The blatant absence of empirical fit of macroeconomic models

8 December, 2015 at 21:00 | Posted in Economics | 7 Comments

Some months ago sorta-kinda ‘New Keynesian’ Paul Krugman argued on his blog that the problem with the academic profession is that some macroeconomists aren’t “bothered to actually figure out” how the ‘New Keynesian’ model with its Euler conditions — “based on the assumption that people have perfect access to capital markets, so that they can borrow and lend at the same rate” — really works. According to Krugman, this shouldn’t be hard at all — “at least it shouldn’t be for anyone with a graduate training in economics.”

aimage.pngBut if people — not the representative agent — at least sometimes can’t help being off their labour supply curve — as in the real world — then what are these hordes of Euler equations that you find ad nauseam in these ‘New Keynesian’ macro models going to help us?

Yours truly’s doubts regarding the ‘New Keynesian’ modelers’ obsession with Euler equations is basically that, as with so many other assumptions in ‘modern’ macroeconomics, the Euler equations don’t fit reality.

In a classic paper by Hansen and Singleton (1982) only very little support for the Euler equations was found, and in later paper by Canzoneri, Cumby, and Diba (2006) it was confirmed that there is vanishing little support for real people acting according to the Euler equatons

In the standard neoclassical consumption model — underpinning ‘New Keynesian’ microfounded macroeconomic modeling — people are basically portrayed as treating time as a dichotomous phenomenon today and the future — when contemplating making decisions and acting. How much should one consume today and how much in the future?

The Euler equation implies that the representative agent (consumer) is indifferent between consuming one more unit today or instead consuming it tomorrow. This importantly implies that according to the neoclassical consumption model that changes in the (real) interest rate and the ratio between future and present consumption move in the same direction.

So good, so far. But how about the real world? Is the neoclassical consumption as described in this kind of models in tune with the empirical facts? Not at all — the data and models are as a rule insconsistent!

In the Euler equation we only have one interest rate, equated to the money market rate as set by the central bank. The crux is that — given almost any specification of the utility function – the two rates are actually often found to be strongly negatively correlated in the empirical literature.

Theories are difficult to directly confront with reality. Economists therefore build models of their theories. Those models are representations that are directly examined and manipulated to indirectly say something about the target systems.

But being able to model a ‘credible world,’ a world that somehow could be considered real or similar to the real world, is not the same as investigating the real world. Even though all theories are false, since they simplify, they may still possibly serve our pursuit of truth. But then they cannot be unrealistic or false in any way. The falsehood or unrealisticness has to be qualified.

If we cannot show that the mechanisms or causes we isolate and handle in our models are stable, in the sense that what when we export them from are models to our target systems they do not change from one situation to another, then they only hold under ceteris paribus conditions and a fortiori are of limited value for our understanding, explanation and prediction of our real world target system.

But how do mainstream economists react when confronted with the monumental absence of empirical fit of their macroeconomic models? Well, they do as they always have done — they use one of their four pet strategies for immunizing their models to the facts:

(1) Treat the model as an axiomatic system, making all its claims into tautologies — ‘true’ by the meaning of propositional connectives.

(2) Use unspecified auxiliary ceteris paribus assumptions, giving all claims put forward in the model unlimited ‘alibis.’

(3) Limit the application of the model to restricted areas where the assumptions/hypotheses/axioms are met.

(4) Leave the application of the model open, making it impossible to falsify/refute the model by facts.

Sounds great doesn’t it?

Well, the problem is, of course, that ‘saving’ theories and models by these kind of immunizing strategies are totally unacceptable from a scientific point of view.

If macroeconomics has nothing to say about the real world and the economic problems out there, why should we care about it? As long as no convincing justification is put forward for how the inferential bridging between model and reality de facto is made, macroeconomic modelbuilding is little more than hand waving.

The real macroeconomic challenge is to face reality and still try to explain why economic transactions take place – instead of simply conjuring the problem away by assuming rational expectations, or treating uncertainty as if it was possible to reduce it to stochastic risk, or by immunizing models by treating them as purely deductive-axiomic systems. That is scientific cheating. And it has been going on for too long now.


Added December 09: In a comment on this post, we are directed to a recent post by Chris Dillow, in which it is argued that “economics is primarily a practical discipline” and since “the real world is a complex place” the solution is to pick models “that are good enough”. It is even maintained that since the world is so complex “there is a positive danger in seeking the truth.”

Well, that is in fact nothing but a (slight) variation of the usual fairy-tale told by mainstream economists in defense of their model Platonistic immunizing strategies. Dillow’s reasoning smacks a lot of Friedman’s instrumentalist immunizing strategy in which the value of model is said to have nothing to do with the ‘truth’ of the hypotheses (assumptions), but (only) with how good the model is in predicting things (which, if really believed in, would have put mainstream economics at rest for good more than a century ago …) In a typical Chicago economics fashion, theories and models are to be treated as something that has very little to do with any substantive content. Unfortunately, this only shows the  prevalent deep ignorance of epistemological and methodological thought among mainstream economists nowadays.



  1. Just to give you a taste for how bad the post I mentioned is:

    “In fact, in a complex world, there is a positive danger in seeking the truth.”

    • Sorry Lars, the post I mentioned where that quote comes from did not come up in the comments. It is this

      I was saying how the important message of your post (and that of people like Habermas) needs to be continually repeated.


      • Thanks for the link 🙂
        I usually appreciate reading Chris’s posts, but on this he’s just plain wrong, and unfortunately in a dangerous way.
        If I get some time off I’ll write a new post and elaborate why I think so.

      • I got a couple of minutes off — see the addendum at the bottom of the post 🙂

      • Chis Dillow is right. Quantum Mechanics is just a mathematical model with no real operating mechanism. There is no real collapsing of a wave function when someone takes a measurement, nor are there Many Worlds in which Lars Syll is a Professor.

  2. Gene I suggest you read this blog, especially the post he has of Habermas’s criticisms of positivist methodology in the social sciences.

    Another thing I keep seeing is this map analogy – models are like maps that do not capture all the detail of reality

    The truth is though that a map is a summary – of what ACTUALLY exists. It is like someone summarises the causes of WWI to get it into a concise, synthesised form. It is not the same as a model which is basically fiction with stories, sometimes quite ridiculous, made up to get a mathematical model often cases where maths really should not even be used.

    OK, now you might take your summary further and summarise how a war happened o get a theory about how wars in general happen. But when you do your own investigation (say of how the Syrian conflict started), you go from the ground up, from documented fact – quantitative and qualitatative including what cannot be put into mathematical models.

    Most likely what caused the financial crisis is precisely what is not convincingly portrayed in models or not in models at all – such as irrational behaviour. The answer to the crisis (the use of government bonds to deal with deflation) was also not in mathematical models – it came straight out of the General Theory – written by someone who was very critical, especially in his later life, of the use of models.

    Like any investigator, you don’t say “we can explain this with this model” – most likely you can – but is it the right explanation? You have to work each time from the ground up, like an investigator.

  3. Many thanks! Indeed while I would have expected such stuff from the likes of Sargent, or maybe even Krugman, from Chris Dillow it was surprising. Let’s just hope it was a one-off and he was having a bad day.

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