knzn explains why he is a Keynesian:
Bullish It, by knzn: ...Smith’s blog leads me to think about the issue of macroeconomics as a field. It seems (especially from the comment thread) that the Old Keynesians and the New Monetarists are at each other’s throats (but, interestingly, the newly christened Market Monetarists – who have some claim to being the legitimate intellectual heirs of the Old Monetarists – basically seem to be on the same side as the Old Keynesians on the major issues here; and the New Keynesians can break for either side depending on whether they’re more Keynesian or more New). Obviously I’m more sympathetic to the Old Keynesians than the New Monetarists, otherwise maybe my pseudonym would be “dsge” instead of “knzn.”
Here’s my take: to begin with, economics is basically bulls**t. I mean, it’s necessary bulls**t, sometimes even useful bulls**t, but I’m extremely skeptical of people who think economics is a science or that it could be a science. We have to make policy decisions (and investment decisions and personal consumption decisions etc.), and we have to have some basis for making them. We could just use intuition, and we often do, but it’s helpful to use logical thought and empirical data also, and systematic study using fields like economics can help us to clarify our intuition, our logical arguments, and our interpretation of the empirical data. The same way that bulls**t discussions that don’t make any pretense at being science can help.
Economics is bulls**t because it relies on the premise that human beings behave in a systematic way, and they don’t. Once you have done enough research to convince yourself that they behave in a certain way, they will change and start behaving in another way. Particularly if they read your research and realize that you’re trying to manipulate them by expecting them to continue behaving the way they have. But even if they don’t read your research, they may change the way they behave just because the zeitgeist changes – cultural sunspots, if you will.
The last paragraph may vaguely remind you of the Lucas critique. Lucas basically said that macroeconomics (as it was being practiced at the time) was bulls**t, but he held out the hope that it could receive micro-foundations that wouldn’t be bulls**t. The problem with Lucas’ argument, though, is that microeconomics is also bulls**t. And Noah Smith, writing some 36 years after the Lucas critique and observing its unwholesome results, takes it one step further by saying, if I may paraphrase, “Yes, the microeconomics upon which modern macro has now been founded is indeed bulls**t, but if we do the micro right, then we can come up with non-bulls**t macro.”
Yeah, I doubt it. Maybe we can come up with slightly better macro than what we’ve got now, but the underlying micro is never going to be right. Experimental results involving human subjects are inevitably subject to the micro version of the Lucas critique: once the results become well-known, they become part of a new environment that determines a new set of behavior. And the zeitgeist will screw with them also. And so on. And in any case, even if the results were robust, I’m skeptical that we can really build them into a macro model or that it would be worth the trouble even if we could. Economics will always be bulls**t.
Now there’s a case for doing rigorous bulls**t, at least as a potentially useful exercise. That’s what I think DSGE modeling is: it’s a potentially useful exercise in rigorous bulls**t. And I don’t begrudge the work of people like Steve Williamson: I think there's some rigorous bulls**t there that may be worth talking about. But in general, when it comes to bulls**t, there is not a monotonic relationship between rigor and usefulness. And to put all your eggs in the rigorous bulls**t basket – not only that, but in one particular type of rigorous bulls**t basket, because rigor does not live by rational equilibrium alone – is something that not even Pudd’nhead Wilson could advocate.
So I’m going to stick with sloppy Old Keynesian models as my main mode of macroeconomic analysis. They’re bulls**t. They’re not rigorous bulls**t. But as bulls**t goes, they’re pretty useful. A lot more useful than unaided intuition. And they’re easy enough to understand that we can have a reasonable idea of where their unrealistic assumptions are likely to lead us astray. Of course all economic models have unrealistic assumptions, but hopefully our intuition allows us to correct for that condition when applying the models to the real world. If the model is too complicated for the typical economist to understand how the assumptions generate the conclusions, then the unrealism becomes a real problem.
When you need an answer fast to a question that the newer models don't address sufficiently, and there are many important questions that fall into this category, and when you don't have time to build a new model before needing to answer -- a situation policymakers face constantly -- then the Old Keynesian IS-LM/MP model can fill the void. It is very easy to use for most questions, in part because it has been explored so thoroughly over the decades. I suspect knzn faces this situation often in his job in finance, i.e. he needs an answer today, wants a model for guidance, doesn't have time to build a full blown dsge model, simulate it, etc. and the IS-LM/MP model can fill the void.
But if this approach is adopted, I think it's important not to forget the lessons of the more modern models. For example, the old and new IS curves differ by how they handle expectations of the future. The new model accounts for this, the old models don't. If changes in expectations about the future are arguably unimportant, and other important differences in the models are similarly unimportant, then the old IS-LM/MP model can provide a good approximation. But when these expectations are important, using the old models can cause you to miss important feedback effects from the expected future to the actual present.
The best of both worlds is, I think, better than either alone. The art is knowing what is "best" in each of the two models.