What can we do to put a stop to global warming?

First, the good news. Here is an infographic about the U.S. contribution to global warming:



U.S. total energy-related carbon emissions are down 13% since 2007. That's huge. Although the U.S. refused to sign the Kyoto Protocol, we managed about 70% of the emissions reductions mandated by that treaty (which is much better than most of the actual signatories!).

Renewable energy now provides 12.1% of U.S. energy. That is big.

Energy demand has fallen 6.4% since 2007, even though GDP is slightly higher. Hence, energy efficiency is responsible for the reduction in demand. That is good.

Gas is replacing coal. That is good, provided that wellhead methane emissions are not making up the difference.

Bottom line: If the U.S. were the world, the fight against global warming would be going well.

OK, now for the bad news: The U.S. is not the world. Global warming is global. The only thing that matters for the world is global emissions. And global emissions are still going up, thanks to strong increases in emissions in the developing world, notably China.

Figures released this week show skyrocketing Chinese coal use. China now burns almost as much coal as the rest of the world combined:



Meanwhile, Indian coal use is also increasing strongly.

If China and the other developing nations cook the world, the world is cooked, no matter what America or any other country does. China et al. can probably cook the world without our help, because global warming has "threshold effects" (tipping points), and because carbon stays in the air for thousands of years.

Bottom line: We will only save the planet if China (and other developing countries) stop burning so much coal. Any policy action we take to avert global warming will be ineffective unless it accomplishes this task.

What will accomplish this task? What can we do to influence the behavior of China? One thing that might help, on the margin, is to tax the carbon content of imports into the U.S. A second thing would be to tax U.S. exports of coal and other fuels.

But these measures - or any carbon-taxing measures taken only by rich countries - will have limited effects, due to the large size of the developing-world economy, which is set to pass the developed world in size very soon. What else can we do to slow developing-world emissions?

As I see it, there is only one thing we can do: develop renewable technologies that are substantially cheaper than coal, and give these technologies to the developing countries. China in particular is not a very globally responsible country; it will continue to pursue growth, economic size, and geopolitical power at any cost, and that means using the cheapest energy source available. The only way China will stop using coal is if it becomes un-economical to continue using coal.

Thus, the rich world should focus its efforts and money on developing renewable energy cheaper than coal. This mainly means solar; it also means better energy storage and transmission technologies. We should give these technologies away to China and other countries for free; the economic hit we take from doing so will help ease developing-country resentment over the fact that the U.S., Europe, Japan and others got rich by burning fossil fuels in the past.

Developing cheap renewable energy technologies requires research funding from the government. A carbon tax would also help, since it provides a subsidy for private firms to develop their own in-house technologies. However, it will not be possible to give privately owned technologies to China; for these to be rapidly adopted in China in time to save the world, we must rely on natural technology diffusion, or on Chinese espionage.

So, government research is the most important component. We need to increase government funding for solar, for energy storage, and for electricity transmission tech. And then we need to give the fruits of our research for free to the entire world, before it's too late.

Are jobless recoveries the Fed's fault?

Matt O'Brien (who, in full disclosure, is the guy who recruited me to write for the Atlantic) hypothesizes that the "jobless recoveries" of recent decades have been caused by the Fed. Specifically, he thinks that the Fed has been practicing "opportunistic disinflation", allowing recessions to lower inflation, and then "stabilizing" inflation at a new, lower level after each recession by raising interest rates too soon. Here is the case:

Through the 1980s, postwar recessions happened when the Fed decided to raise rates to head off inflation, and recoveries happened when the Fed decided things had tamed down enough to lower rates. But now recessions happen when bubbles burst...and the Fed hasn't been able to cut interest rates enough to generate strong post-crash recoveries. Or maybe it hasn't wanted to... 

Why have interest rates and inflation mostly been falling for the past 30 years? In other words if the Fed has been de facto, and later de jure, targeting inflation for most of this period (and it has), why has inflation been on a down trend (and it has)?...  

 

Say hello to "opportunistic disinflation...The Volcker Fed had come in for quite a bit of abuse when it whipped inflation at the expense of the severe 1981-82 downturn, and the Fed seems to have learned it was better not to leave its fingerprints on the business cycle.  

In other words, Let recessions do their dirty work for them. 

It's not hard for central bankers to get what they want without doing anything, as long as what they want is less inflation (and that's almost always what central bankers want). They just have to wait for a recession to come along ... and then keep waiting until inflation falls to where they want it. Then, once prices have declined enough for their taste, they cut rates (or buy bonds) to stabilize inflation at this new, lower level. But it's one thing to stabilize inflation at a lower level; it's another to keep it there. The Fed has to raise rates faster than it otherwise would during the subsequent recovery to keep inflation from going back to where it was before the recession. It's what the Fed calls "opportunistic disinflation," and it's hard to believe this wasn't their strategy looking at falling inflation the previous few decades. Not that we have to guess. Fed president Edward Boehene actually laid out this approach in 1989, and Fed governor Laurence Meyer endorsed the idea of "reducing inflation cycle-to-cycle" in a 1996 speech -- the same year the Wall Street Journal leaked an internal Fed memo outlining the policy.  

In short: Recoveries have been jobless, because that's how the Fed likes them.

I guess this is a pretty solid case. Fed memos and speeches, combined with the low path of observed inflation. However, I don't believe it.

Why not? Well, there have been three "jobless recoveries" in recent decades: the early-90s recovery, the early-2000s recovery, and the current recovery. Looking at Matt's inflation history graph, we see that in the 2000s, inflation didn't shift to a lower level - so, no "opportunistic disinflation" there (unless the Fed tried and failed!). In the current recovery, the Fed hit the Zero Lower Bound, and inflation actually fell below the Fed's desired rate. So let's look at the one remaining candidate for "opportunistic disinflation" - the early 90s. Here is a graph of the Federal Funds rate over time:



We see that the Fed cut rates during the early-90s recession, and kept cutting then for several years after that. Remember what Matt said: "The Fed has to raise rates faster than it otherwise would during the subsequent recovery to keep inflation from going back to where it was before the recession." According to this principle, the rate rise in 1995 1994 must have come earlier than it would have come, had the Greenspan Fed not been practicing "opportunistic disinflation."

But compared to other recessions, the 1994 rate rise came with a very long lag. In fact, the 1990s recession is nearly unique in that the Fed Funds kept falling for quite some time after GDP stopped contracting. In fact, by the time the Fed started raising rates in 1994, the unemployment rate had already fallen to around its pre-recession level:



In other words, it sure looks like the Fed didn't even start raising rates until after the unusually long "jobless recovery" of the early 1990s was already finished.

Now, of course, it is fashionable these days to say that looking at the Fed's policy rate actually tells us nothing whatsoever about monetary policy. If you believe that the Fed chooses the level of NGDP at all points in time, then by assumption, all "jobless recoveries" were chosen by the Fed, and the policy rate simply did what it had to do in order to produce the observed time path of NGDP.

But I am highly skeptical of this idea.

