Science is about discarding models, not making them

As someone who is preparing to apply for jobs as a professional economist, I can't help feeling down when I see Paul Krugman write something like this:

I’ve never liked the notion of talking about economic “science”...Still, when I was younger I firmly believed that economics was a field that progressed over time, that every generation knew more than the generation before. 

The question now is whether that’s still true...I think you can actually make the case that in important ways the profession knew more in 1971 than it does now... 

[M]any economists aren’t even trying to get at the truth. When I look at a lot of what prominent economists have been writing in response to the ongoing economic crisis, I see no sign of intellectual discomfort, no sense that a disaster their models made no allowance for is troubling them; I see only blithe invention of stories to rationalize the disaster... 

And all this makes me wonder what kind of an enterprise I’ve devoted my life to.

Paul Krugman is one of my personal heroes; it was the brilliance of his theories that lured me to the profession in the first place. So it makes me pretty sad to hear him questioning the value of the whole enterprise.

But I can't really disagree with his characterization. There's a reason you keep seeing these "is economics a science?" posts popping up around the blogosphere. The crisis made a lot of people question the value of economics, in its current form, as a useful tool for understanding and affecting the world. But when many economists seemed not to experience similar doubts, it raised the question of whether the profession approaches the world in a scientific way.

About 400 years ago, see, humans discovered a new way of understanding and interacting with the world, which seemed to work a lot better than what we had been doing before. The new approach involved things like doing experiments, writing down models, and observing the natural world. But what exactly was so great about this approach, which we called "science"? What were the key features of this new approach that made it so much more effective? If we have the models without the experiments, or vice versa, will we still get the same results?

I believe that we - some of us, anyway - have had a good answer to this question for a long time. The answer is that science works when it has a way to discard ideas that do not work. People have phrased this answer in different ways. Francis Bacon called it eliminative induction. Karl Popper called it "falsifiability." Richard Feynman called it "doubt." But it's the same idea. You actively look for what doesn't work, and throw it out.

Economists, I think, do not always see this as the essence of science. For example, here is Scott Sumner, in March 2011:

I’ve always thought that the debate over whether economics is a science is actually a debate about the meaning of the term ’science.’  If science is when people build models to better understand the world around us, then economics is a science.

And here is Stephen Williamson:

I looked up a definition of "science," and came up with this:

The intellectual and practical activity encompassing the systematic study of the structure and behavior of the physical and natural world through observation and experiment. 

So, as economists we are systematic, we study the structure of the economy and the behavior of individuals in it, and we observe and experiment. Thus, apparently, we are a science.

Now, far be it from me to argue with the Oxford English Dictionary. But I contend that the real question here is substantive, not semantic. Whether or not an object is an "airplane," the important question is whether it flies. And whether or not economics is a "science," the important question is whether or not it discards its bad ideas. 

Economics has several ways of discarding bad ideas. The most common is to use empirical data to reject models. One particularly effective way of doing this is to use "natural experiments". A second method is to use experiments, which can be laboratory experiments or field experiments. 

So, procedurally, economics is a science.

But there is a difference between what a field can do and what it does do. A field is not just a set of techniques, it is also an established culture that chooses when and how to use those techniques. It is in this sense that economics does not always live up to its potential as a science. 

What I am not talking about are models that are that non-testable. Economics does make some of these, but that's fine. These models may be interesting as pure mathematics, or they may be of use in doing future science, even though they themselves are not science. I don't lose any sleep over these.

What bothers me is that the economics profession, as a culture, does not always insist that the testable models be tested and discarded. When enough economists ignore the facts and keep believing in models that can and should be discarded, then even though economics is procedurally a science, culturally it is not behaving like one. Obviously, I am referring to most of the popular macro models in use before the crisis.

So I disagree very strongly with Scott Sumner. The heart of science is not building models, but discarding them. Economics as a discipline has the tools to prune its tree of models, but economics as a culture has not been using these tools harshly enough. And so we've ended up as a sort of massive supermarket of models, where we have a model (or twenty models) for any conceivable phenomenon, but little way of knowing which model we should use in which situation. Economists who protest that "we had plenty of models that described financial crises" can't answer the question of why nobody was paying attention to those models before the crisis slapped us in the face.

