"Measure what is measurable, and make measurable what is not so." - Galileo Galilei
"I appear to be wiser than he, because I do not fancy I know what I do not know." - Socrates
Writing some of my recent posts has gotten me thinking a lot about economics as a science. It seems to me that all too few economists view their field the way natural scientists do their own - as a potential tool for understanding and mastering the Universe. Plenty of economists value models that are "interesting" or "thought-provoking," that tell "good stories," or that have a priori plausible assumptions. That is how journalism or philosophy works, but it is not how Science works.
So it is extremely gratifying and refreshing to hear leading economists stick up for two of the key elements of science: observation and doubt.
[T]he theory of outlier events doesn’t actually say that they cannot eventually be predicted. Many of them can be, if the right questions are asked and we use new and better data. Hurricanes, for example, were once black-swan events. Now we can forecast their likely formation and path pretty well, enough to significantly reduce the loss of life. Such predictions are a crucial challenge in economics, too, and they are why data collection need not be a dull or a routine field...
Armchair scientists will never get far; observation makes all the difference. Think of the advances that came with the microscope and telescope. So it is with measurements in economics, too.
I produced a century-long series of home prices, which revealed how unusual the housing-price boom was [in the mid-00s]. General talk about the nature of bubbles didn’t convince many people that a bubble was forming, but the data I collected did convince at least some that we were in a very risky and historically unparalleled situation...
We need another measurement revolution like that of G.D.P. or flow-of-funds accounting. For example, Markus Brunnermeier of Princeton, Gary Gorton of Yale and Arvind Krishnamurthy of Northwestern are developing what they call “risk topography.”...We should respond just as we did to the Depression, by starting the long process of redefining our measurements so we can better understand the risk of another financial shock. (emphasis mine)
This is absolutely right. To figure out how the world works, you have to actually look out the window. The revolution in astronomy in the 1600s - which led to and motivated the invention of physics itself - depended crucially on improvement in telescopes, like the ones invented by Galileo and Newton. Similarly, we didn't correct classical physics (with relativity and quantum mechanics) until we mastered electricity and observed electric phenomena that didn't square with existing theories.
As Shiller notes, the big data revolution in econ came after the Depression, when we invented things like the National Income and Product Accounts. All the macro we have today, from RBC to New Keynesian models to more outlandish stuff, is an attempt to explain what we see in the NIPA. Those theories are extremely limited; if we're going to improve upon them, we need better data, not just to pick from the cornucopia of models we have now, but to develop new and more useful ones. Shiller talks about better financial data (also see Hernando de Soto on that subject), but another source of good data is coming from experimental economics, which is rapidly becoming more central to the field.
But to find theories that work, we also need another pillar of the scientific approach: doubt. That is why I was pretty happy to see Greg Mankiw write this in the Times:
After more than a quarter-century as a professional economist, I have a confession to make: There is a lot I don’t know about the economy. Indeed, the area of economics where I have devoted most of my energy and attention — the ups and downs of the business cycle — is where I find myself most often confronting important questions without obvious answers...
The inflation rate that the economy gets is, in large measure, based on the inflation rate that people expect...Even if expectations are as important as the conventional canon presumes, it isn’t obvious what determines those expectations. Are people merely backward-looking, extrapolating recent experience into the future? Or are the expectations based on the credibility of policy makers? And if credibility matters, how is it established? Are people making rational judgments, or are they easily overcome by fear and influenced by extraneous events?...
I just cannot express how refreshing it is to see this kind of scientific humility being expressed by one of macroeconomics' most respected practitioners. Yes, Mankiw is using doubt to score political points over his opponents; the ideas about which he waxes skeptical are things like "We should worry about unemployment more than inflation" and "The U.S. government can safely borrow more money." But that's absolutely fine! There will be plenty of people on the other side of the political spectrum to cast doubt on the idea that we should worry about inflation and deficits. Don't worry.
Because something bigger is at stake here. By invoking doubt, and by admitting his ignorance and the limitations of his models, Greg Mankiw is doing the economics field a great service. Mankiw is probably the ultimate virtuoso practitioner of macro's dominant DSGE paradigm. By admitting that that paradigm has failed to answer some of its own central questions, he is reminding us that - in a field filled with chest-thumping and argument-from-authority - the crucial idea of scientific doubt is not quite dead.
No comments:
Post a Comment