Actually, in the case of post-Volcker monetary policy, I find the typical story to be the most convincing one. Estimates of the Fed's "reaction function", such as this one by Clarida, Gali, and Gertler in 2000 and others since then, find that the Fed has always seemed to use a "Taylor-type" rule to set policy rates, but that the Fed's rule started putting more of an emphasis on inflation-fighting, and less on unemployment-fighting, since Volcker took over. According to this common received wisdom, the Volcker Recessions convinced America that the Fed wouldn't tolerate inflation, and then higher productivity growth in the 90s enabled Greenspan to keep rates low without causing inflation expectations to come un-anchored. That story would explain the lower inflation observed post-1980 in O'Brien's graph. But it's not the same thing as "opportunistic disinflation", and it would not lead to jobless recoveries, because the Fed would still set its policy rate to respond to the best current estimates of inflation and the output gap.

As for the Fed's memos and speeches suggesting opportunistic disinflation? Well, Fed memos and speeches suggest a lot of things. That doesn't mean that the Fed actually does them...

So while I also think the Fed has probably been a little too focused on inflation since the experience of the 70s, my gut tells me we need to look elsewhere for the source of the jobless recovery phenomenon. My own guess is that financial-based explanations, in particular the idea of "balance sheet recessions", is more compelling. As Matt noted, recessions with "jobless recoveries" (really, just recoveries with sluggish growth) have tended to follow very different kinds of financial events than pre-1990 recessions. Some international comparisons find that recoveries tend to be anemic after a certain kind of financial crisis. If I were a betting man, I'd put my money on that explanation.

The power and the terror of Irrational Expectations

In September 2011, in an interview with the Wall Street Journal, Robert Lucas gave the following justification for the use of 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.

So, are Rational Expectations not "just made up"? Does the evidence tell us that this is how people form expectations? I don't think so. It seems to me that Lucas is saying that we should pick Rational Expectations because they are appealing in some a priori way. I'm not sure what that is, though.

Be that as it may, figuring out how people actually form expectations, in the real world, is devilishly hard. Thomas Sargent and many others have experimented with models of Bayesian learning. Roger Farmer has advanced the idea that agents use a "belief function" in cases where rational expectations of the Lucas variety can't be formed. Greg Mankiw and Ricardo Reis have experimented with macro models in which people don't always update their beliefs on time, and Christopher Sims and many others have tried to microfound this idea with various models of rational inattention (in fact, rational inattention is now a hot topic in behavioral finance).

Of course, there are older, simpler ideas of expectation formation that were pushed out by the Lucas revolution, but which may have received a bad rap. One of these is Milton Friedman's theory of "adaptive expectations", which in its simplest form doesn't seem to explain the data, but may actually be going on in some more complicated form.

That is the conclusion of a recent paper by Ulrike Malmendier, a star of the behavioral finance field. Malmendier shows that people's inflation expectations are strongly affected by recency bias; in other words, people who have experienced higher inflation during a large percentage of their lifetime tend to expect higher inflation, even if their lifetimes haven't been that long yet. From the abstract:

How do individuals form expectations about future inflation? We propose that past inflation experiences are an important determinant absent from existing models. Individuals overweigh inflation rates experienced during their life-times so far, relative to other historical data on inflation. Differently from adaptive-learning models, experience-based learning implies that young individuals place more weight on recently experienced inflation than older individuals since recent experiences make up a larger part of their life-times so far. Averaged across cohorts, expectations resemble those obtained from constant-gain learning algorithms common in macroeconomics, but the speed of learning differs between cohorts.

This comes via Carola Binder, a grad student blogger at Berkeley (whom you should follow, by the way).

Binder discusses the implications of this finding for Japanese exchange rates, but I wish she had touche more on the basic idea that this sort of expectation formation might be responsible for the persistence of Japan's deflationary trap itself. Japan has been in deflation, or near it, for two decades now. That's a large fraction of the working lifetimes of many of Japan's current adults. If inflation expectations are set in the backward-looking way that Malmendier suggests, then it might take far more dramatic and sustained central bank action than anyone realizes in order to produce a return to an inflationary environment.

But to me, that's not even the most disturbing implication of Malmendier's finding, and of this type of expectations model in general. In most theories of non-rational expectations, like Bayesian learning or rational inattention, expectations evolve in a smooth, stable way. And so these models, as Chris Sims writes, look reassuringly like rational-expectations models. But there is no guarantee that real-world expectations must behave according to a stable, tractable model. I see no a priori reason to reject the possibility that expectations react in highly unstable, nonlinear ways. Like tectonic plates that build up pressure and then slip suddenly and unpredictably, expectations may be subject to some kind of "cascades". This can happen in some simple examples, like in the theory of "information cascades" (In that theory, people are actually rational, but incomplete markets prevent their information from reaching the market, and beliefs can shift abruptly as a result). In the real world, with its tangle of incomplete markets, bounded rationality, and structural change, expectations may be subject to all kinds of instabilities.

In other words, to use Lucas' turn of phrase, expectations might just make themselves up...and we might get any result that we don't want.

What if inflation expectations change suddenly and catastrophically? That would probably spell the death knell for macro theories in which the central bank can smoothly steer the path of things like inflation, NGDP, etc. It would raise the specter of an "inflation snap-up" (or "overshoot", or "excluded middle") - the central bank might be unsuccessful in beating deflation, right up until the moment when hyperinflation runs wild.

And what would be the implications of financial markets and financial theories of the macroeconomy? Belief cascades could obviously cause asset market crashes. It seems like sudden changes in expectations of asset price appreciation might also cause abrupt and long-lasting changes in saving and investment behavior. Which in turn could cause...well, long economic stagnations.

A very disturbing thought.

Bayesian vs. Frequentist: Is there any "there" there?

The Bayesian/Frequentist thing has been in the news/blogs recently. Nate Silver's book (which I have not yet read btw) comes out strongly in favor of the Bayesian approach, which has seen some pushback from skeptics at the New Yorker. Meanwhile, Larry Wasserman says Nate Silver is really a frequentist (though Andrew Gelman disagrees), XKCD makes fun of Frequentists quite unfairly, and Brad DeLong suggests a third way that I kind of like. Also, Larry Wasserman gripes about people confusing the two techniques, and Andrew Gelman cautions that Bayesian inference is more a matter of taste tan a true revolution. If you're a stats or probability nerd, dive in and have fun.

I'm by no means an expert in this field, so my take is going to be less than professional. But my impression is that although the Bayesian/Frequentist debate is interesting and intellectually fun, there's really not much "there" there...a sea change in statistical methods is not going to produce big leaps in the performance of statistical models or the reliability of statisticians' conclusions about the world.

Why do I think this? Basically, because Bayesian inference has been around for a while - several decades, in fact - and people still do Frequentist inference. If Bayesian inference was clearly and obviously better, Frequentist inference would be a thing of the past. The fact that both still coexist strongly hints that either the difference is a matter of taste, or else the two methods are of different utility in different situations.

So, my prior is that despite being so-hip-right-now, Bayesian is not the Statistical Jesus.

