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Your comment: 'Continuously readjusting non-explanatory models to fit new data isn't what a science does. ' is too optimistic.

I guess by 'causal mechanical' you mean dynamical models, and explicitly not regression or stochastic schemes? If so, fitted models like the ones I mentioned are still the best tools available in some noisy physical sciences, I'm thinking hydrology in particular, and older but still used atmospheric subgrid parameterisations.

Nevertheless, you're right to prefer a dynamical approach where available. I suspect though, as others in the thread have noted, that the system is simply unpredictable at some of the time scales we'd like it to be, and that it might turn out that simple models explain most of the predictable variance.

Actually, in Astronomy the invariance of the laws of nature is subject to verification. The most flashy example I'm aware of is that in supernovas, all of the elements in the periodic table, including the really short half-life elements, are produced. These elements decay according to their individual nature, and that decay can be observed through the fall-off in the brightness of their spectrum lines. Each of the elements always decays at exactly the rate it would on Earth, no matter where in the observable universe the supernova occurs.

Ok, now: I actually agree with you that Wilkinson goes astray when he attempts to prescribe a particular alternative approach that would be “better science.” But his *criticisms* are on-target. Your response is actually the one that proves too much, because it could be made just as strongly on behalf of Christian apologetics, astrology, Lysenkoism, Marxist dialectics, acupuncture, chiropractics, natural law, Freudian psychotherapy, … in short, any discursive practice that combines reasoned disagreement with a method of processing this disagreement into an acknowledged “canon.”

Now, Wilkinson wants to use the science/not-science distinction to separate astronomy from astrology; I actually think that particular dichotomy muddles things more than it helps. As I said in my reply to pushmedia1, we need an approach that blends pragmatism and social epistemology: what we want to know is *which* bodies of “expertise” warrant epistemic authority *and in which contexts*. So: look to the web of belief and action; how the knowledge-producing communities impinge upon the knowledge-using communities, the feedback mechanisms between theory and practice (what's taken as “disconfirming,” what isn't); that sort of thing.

When we do that, we see that physics and chemistry, through their interpenetration with engineering and problem-solving more prosaically, haven't just made predictions or offered plausible explanations; their claims have become so thoroughly integrated within everything we do that we confirm, if not their “truth,” then at least their reliability, every time we wake up and turn on a light-switch.

Macro-economics? Not so much. Sure, I'm sure you and pushmedia1 see DSGE models confirmed in what you read in the news and in history, but plenty of others just as smart as you think that *completely incompatible* approaches make sense of things, and that macro-astrology would be just as persuasive as macro-economics if it put as much brainpower and CPU cycles into refining the models to fit the data. Sure, it's crazy to think that the differential gravitational fields of heavenly bodies determines our fates in the way that such a macro-astrology would say … but then, it's just as crazy to think that our economy is populated by agents acting out their parts in the solution to an infinite-period stochastic game of utility-function maximization.

Leaving issues of semantics aside, is there something fundamentally wrong with this? The scientists above aren't claiming to do anything more than predict, and they predict successfully.

Now, I _don't_ think this is the position modern macro is in. As best as I can tell, macro has failed as a predictive science. I also don't think that explaining causal relationships is worthless – it tends to do a good job of predicting, in fact. It's just not strictly necessary for prediction, which seems to be a legitimate endeavor, whether or not you want to call it science.

The movements of heavenly bodies prompt *extremely* intuitive, yet false, astronomical theories; a heliocentric solar system is about as classic a case of a counterintuitive scientific finding as you can get, up there with inertia.

Whereas one of the constants throughout the emergence of modern markets is the outrage they provoke precisely because they seem *unnatural*.

As for why most of the natural sciences, collectively understood, have earned epistemic authority in a way that economics has not: they're part of a web of belief that impinges on empirical experience so thoroughly and pervasively that about the only alternative to physics & chemistry getting things more or less “right” (however you cash out “right”) is to presume that something like a Cartesian Demon is just messing with us, or we're in the Matrix, or something. (And those possibilities have no practical implications.)

What's more, this tight integration between basic science, engineering, and everyday problem-solving doesn't merely validate the corpus of knowledge at any given time; it also helps us when trying to evaluate the *institutional epistemic authority* of various methods for the producing and distributing knowledge.

When it comes to depressions, macro is more successful as a descriptive science than as a prescriptive one. Krugman's essay omitted a hugely likely possibility which is: nobody knows how to prevent depressions. Really big crashes come around so infrequently, have so many contributing factors and are so specific to their local circumstances that we just don't have a solid, well-tested theory about how to stop them. Which almost goes without saying. Sure, there are policies in place, but if they work at “preventing a depression” the depression doesn't happen so we have no way of knowing that they worked; we can't logically distinguish “it worked” from “we had a lucky run”. We only notice the failures.

From one point of view, 70 years without a depression is a pretty good run and indicates we're doing something right. It's only a problem if you think preventing all depressions is possible. Krugman apparently thinks it is, so he wants to make sure the next team has the right combination of strategies from Team A and Team B. But if he's mistaken, then this crash only tells us that economists are fallible with respect to giving advice that will entirely prevent depressions. Just as meteorologists are fallible with respect to hurricane-prevention advice. It doesn't necessarily mean the field is in crisis; it might just mean we should dial back our unreasonable expectations a bit.