This, I believe, is why the public has become incredibly skeptical of our profession. We let ourselves get away with too much. When we saw data that flatly contradicted our favorite theories, we just shrugged and kept on believing. And many of us seem still to be doing this, even now. And that is why these philosophy-of-science blog posts keep coming and coming. As well they should.


(Note: Most of what I'm complaining about here, like much of what I write on this blog, really goes only for macro. Micro, which is just a lot easier to test, is generally much better about being "scientific." But the difficulty of testing macro models doesn't let the field off the hook...)

Miscellaneous Lucas

Someday I intend to write a book about the history of modern macroeconomics. I plan on having Bob Lucas be a pivotal figure in this book, so I'm always interested what he has to say, even though he is now pretty old. Here's an interview Lucas gave recently for the Wall Street Journal. Here's a few excerpts:

One [thing on Lucas' mind] is the failure of the European and Japanese economies, after their brisk growth in the early postwar years, to catch up with the U.S. in per capita gross domestic product. The GDP gap, which once seemed destined to close, mysteriously stopped narrowing after about 1970... 

For the best explanation of what happened in Europe and Japan, he points to research by fellow Nobelist Ed Prescott. In Europe, governments typically commandeer 50% of GDP. The burden to pay for all this largess falls on workers in the form of high marginal tax rates..."The welfare state is so expensive, it just breaks the link between work effort and what you get out of it, your living standard," says Mr. Lucas. "And it's really hurting them."

Now, like I said, Lucas' age really does excuse him in a lot of cases. But doesn't he know that Japan has lower taxes (and more work hours) than the U.S., not less? That supports the idea that high taxes make people work less, but it definitely contradicts the hypothesis that taxes are behind the GDP gap. 

It's always struck me as kind of amazing how many economic phenomena Lucas and Prescott and others of their generation ascribe to marginal tax rates, even when it obviously makes no sense to do so.I guess it just goes to show how deep an imprint the high tax rates of the postwar period made on the minds of the economists who brought down that tax regime in the 70s and 80s.

Anyway, more Lucas:

Turning to the U.S., he says, "A healthy economy that falls into recession has higher than average growth for a while and gets back to the old trend line. We haven't done that. I have plenty of suspicions but little evidence. I think people are concerned about high tax rates, about trying to stick business corporations with the failure of ObamaCare, which is going to emerge, the fact that it's not going to add up. But none of this has happened yet. You can't look at evidence. The taxes haven't really been raised yet."

Lucas is being intellectually honest here. The line that Obama is keeping the economy from recovering by being a scary socialist has by now become a standard conservative argument, from the most disreputable hacks on CNBC all the way up to the lofty ranks of the Nobel-wielding demigods. But Lucas admits what few others will say, which is that this line is a guess and a hunch and a supposition, not the result of any economic theory or empirical work. Obama's attitude, even more than his policies, just feel wrong to conservatives, and they feel like this must be what is causing macroeconomists' models to break.

Here's Lucas on Rational Expectations:

"If you're going to write down a mathematical model, you have to address that issue. Where are you supposed to get these expectations? If you just make them up, then you can get any result you want."

This is true. But my problem with Rational Expectations is kind of the flip side of this statement; if you don't care about what result you get, you can make up anything you want! 

Do people have rational expectations? Sometimes they do. And sometimes they don't. I recently did an experiment in which people invested in a little toy financial market. Even the people who demonstrated that they understood the asset's value perfectly well also reported that they didn't believe that the market price would converge to that value. When there was a price bubble, even the savviest traders didn't predict a crash, and they were taken completely by surprise when the crash came. That kind of outcome just doesn't gel with Rational Expectations.

The moral of the story is that you can't derive people's expectation process just from deductive logic. You have to go see how people really behave.

Lucas on "foxhole Keynesianism":

Mr. Lucas believes Ben Bernanke acted properly to prop up the system. He doesn't even find fault with Mr. Obama's first stimulus plan. "If you think Bernanke did a great job tossing out a trillion dollars, why is it a bad idea for the executive to toss out a trillion dollars? It's not an inappropriate thing in a recession to push money out there and trying to keep spending from falling too much, and we did that."

It's interesting that this position would be contradicted by Lucas' own preferred macro models. I guess this just goes to show how deep the intuitive sympathy for Keynesian ideas runs, even among the titans of neoclassical macro. 

At any rate, although I disagree with a lot of what Lucas says, I've got to hand it to him: even at his age, he shows a decent amount of nuance and skepticism. That's great to see.