I actually have some other reasons for thinking this. It seems to me that the big difference between Bayesian and Frequentist generally comes when the data is kind of crappy. When you have tons and tons of (very informative) data, your Bayesian priors are going to get swamped by the evidence, and your Frequentist hypothesis tests are going to find everything worth finding (Note: this is actually not always true; see Cosma Shalizi for an extreme example where Bayesian methods fail to draw a simple conclusion from infinite data). The big difference, it seems to me, comes in when you have a bit of data, but not much.

When you have a bit of data, but not much, Frequentist - at least, the classical type of hypothesis testing - basically just throws up its hands and says "We don't know." It provides no guidance one way or another as to how to proceed. Bayesian, on the other hand, says "Go with your priors." That gives Bayesian an opportunity to be better than Frequentist - it's often better to temper your judgment with a little bit of data than to throw away the little bit of data. Advantage: Bayesian.

BUT, this is dangerous. Sometimes your priors are totally nuts (again, see Shalizi's example for an extreme case of this). In this case, you're in trouble. And here's where I feel like Frequentist might sometimes have an advantage. In Bayesian, you (formally) condition your priors only on the data. In Frequentist, in practice, it seems to me that when the data is not very informative, people also condition their priors on the fact that the data isn't very informative. In other words, if I have a strong prior, and crappy data, in Bayesian I know exactly what to do; I stick with my priors. In Frequentist, nobody tells me what to do, but what I'll probably do is weaken my prior based on the fact that I couldn't find strong support for it. In other words, Bayesians seem in danger of choosing too narrow a definition of what constitutes "data".

(I'm sure I've said this clumsily, and a statistician listening to me say this in person would probably smack me in the head. Sorry.)

But anyway, it seems to me that the interesting differences between Bayesian and Frequentist depend mainly on the behavior of the scientist in situations where the data is not so awesome. For Bayesian, it's all about what priors you choose. Choose bad priors, and you get bad results...GIGO, basically. For Frequentist, it's about what hypotheses you choose to test, how heavily you penalize Type 1 errors relative to Type 2 errors, and, most crucially, what you do when you don't get clear results. There can be "good Bayesians" and "bad Bayesians", "good Frequentists" and "bad Frequentists". And what's good and bad for each technique can be highly situational.

So I'm guessing that the Bayesian/Frequentist thing is mainly a philosophy-of-science question instead of a practical question with a clear answer.

But again, I'm not a statistician, and this is just a guess. I'll try to get a real statistician to write a guest post that explores these issues in a more rigorous, well-informed way.

Update: Every actual statistician or econometrician I've talked to about this has said essentially "This debate is old and boring, both approaches have their uses, we've moved on." So this kind of reinforces my prior that there's no "there" there...

Update 2: Andrew Gelman comments. This part especially caught my eye:

One thing I’d like economists to get out of this discussion is: statistical ideas matter. To use Smith’s terminology, there is a there there. P-values are not the foundation of all statistics (indeed analysis of p-values can lead people seriously astray). A statistically significant pattern doesn’t always map to the real world in the way that people claim. 

Indeed, I’m down on the model of social science in which you try to “prove something” via statistical significance. I prefer the paradigm of exploration and understanding. (See here for an elaboration of this point in the context of a recent controversial example published in an econ journal.)

Update 3: Interestingly, an anonymous commenter writes:

Whenever I've done Bayesian estimation of macro models (using Dynare/IRIS or whatever), the estimates hug the priors pretty tight and so it's really not that different from calibration.

Update 4: A commenter points me to this interesting paper by Robert Kass. Abstract:

Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice, labeled here statistical pragmatism, serves as a foundation for inference. Statistical pragmatism is inclusive and emphasizes the assumptions that connect statistical models with observed data. I argue that introductory courses often mischaracterize the process of statistical inference and I propose an alternative "big picture" depiction.

Solar: It's about to be a whole new world.

Many conservatives appear to have an unshakable, bedrock belief that solar power will never be cost-effective. Talk about solar, and conservatives often won't even look at the numbers - they'll just laugh at you. Mention that solar power recently provided almost half of Germany's electricity at peak hours, and they'll say things like "Oh, Germany's economy must be tanking, then." It seems like almost a fundamental axiom of their worldview that solar will always be too expensive to exist without government subsidies, and that research into solar is therefore money flushed down the toilet.

I suspect that many of these conservatives came of age in the 1970s, when solar was first being mooted as the "green" alternative to fossil fuels. They probably saw solar as a crypto-socialist plot; by scaring everyone about global warming and forcing businesses to convert to expensive solar power, "greens" would impose huge a implicit tax on business, causing the capitalist system to grind to a halt.

Maybe some people did support solar for just such a (silly) reason. But far-sighted people knew that technologies often require lots of government support to develop (basic research being, after all, a public good), and they saw that fossil fuels would have to start getting more expensive someday.

And now, after decades of research and subsidies, we may be on the verge of waking up into a whole new world. The cost of solar power has been falling exponentially for the past 35 years. What's more, there is no sign at all that this cost drop is slowing. New technologies are in the pipeline right now that have the potential to make solar competitive with coal and natural gas, even with zero government subsidy. Here are a few examples:

1. Nano-templated molecules that store energy
MIT associate professor Jeffrey Grossman and others successfully created a new molecule [to] "lock in" stored solar thermal energy indefinitely. These molecules have the remarkable ability to convert solar energy and store it at an energy density comparable to lithium ion batteries...

2. Print solar cells on anything
An MIT team led by professor Karen Gleason has discovered a way to print a solar cell on just about anything...The resulting printed paper cell is also extremely durable and can be folded and unfolded more than 1,000 times with no loss in performance.

3. Solar thermal power in a flat panel
Professor Gang Chen has been working on a revolutionary new way to make solar power — micro solar thermal — which could theoretically produce electricity at 8 times the efficiency of the word's best solar panel...Because it is a thermal process, the panels can heat up from ambient light even on an overcast day, and these panels can be made from very inexpensive materials.

4. A virus to improve nano-solar cell efficiency
MIT graduate students recently engineered a virus called M13 (which normally attacks bacteria) that works to precisely space apart carbon nanotubes so they can be used to effectively convert solar energy...

5. Transparent solar cell could turn windows into power plants
...Electrical engineering professor Vladimir Bulovic has made a breakthrough that could eliminate two-thirds of the costs of installing thin-film technology [on windows] by incorporating a layer of new transparent organic PV cells into the window glazing. The MIT team believes it can reach a whopping 12 percent efficiency at hugely reduced costs[.]

And then there are the technologies that are out of the laboratory and being sold to customers. For example, here's this article from the website Grist:

The company is called V3Solar (formerly Solarphasec) and its product, the Spin Cell, ingeniously solves two big problems facing solar PV. 

First, most solar panels are flat, which means they miss most of the sunlight most of the time...The Spin Cell is a cone...The conical shape catches the sun over the course of its entire arc through the sky, along every axis. It’s built-in tracking. 

