a regular path; debt higher than certain levels becomes unstable.

      Ever since the marginal revolution, economists have constructed patterns that do not exist in nature. If, initially, forethought –which is intrinsic to reason or rationality– meant seeing or inferring meaning from patterns (including the entrails of a chicken or the pattern of tea leaves in a cup in an all too deterministic world), science began with questioning whether the meaning –and the prediction from that meaning– were actually present.

      The marginal revolution, however, imagined a pattern and then imagined what the pattern predicted (similar to finding a deterministic pattern in the entrails of a chicken whether it existed or not), and then insisted that this imagined pattern and its predictions were universally true. (Read Milton Friedman, for instance.)

      Obviously, observations count for nothing if the imagined pattern is never examined for its conformity with actual economic behavior.

  2. February 11, 2017 at 3:34 am

    In my view, the greatest impediment to realizing this goal is that economists don’t really understand what science is or how it works. It’s not their fault, however. Most have little or no science education or experience to rely on for this. They have education in some, but only some axiomatic philosophy and mathematics. And a bit of background in statistical theory (not much in probability mathematics). So, all-in-all it’s their ignorance that stops economists from working as scientists.

    This article shows some of that ignorance. For example, several times truth is set up as a goal of a scientific economics. Science is not concerned with truth. It is concerned with useful and pragmatic. And, of course with temporary. Also, the article states, “A model or hypothesis without a specific applicability is not really deserving our interest.” This could be a bit confusing. Models may need to be teleological (to have a goal) but human society and the part of it called economics does not. Society and economics is made up as we go along. Not a long- or short-term plan. Finally, the article states, “The biggest problem in macroeconomics today is that macroeconomists don’t care about facts.” Some caution is called for on facts. Facts are not self-evident. They are created in collective life through interactions. It’s this process of creation economists as scientists need to examine. And this process is not purely “economic” in the discipline sense. Economists studying economics must, like other social scientists coordinate their work across disciplines.

  1. No trackbacks yet.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.