Monday, December 22, 2014

The limits of knowledge in economics, Part I.

I rather like this paragraph from Ed Leamer's Journal of Economic Perspectives piece on the utility and limits of econometrics:

Finally, I think that Angrist and Pischke are way too optimistic about the
prospects for an experimental approach to macroeconomics.  Our understanding
of causal effects in macroeconomics is virtually nil, and will remain so.  Don’t we
know that?  Though many members of our profession have jumped up to support
the $787 billion stimulus program in 2009 as if they knew that was an appropriate
response to the Panic of 2008, the intellectual basis for that opinion is very thin,
especially if you take a close look at how that stimulus bill was written.  
The economists who coined the DSGE acronym combined in three terms the
things economists least understand:  “dynamic,” standing for forward-looking decision
making; “stochastic,” standing for decisions under uncertainty and ambiguity; and “general equilibrium,” standing for the social process that coordinates and
influences the actions of all the players...that’s what we
do.  We seek patterns and tell stories [italics added].
The point is correct: among other things, we have nothing like the necessary degrees of freedom (not exactly the same as observations, but to a lay person, close enough) necessary to identify causal relationships in the macroeconomy with anything like certainty. We are now in our 11th business cycle since World War II, and as much as we like using high frequency data (I, for one, am guilty as charged), that really means in an important sense we have 11 observations about the post-War macroeconomy.

All that said, I did support the stimulus, because I have a Bayesian prior that Keynes was basically right.  In particular, the ideas that high unemployment can result from inadequate aggregate demand, and that in turn that high unemployment is an unrecoverable waste of resources, and, finally, that deficit spending can spur aggregate demand all make sense to me.

At the same time, George Akerlof lists example after example of how new classical macro-theory is rejected by empirical evidence (such as it is), while also showing that the empirical evidence, such as it is, is consistent with Keynesian predictions.  But this is still different from confirming that Keynes was right, something we are unable to do with data.

So back to Leamer. Elsewhere in the paper, he talks about three-valued logic: the ability to use evidence to come to a yes, and no, or an I don't know.   The honest thing to say about macroeconomics is "I don't know."  Alas, while the world is uncertain, policymakers still need to make policy decisions.

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