The second problem: Solar panels produce much more energy if sunlight is concentrated by a lens before it hits the solar cell; however, concentrating the light also creates immense amounts of heat, which means that concentrating solar panels (CPV) require expensive, specialized, heat-resistant solar cell materials. 

The Spin Cell concentrates sunlight on plain old (cheap) silicon PV, but keeps it cool by spinning it... 

[T]he company tells CleanTechnica that it already has over 4 GW of requests for orders. There is 7 GW of installed solar in the U.S., total... 

Maybe this tech or this company will peter out before reaching mass-market scale. But advances in solar technology are coming faster and faster. (Small, distributed energy technologies are inherently more prone to innovation than large, capital-intensive energy technologies.)

As the article says, this could easily be just an illusion. Don't believe the hype. But the point is that there are now lots of companies and academic labs making claims like this, and the rate appears only to be increasing. Sooner or later - and recent trends suggest "sooner" rather than "later" - one of these claims is going to be right.

And on that day, we will wake up into a whole new world.

Cheap solar energy will change pretty much everything. First of all, it will cause a huge boom among essentially all industries in every country (except for competing energy technologies, of course). Energy powers everything. So far, with nuclear technology stalled, we don't have anything cheaper than coal and gas for producing electricity. Our only hope for cheaper energy has been to find better ways to mine coal and gas. With cheap solar, that is no longer true. The Great Stagnation - which many suspect is really just an energy technology stagnation - would suddenly be a lot less scary. 

Mention this possibility to conservatives, and they will of course be skeptical. These days, you are less likely to hear outright denials of solar's cheapness; instead, the knee-jerk conservative response is "Well what about the intermittency? Solar power only works during the day!"

Two things to note about this. First, it's very telling that solar detractors didn't talk much about intermittency a decade ago. They didn't have to; solar was too expensive even at high noon. The fact that detractors are falling back on the intermittency argument shows how much the game has changed.

Second, the problem of intermittency isn't really a big one. Most electricity is used during "peak" hours, which incidentally is when the sun is shining. It's easy to imagine a future in which solar electricity powers the world during the day, and then gas takes over at night. But that will mean solar is the main source, and gas only a sideshow. (And that's even without any breakthroughs in energy storage technology.)

Anyway, it's looking more and more likely that conservatives are going to wake up one day soon, and look around and blink and find that one of their bedrock beliefs has suddenly been invalidated on a grand scale. If they're smart, conservatives will take this opportunity to discard the old belief that solar is the thin wedge of crypto-socialism, and recognize it for what it truly is - a breakthrough technology, being developed by entrepreneurs for profit on the free market.

In other words, exactly the kind of thing they should applaud.


Update: A commenter writes:

Great discussion. I am a conservative and I own a solar energy company. I do not understand your premise on conservatives aversion to solar power. By nature most conservatives I know desire to break free from the control of the energy,environmental, foreign wars and government lobby, and solar allows us to get there.

Good point. Some other good reasons why conservatives should be more pro-solar.

Update 2: I guess I should give a concrete prediction about when solar will actually start being cost-competitive with fossil fuels, without subsidies, in some locations for some customers. My prediction is: around 2020, or 7 years from now. 95% credible interval would be...um, let's see...2014 to 2040. So that's a fairly wide interval.

Update 3: Commenter Kevin Dick provides some numbers regarding current costs:

[T]he US DOE actually tries to calculate the cost of various energy sources using a complicated levelized cost model. See http://www.eia.gov/forecasts/aeo/electricity_generation.cfm. For power plants coming on line in 2017, their nationwide average estimates in $/MWH are: 

Conventional Coal: 98
Convenional CC Gas: 66
Solar PV: 153  

On average, PV has a ways to go. However, the lowest regional cost of PV is 119, while the highest regional cost of coal is 115 and advanced nuclear is 119.  

So there are probably places today where PV is cost competitive. But the market can surely figure this out at least as well as the government.

If these numbers are right, it means that we are just now hitting the point where solar power makes economic sense in a few places without any government subsidies. That's pretty amazing, if you ask me. I wonder how many of those places there will be in 7 years...

Macro always fights the last war

Matthew Klein of The Economist has a great post up about the history of modern macro, drawing on a presentation by the incomparable Markus Brunnermeier. If you are at all interested in macroeconomics, you should check it out (though of course econ profs and many grad students will know the bulk of it already).

Here is Klein's summary of pre-2008 macro:

As the slideshow makes clear, macro has evolved in fits and starts. Existing models seem to work until something comes along that forces a rethink. Then academics tinker and fiddle until the next watershed.  

In response to the Great Depression, John Maynard Keynes developed the revolutionary idea that individually beneficial actions could produce undesirable outcomes if everyone tried to do them at the same time. Irving Fisher explained that high levels of debt make economies vulnerable to downward spirals of deflation and default... 

Problems developed in the 1970s. “Stagflation,” the ugly portmanteau that describes an economy beset with rapid price increases and high levels of unemployment was not supposed to be possible—yet it was afflicting all of the world’s rich countries...A new generation of macroeconomists, including Ed Phelps, Robert Lucas, Thomas Sargent, Christopher Sims, and Robert Barro, responded to the challenge in the late 1970s and early 1980s...[their] new “dynamic stochastic general equilibrium” (DSGE) models were based on individual households and businesses that tried to do the best they could in a challenging world...Despite...many drawbacks, DSGE models got one big thing right: they could explain “stagflation” by pointing to people’s changing expectations.

Klein and Brunnermeier both say that macro is changing again, this time in response to the Great Recession and the financial crisis that preceded it. The big change now, they say, is adding finance into macro models.

Reading this, one could be forgiven for thinking that macro lurches from crisis to crisis, always trying to "explain" the last crisis, but always missing the next one.

How true is that? Well, on one hand, science should progress by learning from its mistakes. You have a model that you think explains the world...then something new comes along, and you need to change your model. Great. That's how it's supposed to work.

Doesn't that describe exactly what macro has been doing? Well, maybe, but maybe not. First of all, what you shouldn't do is develop models that only explain the most recent set of observations. In the 70s and 80s, the DSGE models that were developed to explain stagflation had a very hard time explaining the Great Depression. Robert Lucas joked about this, saying: "If the Depression continues, in some respects, to defy explanation by existing economic analysis (as I believe it does), perhaps it is gradually succumbing under the Law of Large Numbers."

But the fact that DSGE models couldn't explain the Depression was not seen as a pressing problem. There was no big push to modify or expand the models in order to explain the biggest economic crisis of the 20th century (though there were scattered attempts).

So macro seems to suffer from some "recency bias".

And here's another issue. When we say macro models "explain" a phenomenon, that generally means something very different, and less impressive, than it means in the hard sciences (or even in microeconomics). When we say that 80s-vintage DSGE models "explain" stagflation, what we mean is "there is the possibility of stagflation in these models". We mean that these models are consistent with observed stagflation.

But for any phenomenon, there are many possible models that are consistent with that phenomenon. How do you know you've got the right story? Well, there are several ways you can sort of tell. One is generality of a model: how well does the model explain not just this one thing, but a bunch of other things at the same time? (This is closely related to the idea of "unification" in physics.) If your model can explain a bunch of different stuff, then it's probably more likely to have captured something real, instead of being a "just-so story".