Update: However, As Brad DeLong points out, Lucas' position on stimulus is not exactly clear and consistent over time...

Update 2: Paul Krugman has a great summary of where Lucas fits into the history of modern macro. Now doesn't that story deserve a whole book? ;-)

Has Steve Williamson proved that our Universe is non-causal?

Steve Williamson has written a review of John Quiggin's Zombie Economics that is based neither on flippancy nor personal insults. Kudos to Steve! I encourage everyone to read the whole thing, which also serves as a pretty good gloss of the entire field of modern macro.

Which is not to say that I agree with everything Williamson writes. Far from it. For example, Williamson defends economists' failure to predict the financial crisis by appealing to the Efficient Markets idea:

By its nature, a financial crisis is an unpredictable event. We could have an excellent model of a financial crisis. The people living in the model world where the financial crisis can happen know it can happen, but they can’t predict it, otherwise they could profit in advance from that prediction. Similarly, an economist armed with the model will not be able to predict a crisis in the real world.

This idea can be generalized to the following principle:

"Assuming efficient financial markets, any event that has relevance for asset prices cannot be predicted in advance."

That is false. For example, consider large asteroid impacts. An impending asteroid impact is quite predictable with modern astronomy and good telescopes. You know when and where it will happen. And it definitely will have a large impact (heh) on asset prices. There is no efficient-markets paradox here. To see why, consider two possibilities:

Case 1: We cannot prevent asteroid impacts. If this is the case, the predictable effect of the asteroid will be incorporated into asset prices shortly after the astronomers confirm the impending event.

Case 2: We can and will prevent asteroid impacts. In this case, the asteroid impact won't happen (and will thus not have an effect on asset prices).

In Case 1, Williamson is wrong. Scientists can predict impending events, even though they can't profit from them. And society benefits from scientists' ability to predict the event (since we will have time to prepare and mitigate the effects of the disaster). The invention of modern astronomy turned what was previously unpredictable into something now quite predictable. John Quiggin is thus perfectly reasonable in calling for economists to improve their crisis-forecasting ability. The invention of better crisis forecasting techniques would not earn excess returns in financial markets, but would be of social benefit.

In Case 2, Williamson is semantically right but substantively wrong. If we knock the asteroid aside with a nuke, then technically, the impact never happened. But we know it would have happened if we hadn't acted. The fact that we stopped it from happening doesn't make the astronomers' prediction "wrong." In this case, "predicting" something really means making a contingent prediction: "IF we don't act, this thing will happen." John Quiggin is perfectly reasonable for asking economics to try to make predictions in this sense. If we were able to see a financial crisis coming and managed to head it off, I somehow doubt that Steve Williamson would fold his arms and snicker and say "See? Crisis didn't happen. Looks like you guys were wrong!"

Moral of the story: The EMH does not imply that we live in a non-causal Universe. That is a misuse of the idea. Predicting the future is often possible and socially beneficial, even when no one can use the predictions to make excess returns. And contingent predictions need not be reflected in prices at all. If you hear someone making the argument that the EMH absolves the econ profession from any responsibility to forecast future events...don't fall for it!

Great Stagnation...or Great Relocation?

"I was on top of the Westin Hotel being shown the sights of [Shanghai], and I had a sudden crisis as I looked out at the extraordinary skyscrapers the architecture and the art deco. I thought to myself, well, the mandate of heaven has passed from us and come home." - Gore Vidal, 2007

I'll say this about Tyler Cowen's Great Stagnation hypothesis: it has really made me think. Although I was resistant to it at first, the more I look at the evidence, the more compelling it seems. Income growth in the U.S. really has slowed down since the 1960s, and more recently, in all the rich countries.

Cowen's idea has much to recommend it. It's undeniable that the easy gains from universal public education and exploitation of cheap land are over. And it also seems pretty clear that there has been a stagnation in transportation technology since the mid-century, driven by the plateauing efficiency of our energy sources. There's a reason our innovation has switched from stuff like cars and planes to stuff like computers and phones.

