Saturday, August 29, 2015

Not too simple: Just wrong

Simon Wren-Lewis has a nice post discussing Paul Romer’s critique of macro.

In Simon's words:

"It is hard to get academic macroeconomists trained since the 1980s to address [large scale Keynesian models] , because they have been taught that these models and techniques are fatally flawed because of the Lucas critique and identification problems."

"But DSGE models as a guide for policy are also fatally flawed because they are too simple. The unique property that DSGE models have is internal consistency."
"Take a DSGE model, and alter a few equations so that they fit the data much better, and you have what could be called a structural econometric model. It is internally inconsistent, but because it fits the data better it may be a better guide for policy."
Nope! Not too simple. Just wrong!

I disagree with Simon. NK models are not too simple. They are simply wrong. There are no ‘frictions’. There is no Calvo Fairy. There are simply persistent nominal beliefs.



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  2. Roger, what do you think about this model from Cochrane:

    Also, are you willing to put your model in a head to head forecasting competition with other macro models (either standard or non-standard)? The 2nd reference in this paper has a model and issued a challenge to macro modelers a year ago, but nobody took him up on it:

    Although he does get feedback from some macro folks once in a while, like here (from Scott Sumner):

    Here's the challenge from last year:

    He's been comparing his model against a Fed model, but no models from professional macro modelers such as yourself. He's provides occasional updates about how he's doing against the Fed, and about the status of his forecasts for several countries.

    If you want to know more about the framework he developed, here's a post about his draft paper he's put together to describe it:

    But I'm not stuck on that framework or model set in particular (it's just the one I'm most familiar with): I'd just love to see some head to head macro model forecasting competition in general. Wouldn't that make macro more exciting? Help nail the lid down on the "Wrong!" models once and for all? Separate the wheat from the chaff, etc?

  3. Are forecasting exercises useful to compare models? Yes. But John has a point. Model comparison is a serious exercise. And those with a horse in the race will not easily be convinced that they were wrong when a couple of data points go against them. They will claim, as have the New Keynesians, that their model was missing a piece: for example, a financial sector.

    1. Well, here are a couple of posts comparing his forecasts to the FED's DSGE model:

      It looks like in that last one he's saying it's still basically a "tie." Do you have a model you'd put up against the Fed's DSGE model? I'd love to see more comparisons like that.

      What's interesting is that his model predicts a maximum inflation rate for an economy (which is governed by a very slowly changing parameter). So he can predict which countries will end up like Japan: seemingly unable to move inflation upwards much. In other words, it seems to me like he's offering an explanation for what John was looking for in his post.

      For example, in July of 2014, Jason's model predicted that Canada would start to undershoot it's inflation target by the end of this year because it's starting to transition from one domain (QTM) to the next (non-QTM). He's got quite a few countries he's looked at in this regard (perhaps 20 or so?) to see where they're at.

      And unlike the "New Keynesians" you speak of, he says he's not too interested in adding "epicycles" to patch up his model if evidence disagrees. He's stated that if it looks like the data is going against his framework, he'll write a post-mortem and abandon it. As it stands he gets by with just a small number of parameters in most of the models (about 3 or so) that he must fit to historical data.


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