But modern macro models don't do a lot of that. Each DSGE model matches a few things, and not other things (this is why they are all rejected by formal statistical testing). Ask the author about the things his model doesn't match, and he'll shrug and say "I'm not trying to model the whole economy, just a couple of things." So there's a huge proliferation of models - not even one model to "explain" each phenomenon, but many models per phenomenon, and very little in the way of choosing which model is appropriate to use, and when.

Another clue that you've got the right story is if your model has predictive power. But modern macro models display very poor forecasting ability (as do non-modern models, of course).

Before the 2008 crisis, there doesn't seem to have been very much dissatisfaction with the state of macro. Models were rejected by statistical tests...fine, "All models are wrong," right? There were 50 models per phenomenon...fine, "We have models for anything!" Models can't forecast the future...fine, "We're not interested in forecasting, we're interested in giving policy advice!" I wasn't alive, but I imagine there existed a similar complacency before the 1970s.

Then 2008 came, and suddenly everyone was scrambling to update and modify the models. No doubt the new crop of finance-including models will be able to tell a coherent, plausible-sounding story of why the 2008 Financial Crisis led to the Great Recession. (In fact, I suspect quite a number of mutually conflicting models will be able to tell different plausible-sounding stories.) And then we'll sit back and smile and say "Hey, look, we explained it!"

But maybe we didn't.

Of course, this doesn't necessarily mean macroeconomists could do a lot better. Maybe this is the best we can do, or close to it. Maybe time-series data is so inherently limited, data collection so poor, and macroeconomies so hideously complex, non-ergodic, and chaotic that we're never going to able to have predictive, general models of the macroeconomy, no matter how many crises we observe. In fact, I wouldn't be terribly surprised if this turned out to be the case. But I think at least we could try, a little more pre-emptively than in the past. And I think that if we didn't tend to oversell the power of the models we have, we wouldn't be so embarrassed when the next crisis comes along and smashes them to bits.

How much value does the finance industry create?

That is the question asked by John Cochrane in this recent draft essay (non-PDF version here), in response to a recent Journal of Economic Perspectives article by Robin Greenwood and David Scharfstein. Both should be required reading for any introductory finance class. There is so much in these essays that one blog post couldn't hope to adequately cover the topic, so don't expect this to be anything resembling a complete response.

Everyone knows that the finance industry has grown in America. In 1980, finance took home about 5% of all the income in America; in 2007, about 8%. This has led many people to question whether all this activity is worth what we pay for it; in other words, how much of the increase in finance-industry GDP is actually value added, and how much is "rent" extracted from the rest of the economy?

Cochrane makes the excellent point that the question of "How much value does industry X really create?" is always an incredibly difficult question to answer:

I don’t claim to estimate the socially-optimal “size of finance” at 8.267% of GDP, so there...After all, if a bunch of academics could sit around our offices and decide which industries were “too big,” which ones were “too small,” and close our papers with “policy recommendations” to remedy the matter, central planning would have worked.  A little...modesty suggests we focus on documenting the distortions, not pronouncing on optimal industry sizes.  Documenting distortions has also been, historically, far more productive than pronouncing on the optimal size of industries, optimal compensation of executives, “global imbalances,” “savings gluts,” “excessive consumption,” or other outcomes. 

Cochrane also describes how we should go about documenting the distortions:

We start with the first welfare theorem: loosely, supply, demand and competition lead to socially beneficial arrangements.  Yet the world around often doesn’t obviously conform to simple supply and demand arguments...First, maybe there is something about the situation we don’t understand. Durable institutions and arrangements, despite competition and lack of government interference, sometimes take us years to understand. Second, maybe there is a “market failure,” an externality, public good, natural monopoly, asymmetric information, or missing market, that explains our puzzle. Third, we often discover a “government failure,” that the puzzling aspect of our world is an unintended consequence of law or regulation. The regulators got captured, the market innovated around a regulation, or legal restrictions stop supply and demand from working. 

This list applies to almost any policy question in all of economics. Sometimes, policy fails. Sometimes, the market fails. And sometimes things are working better than we realize, with our limited data and models.

In casual discussions of finance in the media and blogs, we've heard all of these ideas before. The idea that finance is excessively large due to collusion with the government (policy failure) is probably the most prominent - this is the idea that big banks have the government in their pocket, allowing them to dump their risk onto the taxpayer (through bailouts) while keeping their gains for themselves. Market failure - "How does making 10 billion trades a minute benefit anyone?" - is also something you hear about. And of course, there is always the question of "If large parts of finance are valueless, why would people, especially rich people who are probably pretty savvy, pay for these things? Maybe value is being created and we just don't understand it."

It's important to belabor this last point. Economists know some things, maybe a lot of things, but this is absolutely dwarfed by the size of the things we don't know and don't understand. If this blog has had one "unifying theme," it would be the depth of our ignorance. So when economists urge caution in using policy to change large sectors of the economy, this doesn't necessarily mean "We know that the free market is always perfect and good and that policy can't help." (That is something that ideological libertarians often say, and I think it's extremely unhelpful for the econ profession when they say it.)

Instead, caution about policy is very similar to doctors' maxim of "first, do no harm." As a doctor, you wouldn't say "I can't figure out how this organ is helping the body function, so let's just take it out." Similarly, it would be foolish to say "I don't see how this finance industry is adding value, so let's regulate the heck out of it." We start with the presumption that things are there for a reason - in biology, because evolution put them there, and in economics, because...evolution put them there.

Of course, if the organ explodes and threatens the rest of the body, then you take it out. And when an industry explodes, like the finance industry did, you use policy to manage the damage. And if you can, you figure out why this organ, or this industry, tends to explode, and you figure out if there are ways you can prevent an explosion, or see it coming, without creating nasty side effects.

But the question of whether finance is unstable and tends to explode (and how to deal with that) is very different from the question of whether its compensation is equal to its value added. People should understand that difference!

Anyway, on to the meat of the issue. Again, there's way too much for one blog post, so I'll just add a few thoughts of my own. Really, you should go and read both. Twice.

In their JEP article, Greenwood and Scharfstein chart the well-known growth of the finance industry in America. They identify which areas of finance have grown. Basically, the big growth areas were 1) asset management, and 2) housing-related finance. Asset management grew because a lot of assets went up a lot in value (think of the stock boom in the 1990s), and asset managers continued to charge the same fees as before. When assets do better, the same percentage fee gets you a lot more money, so this caused the finance sector to grow. As for housing-related finance, this has been much-discussed in the media; it includes shadow banking and the entire apparatus that was developed to handle trading of mortgage-backed assets.

