by David Andolfatto’s DSGE flimflam David Andolfatto — vice president at Federal Reserve Bank of St. Louis — has a post up on his blog trying to defend the much criticised use of DSGE models. According to Andalfatto ‘to help organize our thinking’, it is often useful to construct mathematical representations of our theories — not as a substitute, but as a complement to the other tools in our tool kit (like basic intuition).This is a useful exercise if for no other reason than it forces us to make our assumptions explicit, at least, for a particular thought experiment. We want to make the theory transparent (at least, for those who speak the trade language) and therefore easy to criticize. We’ve heard this line of ‘defence’ before, and it’s as little convincing as ever. But as extra ammunition in defending DSGE for policy issues, Andolfatto refers us to an interview with Nobel laureate Tom Sargent. So let’s see if there’s anything in that interview that would make us believe in this ‘help us organise our thinking’ fairytale. Sargent gives the following defense of ‘modern macro’ (my emphasis): Sargent: I know that I’m the one who is supposed to be answering questions, but perhaps you can tell me what popular criticisms of modern macro you have in mind. Rolnick: OK, here goes.
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David Andolfatto’s DSGE flimflam
David Andolfatto — vice president at Federal Reserve Bank of St. Louis — has a post up on his blog trying to defend the much criticised use of DSGE models. According to Andalfatto
‘to help organize our thinking’, it is often useful to construct mathematical representations of our theories — not as a substitute, but as a complement to the other tools in our tool kit (like basic intuition).
This is a useful exercise if for no other reason than it forces us to make our assumptions explicit, at least, for a particular thought experiment. We want to make the theory transparent (at least, for those who speak the trade language) and therefore easy to criticize.
We’ve heard this line of ‘defence’ before, and it’s as little convincing as ever. But as extra ammunition in defending DSGE for policy issues, Andolfatto refers us to an interview with Nobel laureate Tom Sargent.
So let’s see if there’s anything in that interview that would make us believe in this ‘help us organise our thinking’ fairytale. Sargent gives the following defense of ‘modern macro’ (my emphasis):
Sargent: I know that I’m the one who is supposed to be answering questions, but perhaps you can tell me what popular criticisms of modern macro you have in mind.
Rolnick: OK, here goes. Examples of such criticisms are that modern macroeconomics makes too much use of sophisticated mathematics to model people and markets; that it incorrectly relies on the assumption that asset markets are efficient in the sense that asset prices aggregate information of all individuals; that the faith in good outcomes always emerging from competitive markets is misplaced; that the assumption of “rational expectations” is wrongheaded because it attributes too much knowledge and forecasting ability to people; that the modern macro mainstay “real business cycle model” is deficient because it ignores so many frictions and imperfections and is useless as a guide to policy for dealing with financial crises; that modern macroeconomics has either assumed away or shortchanged the analysis of unemployment; that the recent financial crisis took modern macro by surprise; and that macroeconomics should be based less on formal decision theory and more on the findings of “behavioral economics.” Shouldn’t these be taken seriously?
Sargent: Sorry, Art, but aside from the foolish and intellectually lazy remark about mathematics, all of the criticisms that you have listed reflect either woeful ignorance or intentional disregard for what much of modern macroeconomics is about and what it has accomplished. That said, it is true that modern macroeconomics uses mathematics and statistics to understand behavior in situations where there is uncertainty about how the future will unfold from the past. But a rule of thumb is that the more dynamic, uncertain and ambiguous is the economic environment that you seek to model, the more you are going to have to roll up your sleeves, and learn and use some math. That’s life.
Are these the words of an ’empirical’ and ‘transparent’ macroeconomist? I’ll be dipped! To me it sounds like the same old axiomatic-deductivist mumbo-jumbo that parades as economic science of today.