On the other hand, the idea that our stagnation is driven by exogenous changes in scientific discovery - we just didn't find enough new stuff this half-century! - does not sit easily with me. One reason for this is that I have a very hard time believing that changes in the rate of technological progress could cause a decrease in per-capita incomes. Consider this graph of real working-age household income since 1987 (courtesy of Karl Smith):

I just have a hard time believing that a slowdown in scientific discovery could cause incomes to go down. I mean, technology doesn't get worse over time, right? (This is also one of the big problems that everyone has with RBC models.) I mean, mayyyyybe technology could stagnate so much that we hit a Malthusian ceiling, in which population growth increases resource costs to the point where people start getting poorer. But it just seems unlikely.

Therefore, I have been thinking about alternative theories to explain rich-world income stagnation. And I have come up with something. I call it the "Great Relocation". The idea, in a nutshell, is that economic activity is relocating from rich Europe, America, and Asia to developing Asia faster than technological progress can replenish it.

The idea of how this works is not due to me, but to Paul Krugman.

Economic Agglomeration and the New Economic Geography

In 2008, Paul Krugman won the Nobel Prize, in part for a theory that called the New Economic Geography. That also happens to be the first economic theory I ever learned in detail (back in 2004!), and the one that lured me into the field of economics. It's a brilliant idea, and has  some solid empirical support. You should read about it, if you don't mind a little math.

The basic idea of the theory is this: It is expensive to move products around. This means that if you have a factory, you want to locate it close to where your customers are, to avoid paying a bunch of shipping costs. Now consider two factories. The workers in the first factory will be the consumers for the second factory, and vice versa. So the two factories want to locate near each other ("agglomeration"). As for the workers/consumers, they want to go where the jobs are, so they move near the factories. Result: a city. The world becomes divided into an industrial "Core" and a much poorer agricultural "Periphery" that produces food, energy, and minerals for the Core. 

Now when you have different countries, the situation gets more interesting. Capital can flow relatively easily across borders (i.e. you can put your factory anywhere you like), but labor cannot. If you start with a world where everyone's a farmer, agglomeration starts in one country, but that country gets maxed out when the costs of density (high land prices) start to cancel out the effect of agglomeration. As transport costs fall and the economy grows, the industrial Core spreads from country to country. Often this spread is quite abrupt, resulting in successive "growth miracles" that get faster and faster (as each new industrial region starts out with a bigger global customer base). The evidence strongly indicates that agglomeration is the driver behind developing-world growth.

But here's the thing: in the theory, the "old Core" doesn't keep getting richer. In fact, under some scenarios (which are difficult to explain concisely), the old Core even gets slightly poorer while the "new Core" catches up. For a while, the negative effects of relocation trump the positive effects of progress.

So this could explain why people in the rich world are getting poorer. In the 50s, America was the only industrial "Core" on the planet. But since the 60s, we have seen successive "growth miracles": Japan and Europe in the 60s/70s, then Taiwan/Korea/Singapore in the 80s, then China since then, and now even India. In a New Economic Geography world, we would expect these successive relocations of manufacturing to hold down income growth in the U.S., even if technology was advancing as usual. And now Japan and Europe are feeling the pinch as well.

Core and Periphery

But the problem is especially acute for America, and here's why. Let's think about Cores and Peripheries. Take a look at this population density map of the world:

Suppose all of those people had the same purchasing power. If you were a factory owner, and you wanted to minimize transport costs, where would you put your factories? The answer is a no-brainer: China and India. Some others in Europe, Japan, and Indonesia. Perhaps a couple on the U.S. East Coast. But for the most part, you'd laugh in the face of any consultant who told you to put a factory in the U.S. The place looks like one giant farm!

It may be that American manufacturing strength was due to a historical accident. Here is the story I'm thinking of. First, in the late 19th and early 20th centuries, our proximity to Europe - at that time the only agglomerated Core in the world - allowed us to serve as a low-cost manufacturing base. Then, after World War 2, the U.S. was the only rich capitalist economy not in ruins, so we became the new Core. But as Europe and Japan recovered, our lack of population density made our manufacturing dominance short-lived.

Now, with China finally free of its communist constraints, economic activity is reverting to where it ought to be. More and more, you hear about companies relocating to China not for the cheap labor, but because of the huge domestic market. This is exactly the New Economic Geography in action. 

Sustain Points and the Great Recession

Actually, the story could be even worse for us. There is another interesting feature of the New Economic Geography theory: hysteresis. I.e., history matters. A place that becomes a city will not easily turn back into a farm. There is a "sustain point" in the economic forces that make an agglomeration viable, and as long as a Core region stays above that point, its initial good luck in becoming the Core will keep it safe from turning back into a backwater.