Greenwood & Scharfstein also briefly discuss ways that these expanded activities might cost more than their value-added. Cochrane's essay, on the other hand, is all about this question. Cochrane basically runs down the full list of finance-sector activities whose value has been called into question, and discusses the ways that each activity might add value. Handing your money to an asset manager and paying a proportional fee, for example, may be highly preferable to doing your own asset-picking, which research shows to be a losing game. Here's Cochrane:

Individual investors, many of whom actively manage their portfolios and whose decisions in doing so are the stuff [of] many behavioral biases, may be doing a lot better with 1% active management fee than actively managing on their own. As a matter of fact, individual investors are moving from active funds to passive funds, and fees in each fund are declining. Many of their fee advisers are bundling more and more services, such as tax and estate planning, which easily justify fees. At least naiveté is declining over time. 

Quite true. And I think Cochrane leaves out another possible function of money managers - the "money doctors" idea being promulgated by Andrei Schleifer. This is the idea that even if people are willing to take risks in exchange for returns, they have emotional fear of actually pulling the trigger and investing in long-term, high-return assets like stocks. Asset managers, by holding rich people's hands and appearing very professional and knowledgeable, calm this fear, much as doctors make people less afraid of taking pills. Even a money manager whose fees exceed his "alpha" may be creating value for society by overcoming human anxiety and stopping rich people's capital from sitting trapped in big stacks of gold bars in their basements. Voila - value creation.

Then again, I think Cochrane also leaves out a reason for concern. We know people are bad at picking stocks, in large part because they trade too much. What if people are bad at picking asset managers for exactly the same reason? If individual investors (or institutional investors like pension fund managers) act like "funds of funds", might they not switch their money rapidly from hedge fund to hedge fund, chasing recent performance, much like day traders ineptly picking stocks? This sort of "higher-level over-trading" could be very costly and bad for markets - after all, haven't we all heard the horror stories of hedge funds who saw a big opportunity coming, but had to close out their position and take a loss because their investors backed out too soon? That sort of thing could create large costs for asset managers, who are then forced to pass on those costs to investors via higher fees. Voila - value destruction.

As for the heavy trading we observe in financial markets, it seems to be necessary in order to incorporate information into the prices of financial assets. Of course, it could create problems as well. Cochrane sums up the dilemma very nicely:

I conclude that information trading...sits at the conflict of two externalities / public goods. On the one hand...“price impact” means that traders are not able to appropriate the full value of the information they bring, so there can be too few resources devoted to information production (and digestion, which strikes me as far more important). On the other hand, as Greenwood and Scharfstein point out, information is a non-rival good, and its exploitation in financial markets is a tournament (first to use it gets all the benefit) so the theorem that profits you make equal the social benefit of its production is false. It is indeed a waste of resources to bring information to the market a few minutes early, when that information will be revealed for free a few minutes later.  Whether we have “too much” trading, too many resources devoted to finding information that somebody already has in will be revealed in a few minutes, or “too little” trading, markets where prices go for long times not reflecting important information, as many argued during the financial crisis, seems like a topic which neither theory nor empirical work has answered with any sort of clarity.

Exactly.

Cochrane goes on to discuss "information trading" in great detail, and I encourage you to read everything else he has to say on the topic.

One related area of research that Cochrane doesn't mention, by the way, concerns the question of excess volatility, as famously discovered by Robert Shiller and demonstrated repeatedly since then. Even an asset market that is "efficient" in the academic-finance-prof sense of the word - i.e., unpredictable - may still swing more wildly than the real value of the assets. This can happen if people trade based on "noise" - if they believe that false information is actually true. A lot of the "information trading" people do may actually just serve to incorporate false information, rumors, and noise into the prices. That's clearly not a value-adding activity, and it does incur trading costs. This could be closely related to the tendency of investors to over-trade, but at an aggregate level instead of an individual level. If there's something coordinating the "noise traders" - some sort of fad or mass sentiment or herd behavior - then the same force that causes people to switch their stock holdings too often might cause markets to gyrate, racking up trading costs but destroying value. This is a separate issue from the issue of "tournaments", and also one that needs to be answered quantitatively (again, easier said than done!).

Cochrane also discusses the "shadow banking system" that was set up to do housing finance in the 2000s. I won't go over all that, but you should read it. I would, however, like to highlight this interesting point:

In any case, following the 2007-2008 financial crisis, and perhaps more importantly the collapse of short-term interest rates to zero and the innovation that bank reserves pay interest, this form of “shadow banking” has essentially ceased to exist. RIP.   

To drive home this point (and to complain about any analysis of the size of finance that stops in 2007), here are two graphs representing the size of the “shadow banking system,” culled from other papers. From Adrian and Ashcraft (2012, p. 24), the size of the securitized debt market... 

 

And from Gorton and Metrick (2012), a different slice of securitized debt markets:  

This highlights an interesting point that often gets lost in discussions like this: Value-destroying activities often get naturally eliminated over time. This is evolution at work.

There are other examples. For instance, in Liar's Poker, Michael Lewis describes his job as basically being the ripping off of fools. As a bond salesman for Salomon Brothers in the 80s, he basically had a rolodex full of fools, many of them in Europe. When a client wanted to rip off a fool, he would call up Salomon, and Michael Lewis would find a fool to take the bad end of the trade, earning middleman fees in the process. Or sometimes, Salomon traders themselves, doing "proprietary trades" with the firm's own portfolio, would do the ripping off. In any case, eventually the fools wised up, and Salomon collapsed and was bought out. That wasn't the end of "face-ripping," though, as the broker-dealer industry came to call the practice. If you believe Greg Smith, it was alive and well at Goldman Sachs in the 2000s. Note that it's perfectly legal to take a fool's money. Broker-dealers have no fiduciary duty to their clients when acting as middlemen. But it still seems like a value-destroying activity, and over time, a firm or industry that does it will lose its reputation and lose its clients. That is evolution in action.

The real questions here are, 1) how long will evolution take, 3) what will be the collateral damage when a value-destroying business dies out, and 3) can policy act faster than evolution, in a reliable manner, to curb value-destroying industries before nature curbs them?

In other words, the bar for policy intervention to curb value-destroying industries should be pretty high here. Eventually, swindlers, hucksters, and useless rentiers will be driven from the market. When we contemplate giving them a kick to speed them on their way out, not only must we ask ourselves "Is this activity value-creating?", but also "Can policy improve the situation fast enough, and safely enough, to justify the possibility that policy might make a mistake?" Just as in medicine, many treatments may not be wort the risk, even if they are effective.

Anyway, this is getting long, and I've barely even scratched the surface of the relevant issues. You can spend your entire life thinking about these issues, and barely even scratch the surface (though you may add lots of value to society!). If you are interested in the question of whether finance is worth it, go read Greenwood & Scharfstein, and go read Cochrane. But don't expect to come away satisfied that you know the answers! As in many areas of human endeavor, the size of our understanding is dwarfed by the size of our ignorance.

Gold, gold, GOLD!!!

On November 11, 2011, Zero Hedge ran a post from a site called GoldCore. The title was: "Gold Over EUR 1,300 - On Way to ‘Infinity’ on Eurozone Contagion?" Here is what it said:

The unprecedented scale of the [European] debt crisis means that inflation and currency devaluations will almost certainly result from the crisis. Savers and those on fixed incomes will be very vulnerable as they were in the stagflation of the 1970’s and in the economic meltdowns seen in Argentina, Russia and in Belarus as we speak... 