Mainstream economic theory today is in the story-telling business whereby economic theorists create make-believe analogue models of the real economic system. This modeling activity is — as both Andolfatto and Sargent give ample evidence of — considered useful and essential. Since fully-fledged experiments on a societal scale as a rule are prohibitively expensive, ethically indefensible or unmanageable, economic theorists have to substitute experimenting with something else. To understand and explain relations between different entities in the real economy the predominant strategy is to build models and make things happen in these “analogue-economy models” rather than engineering things happening in real economies.
Formalistic deductive “Glasperlenspiel” can be very impressive and seductive. But in the realm of science it ought to be considered of little or no value to simply make claims about the model and lose sight of the other part of the model-target dyad.
Mainstream economics — and especially of the Chicago ilk — has since long given up on the real world and contents itself with proving things about thought up worlds. Empirical evidence only plays a minor role in economic theory, where models largely function as a substitute for empirical evidence. But, hopefully humbled by the manifest failure of its theoretical pretences, the one-sided, almost religious, insistence on axiomatic-deductivist modeling as the only scientific activity worthy of pursuing in economics will give way to methodological pluralism, relevance, and realism, rather than formalistic tractability.
I remember attending the first lecture in Tom Sargent’s evening macroeconomics class back when I was in undergraduate: very smart man from whom I have learned the enormous amount, and well deserving his Nobel Prize. But…
He said … we were going to build a rigorous, micro founded model of the demand for money: We would assume that everyone lived for two periods, worked in the first period when they were young and sold what they produced to the old, held money as they aged, and then when they were old use their money to buy the goods newly produced by the new generation of young. Tom called this “microfoundations” and thought it gave powerful insights into the demand for money that you could not get from money-in-the-utility-function models.
I thought that it was a just-so story, and that whatever insights it purchased for you were probably not things you really wanted to buy. I thought it was dangerous to presume that you understood something because you had “microfoundations” when those microfoundations were wrong. After all, Ptolemaic astronomy had microfoundations: Mercury moved more rapidly than Saturn because the Angel of Mercury left his wings more rapidly than the Angel of Saturn and because Mercury was lighter than Saturn…
Andolfatto — not to mention Sargent — seems to be impressed by the ‘rigour’ brought to macroeconomics by new classical DSGE models and its rational expectations, microfoundations and ‘Lucas Critique’.
It is difficult to see why.
Take the rational expectation assumption for example. Rational expectations in the mainstream economists’s world implies that relevant distributions have to be time independent. This amounts to assuming that an economy is like a closed system with known stochastic probability distributions for all different events. In reality it is straining one’s beliefs to try to represent economies as outcomes of stochastic processes. An existing economy is a single realization tout court, and hardly conceivable as one realization out of an ensemble of economy-worlds, since an economy can hardly be conceived as being completely replicated over time. It is — to say the least — very difficult to see any similarity between these modelling assumptions and the expectations of real persons. In the world of the rational expectations hypothesis we are never disappointed in any other way than as when we lose at the roulette wheels. But real life is not an urn or a roulette wheel. And that’s also the reason why allowing for cases where agents make ‘predictable errors’ in DSGE models doesn’t take us any closer to a relevant and realist depiction of actual economic decisions and behaviours. If we really want to have anything of interest to say on real economies, financial crisis and the decisions and choices real people make we have to replace the rational expectations hypothesis with more relevant and realistic assumptions concerning economic agents and their expectations than childish roulette and urn analogies.
‘Rigorous’ and ‘precise’ DSGE models cannot be considered anything else than unsubstantiated conjectures as long as they aren’t supported by evidence from outside the theory or model. To my knowledge no in any way decisive empirical evidence has been presented.
No matter how precise and rigorous the analysis, and no matter how hard one tries to cast the argument in modern mathematical form, they do not push economic science forwards one single millimeter if they do not stand the acid test of relevance to the target. No matter how clear, precise, rigorous or certain the inferences delivered inside these models are, they do not per se say anything about real world economies.
Proving things ‘rigorously’ in DSGE models is at most a starting-point for doing an interesting and relevant economic analysis. Forgetting to supply export warrants to the real world makes the analysis an empty exercise in formalism without real scientific value.