BUT, a severe shock can knock you down below the sustain point. If your Core no longer has a good reason to be the Core - if it remained rich and built-up only because it would have cost too much to move it - then a big recession (or a devastating war, or a natural disaster) will cause economic activity to leave permanently. Think about the permanent shrinkage of New Orleans in the wake of Katrina.

In this light, the Great Recession of 2008-whenever might be a lot more ominous than even the Great Depression. What if this gargantuan shock has finally made it worthwhile for the center of world industrial activity to relocate to the North China Plain, where nature says it ought to reside? 

In that worst-case scenario, the U.S. industrial economy is not coming back any time soon. From the air we look like a farm, and that is what we will once again become. Thanks to our technological edge, we will retain strengths in industries like software and business services, for which transport costs are extremely low. But our days of "good jobs for everybody" are done. (Keep in mind, this is just a worst-case hypothetical.)

Relocation and Stagnation

Note that although this Great Relocation is an alternative to Tyler Cowen's Great Stagnation, it does not preclude it. Lower productvity growth could coexist alongside agglomeration effects. Or...they might even go together. As I wrote in an earlier post, some "endogenous growth" theories suggest that the availability of cheap labor can reduce the incentives for innovation. If technological progress has stalled, it might just be because the Great Relocation has taken priority.

So What Do We Do About It?

So China "took our jobs." But this was not due to their exchange rate policy, or their export subsidies, or their willingness to pollute their rivers and abuse their workers, although all these things probably spend the transition. They took our jobs because it made no sense for a farm like the U.S. to be building the world's cars and fridges in the first place. Forcing China to revalue the yuan might slow the Great Relocation a little, but has zero hope of stopping it.

So how do we fight this force of nature? How do we get new jobs? I have a few ideas, but keep in mind that these are the thoughts of Smith, not Krugman, and thus take them with a couple extra grains of salt.

1. Keep immigration going strong. 

The United States still has a massive technological and institutional edge. That means that people who come here will be more productive than Chinese people for a long time to come. Every worker we add increases local demand by a lot, and decreases the incentive for production to relocate. This goes double (or triple, or quadruple) for high-skilled immigrants. Beefing up our population with the world's elite knowledge workers is pretty much a no-brainer. Canada gets this; we do not. 

And in the long term - a few decades down the line - high immigration levels will even reverse the Great Relocation, if China's population ages dramatically and ours remains young and growing. With our fertility at exactly the replacement level, the U.S. will only grow by immigration.

2. Promote urban density.

Agglomeration happens because people live close to one another. But the United States has some of the world's least-dense cities, thanks to massive zoning and building height restrictions (and free parking). If darker purple on the "density map" equals long-term prosperity, we need to scrap these policies and start encouraging high-density housing and efficient light rail systems. We need a place to put all those new, high-skilled immigrants!

This will require conservatives to give up their nonsensical anti-train animus. It will also require certain well-off liberals to drop their NIMBY-ish insistence on "open space" (I'm looking at you, Silicon Valley!). Most importantly, because new immigrants will come mostly from Asia, this will require Americans of all stripes to reconcile themselves permanently to the notion that they live in a multi-racial country. 

3. Repair the roads, now.

Agglomeration depends not only on density but on transportation costs. Lower transportation costs between cities make it easier to transport goods between cities. If we make it cheaper for California and Michigan to supply each other, it strengthens the status of the United States as a single industrial agglomeration.

Our roads here in America used to be the world's best, but now they are falling apart for lack of maintenance. This needs to change, and now - while borrowing costs are at rock bottom - is exactly the time to do it. Note that public goods spending is also believed to be the most effective kind of stimulus...so this is a case in which there is zero conflict between short-term and long-term priorities.

4. Conclude free trade deals with other rich countries.

The Great Relocation story is about the world's industrial Core shifting to poor countries in Asia. This may cause some to agitate for trade protectionism (though I think this could only slow the transition, and probably at great cost). But it makes lots of sense for us to boost our trade with other rich countries - i.e., the other countries of the Old Core. Production is not going to relocate from the U.S. to Japan or Europe, because costs there are equally high. Instead, what will happen is closer to the standard "comparative advantage" or "New Trade" stories, where both countries get a boost. (Another way of thinking about this is that free trade lets us improve our competitive position vis-a-vis China when selling stuff to Europe and rich Asia.)