However, the US is itself facing a debt crisis which is also of a monumental scale. It is of a scale that it cannot be resolved by the usual kneejerk resorting to the printing presses and today’s equivalent panacea - computer credit creation... 

Ron Paul gave another perceptive interview to CNBC yesterday and warned of hyperinflation and the possibility that the dollar could become worthless. 

When asked how high the gold price would go and why, he responded: 

“well, the question is how much lower is the dollar going to go in purchasing power? and I said to infinity unless we change our ways."

Here, courtesy of Goldprice.org, is a picture of gold prices over the past two years. Note that the Zero Hedge post appeared a few months after the peak:

For comparison, courtesy of Yahoo Finance, here is the S&P 500 over the same period:

Now, if you believed the Zero Hedge post, and immediately went out and invested $100 in gold, you would now have $17 less than a friend who ran out and invested $100 in an S&P index fund.

On March 6, 2012, Zero Hedge ran a post of its own, titled "Stay Long Gold", citing Morgan Stanley. If you believed that Zero Hedge post, and immediately went out and invested $100 in gold, you would now have $9.60 less than a friend who ran out and invested $100 in an S&P index fund.

Goldbugs and Zero Hedge fans who read these facts tend to make one or more of the following responses:

1. "You're cherry-picking. Go back 5 years and see how much gold has beaten stocks. Or 10 years."

2. "Look how much money central banks are printing. Obviously, fiat money is going to become worthless, and gold will be left as the one true form of money."

3. "OK, dude, whatever you say, look how much money I made investing in gold! Who's the fool now, huh?"

4. "Gold and stocks aren't substitutes. Gold is an important part of a diversified portfolio."

Number 1, of course, is just counter-cherry-picking. The S&P has beaten gold over every 30-year period of history, ever. Why 30 years? Well, it's a standard "long-term" investment horizon. But the same is true for 40 years, 50 years, etc.

Number 2 really fails to understand a basic idea about financial markets. If it's obvious that central bank money-printing will drive up the value of gold, why isn't that fact already incorporated into gold prices? In other words, the only central bank actions that should make gold prices rise are surprise actions - like printing even more money than people thought.

Now, Zero Hedge and the whole "goldbugosphere" tries to push the idea that they understand macroeconomics better than everyone else out there - that what is "obvious" to them is not obvious to most of the world, which is still in thrall to (Keynesians, neoclassical econ, Xenu, take your pick). 

But this also does not mean that gold prices can be expected to rise. Because even if it's true - suppose goldbugs are much much wiser and savvier than the rest of humanity - the only reason goldbugs wouldn't have already been able to push gold to its optimal price would be if goldbugs were liquidity constrained. But if that's the case, the only people who will believe in the predictions of higher gold prices will, by definition, be people who are unable to take advantage of their superior wisdom and savvy.

As for Number 3, note how it exploits a fairly well-known behavioral bias: Envy. When the gold flogger proudly boasts that "I made a fortune in gold!", people feel like unless they do the same, they aren't as smart as the guy making the boast. There's a knee-jerk psychological reaction of "If you can do it, well by golly, I can too!"

But notice how crazy this is. Even if you're as smart as the goldbug, it doesn't mean that you can replicate his success just by buying the same thing he bought. In fact, chances are you can't. Chances are, the huge gains that gold has seen over the past decade were a one-off event, not to repeated anytime soon. 

Investing is an area of human endeavor in which copying other people is not a surefire route to success. This makes it different from many other areas of life. If someone says "I tried the Atkins diet and I lost 40 lbs.!", then - assuming they're not BSing you - there's a pretty good chance that you too can lose 40 lbs. with the Atkins diet. Just copy best practice. But in investing, "copying best practice" by buying what the winners buy is actually just herd behavior, and is likely to make you lose money. Gold is not the Atkins Diet.

Of course, Zero Hedge knows this, and it knows that by creating this myth that "anyone can get rich by investing in gold", it can play on your own behavioral biases. Note that this is not the only bias they cleverly exploit - they also try to play to your masculinity in order to strengthen your overconfidence.

(As for Number 4, well, it might be right. But you shouldn't need Zero Hedge articles to tell you to diversify your portfolio! And let's be real: articles with titles like "Gold headed to infinity" and "Stay long gold" are not really articles about portfolio diversification.)

Note how there's a common theme here: Past performance is no guarantee of future results. According to "efficient" markets theory, past performance is unrelated to future results. According to behavioral finance research, future results will actually tend to reverse past performance, possibly because so many silly people exhibit herd behavior and jump on bandwagons.

Of course, as anyone knows who has ever tried to reason with goldbugs, this post is likely to fall mostly on deaf ears. But if you've had Zero Hedgie types brag to you about how much money they made investing in gold, don't feel bad. Look at their results in the last year and a half. And quietly snicker.


Update: as a commenter pointed out, Zero Hedge is probably just "talking their book". They own a bunch of gold, so right up until the point they're ready to dump it, they'll say "Buy, buy, buy!" Then they dump it, then they start yelling "Sell, sell, sell!" If it works, it's the old pump-and-dump scam, which is illegal when you do it to a stock, but perfectly legal to do when it's a whole asset class, like gold. Of course, Zero Hedge probably doesn't have a lot of ability to move gold prices, but why not try? In the meantime, they make money selling ads for their website. There's really no downside for them.

New Atlantic column: Redistribution in the age of robots

I have a new Atlantic column, about how to prevent extreme inequality after most human tasks are replaced by automation. Excerpts:

For most of modern history, inequality has been a manageable problem. The reason is that no matter how unequal things get, most people are born with something valuable: the ability to work, to learn, and to earn money. In economist-ese, people are born with an "endowment of human capital."... 

But in the past ten years, something has changed. Labor's share of income has steadily declined, falling by several percentage points since 2000. It now sits at around 60% or lower. The fall of labor income, and the rise of capital income, has contributed to America's growing inequality... 

The big question is: What do we do if and when our old mechanisms for coping with inequality break down?..A society with cheap robot labor would be an incredibly prosperous one, but we will need to find some way for the vast majority of human beings to share in that prosperity, or we risk the kinds of dystopian outcomes that now exist only in science fiction. 

How do we fairly distribute income and wealth in the age of the robots?... 

First of all, it should be easier for the common people to own their own capital - their own private army of robots. That will mean making "small business owner" a much more common occupation than it is today... 

More families would benefit from owning stock in big companies...All large firms should be given incentives to list publicly. This will definitely mean reforming regulations like Sarbanes-Oxley that make it risky and difficult to go public; it may also mean tax incentives... 

And then there are more extreme measures...What if, when each citizen turns 18, the government bought him or her a diversified portfolio of equity?...This portfolio of capital ownership would act as an insurance policy for each human worker; if technological improvements reduced the value of that person's labor, he or she would reap compensating benefits through increased dividends and capital gains. This would essentially be like the kind of socialist land reforms proposed in highly unequal Latin American countries, only redistributing stock instead of land.