I suspect the difference between astronomy and macroeconomics is we have very few intuitions about the former and lots about the latter. When an astronomer makes crazy assumptions to get her result, we shrug our shoulders because whatever she's making a assumptions about are so unfamiliar. Economists make assumptions about human psychology and other stuff that everyone thinks they know about. Our crazy simplifications are more obvious and more intimately unreasonable.

But I'll punt the ball a bit further down field by asserting that as champions of liberty we can't have our cake and eat it too. It seems awkward to hold the following two positions simultaneously: i. that nothing the government can do will have any effect, and ii. that everything government does has a bad outcome. The arguments for the first conclusion — that individuals will factor in government actions thereby neutralizing it–seem to run counter to the arguments Peter's making–that government agencies are as subject to cognitive bias as anyone, and will enact policies that have bad outcomes. There's a case for the G-man, now and then.

I think it's fair enough to make the following claims. Free market capitalism–words ordered for priority–is the best approach to managing scarcity we've ever come up with, and works really well. Except when it doesn't. And when it doesn't, it's not the fault of free market capitalism. It's because us semi-evolved simians aren't good enough for it. But where none of us, as individuals, is tall enough to grab the banana, we can overcome our base natures from time to time, and work together (monkey pyramid, go!).

I think a slightly better way to think of it is to say that any collective action needs to be justified on its merits. How? Well, as in the case of (say) financial market crises, or even something as banal as a good ol' fashioned bank run, we can apply the grease of our monkey minds to the machinery of the (as Will puts it) “sometimes illuminating … counterfactual worlds”.

We're gonna make mistakes. We're gonna forget. It isn't going to be perfect or lovely or soviet-ice-cream-on-every-street-corner, but it's at least reasonable, no?

Or it could st as well be that we can expect a lot from government intervention! The question becomes, under what circumstances?

I mean, I think holding up Hajek's thinking on the importance of information in market economies, and the way localized decisions propagate into the macro world is a bit of grasping at straws. Hajek was writing before we understood the importance of systematic (ie. predictable) biases in human cognition. When I read Hajek now I'm struck by the profundity of his insight about the importance of price, and his naivety about how people process questions of value.

When Keynes (and even economists like Thorsten Veblen, and John K. Galbraith) made claims about “animal spirits”, or “It is better to fail conventionally than to succeed unconventionally.”, their underlying point, though expressed with more pith and less rigor, sounds a lot like confirmation bias.

Which is (I think) Krugman's point. Today, we have a rigorous and 'lab tested' basis for believing a) that agents in markets are not rational, and b) for reasoning about those biases. A small idea, like Keynes' paradox of thrift illustrates the point nicely.

The paradox of thrift arises when a large number of local decision makers deciding between savings and consumption find themselves irrationally restrained by the 'anchoring effect' or 'focusing effect' (where recent information is emphasized over a longer term view). Keynes observed this behavior during the early years of the depression. It's much in evidence recently.

What to do? Getting out of this non-optimal equilibrium involves acting to counter the widespread bias. Which means collective action. Which means government intervention.

“Economic theory is essentially a collection of models. Broad insights that are not expressed in model form may temporarily attract attention and even win converts but they do not endure unless codified in a reproducible – and teachable – form. You may not like this tendency; certainly economists tend to be too quick to dismiss what has not been formalized (although I believe that the focus on models is basically right). Like it or not, however, the influence of ideas that have not been embalmed in models soon decays.” (Krugman, P. 1995. Development, Geography and Economic Theory. Cambridge: MIT Press. p.27)

1. You have misunderstood science and especially economics qua (quasi-)science. Science generates if-then statements that have predictive power. Science does not explain. It especially does not explain causality. Starting from that position of epistemological modesty, it's simply irrelevant whether macro models' starting assumptions correspond well to the real world. Nope, what matters is not whether the assumptions are realistic, but instead whether the if-then statements generated by deduction from those assumptions have strong predictive power. Non-Euclidean geometry has some crazy assumptions (well, one missing realistic assumption), but nonetheless somehow generates if-then statements with high predictive power.

Critics of macro (and econ generally) really are missing the point when they criticize macro's admittedly silly assumptions. You instead should be focusing on whether the if-then statements fit the data.

2. It's a waste of time to debate whether economics is a “science.” So what if it is, so what if it isn't? It tries to generate predictive hypotheses. It does a pretty good job at it. If science, then [what?]. If not science, then [what?]. Angels dancing on a pin….

3. This statement of yours is just false. Regardless of whether a “science,” macro will be persuasive so long as its if-then statements have predictive power.

“But we can’t count on elite economists to admit it, since their claim to authority on matters of public policy stands or falls with their claim to scientific expertise.”

3. The distance between the freshwater and the saltwater econocamps is less than popularly imagined. The market drive toward product differentiation is esp strong in the academic market.