There is one such agreement currently on the table: the Korea-US Free Trade Agreement. Korea is a rich, developed country, so we should pass this right away.

(Update: I removed a fifth suggestion, "support basic research," since I am kind of a broken record on that one anyway, and it's not really agglomeration-related.)

So those are my policy suggestions for fighting a Great Relocation. Keep in mind that these things are almost certainly good things to do no matter what. But in a world where the U.S. is in danger of turning back into a farm, these measures become essential.

Also, note that the Great Relocation is a story about the long term, not the short term. These are not policies to fight the current recession; they are policies to increase the growth of U.S. median income over the next 20 to 50 years. 

Anyway, there is my alternative to the Great Stagnation story. My story is equally scary, but it is something that policy can address. I am not certain that this is really what is going on, but I think it it is worth a lot of thought, and some research too.

OK, back to dissertation. :)


Update: Ryan Avent writes:

It's not clear what story Mr Smith is telling.

Let me boil it down. There are two stories here:

Basic story: Rich countries are experiencing a temporary and mild drop in living standards as China and other poor countries go through an ultra-rapid transition from farming to industrialization.

Scarier story: With the entry of East and South Asia into the global trading system, the U.S. will be in the "agglomeration shadow" of the new pattern, and hence will (partially) deindustrialize. This transition was hastened by the shock of the Great Recession.

I'm not saying either story is definitely true; I don't have the empirical work to make a definitive statement. The basic story sounds very plausible to me, and the scarier story sounds less likely but very scary. My point is agglomeration is a big idea and nobody so far has been talking about it much when they talk about developed-world income stagnation.


Update 2: The Economist has some data that seem to support this general story I'm telling. Thanks to commenter "notyourbusiness" for the link.

Does rapid TFP growth make recessions end quickly?

Tyler Cowen believes that having rapid TFP growth makes recessions end more quickly:

It also seems to me that the long run comes more quickly when TFP is relatively high, which again brings us back, at least partially, to the supply side.  This view is supported by theory.  When the economy has a lot of broad-based technological innovation, at least somewhat evenly distributed, job creation is easier, income effects are more likely to positively cumulate, and monetary and fiscal policy are more likely to gain traction.

The post to which he links regards the depression of the 1870s, and says this:

1873-79 was quite turbulent, but afterwards the global economy adjusted to deflation.

First, I would like to point out that 1873-1879 is six years. That doesn't sound "quick" to me! Recall that that particular depression is typically called the "Long Depression". This despite the high TFP growth at the time.

And six years is twice the amount of time from the 2008 financial crisis until now. If a six-year depression is "quick," why should we conclude, after three years, that our current depression is being prolonged by supply-side factors? That does not make sense to me.

Also, there are other obvious counterexamples. The recessions of the early 1980s were very short and "V-shaped," despite the extremely low rate of TFP growth at the time:

By contrast, the early-2000s recession, though shallow, was much longer and "U-shaped", despite the recovery in TFP growth.

Therefore, it seems to me that the historical record does not show an inverse relationship between TFP growth and recession duration. That doesn't mean a relationship isn't there, but it would require serious and careful econometrics to tease out. I know of no study that has done that yet.

If supply-side factors are prolonging our current malaise, this does not appear to be the channel through which they are working.

Sean Carroll on social science vs. natural science

I generally don't like to repost other people's blog posts in full on my blog, because it deprives the writers of pageviews. And of course the fact that I say that reliably indicates that I'm about to make an exception. Sean Carroll, who writes for the physics blog Cosmic Variance over at Discover, has written an absolute must-read post on social science vs. natural science. So here it is in full, with emphasis added by me:

Over on the Google+, Robin Hanson asks a leading question: 

Explain why people shouldn’t try to form their own physics opinions, but instead accept the judgements of expert physicists, but they should try to form their own opinions on economic policy, and not just accept expert opinion there. 

(I suspect the thing he wants me to explain is not something he thinks is actually true.) 

There are two aspects to this question, the hard part and the much-harder part. The hard part is the literal reading, comparing the levels of trust accorded to economists (and presumably also political scientists or sociologists) to the level accorded to physicists (and presumably also chemists or biologists). Why do we — or should we — accept the judgements of natural scientists more readily than those of social scientists? 

Although that’s not an easy question, the basic point is not difficult to figure out: in the public imagination, natural scientists have figured out a lot more reliable and non-obvious things about the world, compared to what non-experts would guess, than social scientists have. The insights of quantum mechanics and relativity are not things that most of us can even think sensibly about without quite a bit of background study. Social scientists, meanwhile, talk about things most people are relatively familiar with. The ratio of “things that have been discovered by this discipline” to “things I could have figured out for myself” just seems much larger in natural science than in social science. 

Then we stir in the matter of consensus. On the very basics of their fields (the Big Bang model, electromagnetism, natural selection), almost all natural scientists are in agreement. Social scientists seem to have trouble agreeing on the very foundations of their fields. If we cut taxes, will revenue go up or down? Does the death penalty deter crime or not? For many people, a lack of consensus gives them license to trust their own judgment as much as that of the experts. To put it another way: if we talked more about the bedrock principles of the field on which all experts agreed, and less about the contentious applications of detailed models to the real world, the public would likely be more ready to accept experts’ opinions. 

None of which is to say that social scientists are less capable or knowledgable about their fields than natural scientists. Their fields are much harder! Where “hard” characterizes the difficulty of coming up with models that accurately capture important features of reality. Physics is the easiest subject of all, which is why we know enormously more about it than any other science. The social sciences deal with fantastically more complicated subjects, about which it’s very naturally more difficult to make definitive statements, especially statements that represent counterintuitive discoveries. The esoteric knowledge that social scientists undoubtedly possess, therefore, doesn’t translate directly into actionable understanding of the world, in the same way that physicists are able to help get a spacecraft to the moon. 

There is a final point that is much trickier: political inclinations and other non-epistemic factors color our social-scientific judgments, for experts as well as for novices. On a liberal/conservative axis, most sociologists are to the left of most economists. (Training as an economist allegedly makes people more selfish, but there are complicated questions of causation there.) Or more basically, social scientists will often approach real-world problems from the point of view of their specific discipline, in contrast with a broader view that the non-expert might find more relevant. (Let’s say the death penalty does deter crime; is it still permissible on moral grounds?) Natural scientists are blissfully free from this source of bias, at least most of the time. Evolution would be the obvious counterexample. 

The more difficult question is much more interesting: when should, in completely general terms, a non-expert simply place trust in the judgment of an expert? I don’t have a very good answer to that one. 

I am a strong believer that good reasons, arguments, and evidence are what matter, not credentials. So the short answer to “when should we trust an expert simply because they are an expert?” is “never.” We should always ask for reasons before we place trust. Hannes Alfvén was a respected Nobel-prizewinning physicist; but his ideas about cosmology were completely loopy, and there was no reason for anyone to trust them. An interested outsider might verify that essentially no working cosmologists bought into his model. 

But a “good reason” might reasonably take the form “look, this is very complicated and would take pages of math to make explicit, but you see that I’ve been doing this for a long time and have the respect of my peer group, which has a long track record of being right about these issues, so I’m asking you to go along this time.” In the real world we don’t have anything like the time and resources to become experts in every interesting field, so some degree of trust is simply necessary. When deciding where to place that trust, we rely on a number of factors, mostly involving the track record of the group to which the purported expert belongs, if not the individual experts themselves. 

So my advice to economists who want more respect from the outside world would be: make it much more clear to the non-expert public that you have a reliable, agreed-upon set of non-obvious discoveries that your field has made about the world. People have tried to lay out such discoveries, of course — but upon closer inspection they don’t quite measure up to Newton’s Laws in terms of reliability and usefulness. 

Social scientists are just as smart and knowledgable as natural scientists, and certainly have a tougher job. But trust among non-experts isn’t demanded, and shouldn’t be based on credentials; it is given on the basis of a long track record of very visible success. Everyone would be in favor of that.

As far as I am concerned, every single thing written in this post is spot-on. I just have a few additional points:

1. What Carroll is saying is far more true of macroeconomics than microeconomics. Microeconomists are pretty good at predicting how bidders will bid at an auction, or how many people will use a new planned subway extension. (An old prof of mine once successfully managed to predict the relative amounts of denominations of money that counterfeiters would fake!) People don't often hear about these quiet successes, caught up as they are in the failures of macro. But they are real.

2. Although the lack of consensus among (macro)economists should give laypeople pause, the converse does not hold; the fact of consensus on a particular issue doesn't mean economists are right. The "Great Moderation" idea, for example, was as near to a business-cycle theory consensus as one could find, but collapsed in the wake of the recent crisis. As another example, a common defense of the DSGE modeling paradigm is that "everybody's doing it." Sorry, but no.

3. Carroll doesn't go into this, but the microfoundations of a discipline are also a factor in how much its experts should be trusted. Climatology has too long a horizon to make repeated verifiable predictions, but it's microfounded by physics that everyone agrees on. Macroeconomics, on the other hand, is microfounded on the parts of microeconomics that we don't really understand yet - consumption-saving behavior, firm investment decisions, technological change, expectation formation, risk aversion, and the like. Once micro people get these nailed down (and I think they will), we'll get some much more credible macro models.

Anyway, go check out the original link, which has some interesting links of its own.


Update: Robin Hanson responds to Carroll. The key argument is this:

Yes, economists were only a supporting influence in creating all those great economic institutions...But similarly, physicists were only a supporting influence in creating all those great physical devices...There were useful steam engines long before thermodynamics helped explain them, and it took far more than basic physics to get men to the moon, just as it took far more than basic economics to create modern industries. It is actually quite hard to say which discipline has been more useful overall to the world. 

This just seems wrong to me. You need to know Newton's Laws to hit the moon with a rocket. You don't need to know supply and demand curves to build a company. Physics theory has been absolutely essential to the creation of a number of industries, economics only to a couple, macroeconomics to basically none. And it should also be noted that before the mid-1900s, economics was non-quantitative, basically a type of philosophy. Which means that back when things like the corporation and the factory were being invented, economists' role was mainly as cheerleaders for free markets. Which was a very important role, but was a political role, not a scientific one.

Tinkering at the margins

Still swamped with work, but time for a quick post to reward myself for getting my dissertation proposal approved...

Harvard profs Greg Mankiw and Robert Barro, two giants of the macro world, have twin editorials in the NYT suggesting what we should do to improve the economy. Mankiw favors free trade agreements and steps to improve international wage competitiveness...

Myriad government actions influence the expected future profitability of capital. These include not only policies concerning taxation but also those concerning trade and regulation. 

For example, passing the free trade agreement with South Korea, which has languished in Congress more than four years after first being negotiated, would be a step in the right direction. So would reining in the National Labor Relations Board; its decision to block Boeing from opening a nonunion plant in South Carolina may have been hailed by organized labor, but it surely did not hearten investors.

...while Barro suggests switching from corporate and estate tax to a VAT:

A broad-based expenditure tax, like a VAT, amounts to a tax on consumption. If the base rate were 10 percent, the revenue would be roughly 5 percent of G.D.P. One benefit from a VAT is that it is more efficient than an income tax — and in particular the current American income tax system... 

Abolishing the corporate income tax is similarly controversial. Any tax on capital income distorts decisions on saving and investment.

Now, I broadly agree with all the policies described above (yes, including allowing South Carolina to compete with Washington state on wages). But do prof.'s Mankiw & Barro really believe that these will get us our of our slump? Where have we seen an example of a country that got itself out of recession by tweaking its tax and labor policies? I can't think of one. Europe has a VAT and a corporate tax rate that is 15 percentage points lower than ours, and they don't seem to have made a quick exit from this slump. Maybe FTAs will have more of a countercyclical effect, but it's important to remember that Korea is one-seventh our size.

And another point. All of these policy suggestions are structural things. They are one-off policies that cannot be repeated. Even if improving tax policy helps us out of this recession, what do we do when the next recession comes along? Now, maybe Mankiw and Barro don't believe that real countercyclical policy exists, and that instead the best we can hope for is that crises will make needed structural changes politically feasible. But then I think they should say this. (Update: Brad DeLong agrees.)

As for me, I doubt that these tweaks will have much of an effect. What do I think will? Well, my hunch - and this is just a hunch - is that we should start taking a very hard look at exchange-rate policy...but that is a blog post for another day...

(Note: Barro also makes an argument for fiscal austerity. I'm not going to get into that now, except to say that the approval I expressed toward his tax policy ideas do not extend to his call for austerity. Just in case anyone was wondering.)