Read the rest here!

A few thoughts on depression

This post isn't about economics at all, just to warn you.

Like everyone else, I'm very sad to hear about the suicide of Aaron Swartz, the gifted programmer and activist. I had heard of him a few times, but never really knew all the things he did. I wish I could have known him. Really, that's the worst thing about people dying...all the living people who will never get to benefit from their continued existence.

What do I have to say about Swartz' death? Well, maybe a little bit, since Swartz is said to have suffered from clinical depression. I do know a little bit about this topic, since I myself have struggled with depression for over a decade. Mine was first triggered by the sudden death of my mother in 1999, although I also have a family history of depression on my mom's side (the Swartz side, ironically, though I don't think Aaron and I were related). 

Obviously, everyone's experience of depression is different, so I don't intend these thoughts to be a universal guide or general theory. Also, bipolar disorder, or "manic depression", is another thing entirely. But that said, here are my thoughts on depression.

1. Depression is not sadness. During the most intense part of a major-depressive episode, what I've felt is nothing at all like sadness. Mostly, it's a kind of numbness, and utter lack of desire and will. Underneath that numbness, there's the sense that something awful is happening - there's a very small voice screaming in the back of your mind, but you hear it only faintly. There's an uncomfortable wrongness to everything, like the world is twisted and broken in some terrible but unidentifiable way. You feel numb, but it's an incredibly bad sort of numbness. This is accompanied by a strange lack of volition - if a genie popped out and offered me three wishes at the depth of my depression, my first wish would be for him to go away and not bother me about the other two. Looking back on this experience, I've conjectured that part of depression might be like some kind of mental "fire sprinkler system" - the brain just floods the building completely to keep it from burning down.

Depressed people often remark that it's impossible to remember what depression is like after it's over, and impossible to imagine feeling any other way when you're in the middle of it. Therefore, most of what I'm saying here comes from things I wrote when I was in the middle of major depressive episodes. I think my most colorful description was that depression was like "being staked out in the middle of a burning desert with a spear through your chest pinning you to the ground, with your eyelids cut off, staring up at the burning sun...forever." 

2. Coming out of depression is the most dangerous time. Coming out of depression, I've found, is like having your emotional system turned back on. But when it's turning back on, it sputters and backfires. You feel incredibly raw. You have days where you feel elated, like you're walking on air. And you have days when you feel black despair, rage, hysterical sadness. These latter are the only times that I've seriously thought about harming myself. And I've done a few...unwise things during these periods.

One of the most common negative episodes, for me, is what I've heard people call the "spiral" - a flood of negative emotions makes you feel like you're bringing down the people around you, which triggers more negative emotions, etc. I often experience this when coming out of depression. It comes on very rapidly. If you see this happening to a depressed person, get them away from large groups of people and high-energy social situations, as fast as possible.

3. Depressed people don't need good listeners, a sympathetic ear, or a shoulder to cry on. Most of the time, when our friends are having life problems, what they need is a sympathetic ear. They need someone to listen to their problems, to understand and accept the validity of their feelings, and to empathize. So when our friends have depression, the natural urge is to sit there and listen, and ask "What's it like?", and "Why do you feel that way?", and to nod, and make a concerned face, and tell them you understand (even though you don't), and to give them a hug. This is a good impulse, but when the person is depressed rather than sad, it's a completely misplaced impulse. This is not what depressed people need, and although it doesn't hurt them, in my experience it doesn't do them any good at all. One reason is that depressed people tend not to think that anyone can really understand what they're going through (and in fact it's very hard for a non-depressed person to understand, thank God). Another is that, while for a normal sad person, getting negative thoughts out in the open helps expunge them, for depressed people airing the negative thoughts just forces them to think their negative thoughts, without expunging them. Another is that the emotional disconnection that I mentioned in point 1 tends to short-circuit the warm, good feeling that usually comes from someone being sympathetic and friendly toward you.

4. Depressed people do need human company. For some reason, human company helps. In fact, it is the single thing that helps the most. But not the kind of company a sad person needs. What a depressed person needs is simply to talk to people, not about their problems or their negative thoughts or their depression, but about anything else - music, animals, science. The most helpful topic of conversation, I've found, is absurdity - just talking about utterly ridiculous things, gross things, vulgar offensive things, bizarre things. Shared activities, like going on a hike or playing sports, are OK, but talking is much, much more important. I really have never figured out why this works, but it does.

And of course, relationships are very, very important. Friends, I think, are the most important, because friends offer opportunity for understanding and positive interaction without much feeling of obligation or shame (see point 6). Family and lovers are important, but really, the friendship component of these relationships has to dominate, so the depressed person doesn't constantly think negative thoughts about how they've let you down. Essentially, to help a depressed person, friends need to become a bit more like family, and family a bit more like friends. Also, you should realize that just because your depressed friend or family member is unresponsive, that doesn't mean that you aren't doing him or her a lot of good.

5. Cognitive behavioral therapy really works. I've taken one antidepressant drug (Lexapro), but it did nothing perceptible for me. (This is not to say that antidepressants in general don't work; for that, ask PubMed. This is just about my personal experience.) What has worked for me is cognitive behavioral therapy. The "cognitive part" is the most important. Basically, depressed people have negative thoughts that they can't get out of their head; cognitive therapy teaches you to habitually identify, examine, and correct these negative thoughts. That really helps; once those negative thoughts aren't always racing unnoticed through the back of your mind, your brain has a much easier time repairing the damage done by a depressive episode. Also, "behavioral" therapies can be important for improving your lifestyle. 

Cognitive behavioral therapy is best done by a counseling therapist, and there are many good therapists, but also many crappy ones. It is easy to see who is good and who is crappy, but since depressed people have low volition, sometimes they need a push to ditch a bad therapist and keep looking for a good one.

6. Depressed people may need a new "narrative". I've also called this a "new perspective", but I think the word "narrative" fits better. I've discussed my "narrative theory of depression" at length with psychotherapists. Keep in mind that this theory of mine might be wrong, and even if it's right, it might only be right for a subset of depressed people!

Basically, I think that the most important repetitive negative thought that afflicts depressed people is negative self-evaluation. You think, in a very detached, dissociated way, "The person who I call 'me' is a worthless person." And I think that the main criterion that we use to evaluate people is the narrative; a story that seems to unify and make sense of a person's life. Obviously, this is not a realistic or accurate method; human beings are not consistent, we are not simple, and we don't make sense. The narratives that we construct for ourselves are mostly bullshit. We construct them out of a need to make sense of the world, not as rational scientific theories that best fit the available data. 

I feel like most people construct a narrative of their life that is basically positive. People tend to think that they are good, and also talented and special, and that their life is progressing toward some purpose. We are each the protagonist in our own story. This narrative gives them motivation, and also the overconfidence they need to take risks and exert effort (Ha! I managed to slip in a behavioral econ reference after all!). People also strive to fit their positive narratives. The part of people that conducts self-evaluations - the "internal performance review" component of the psyche, if you will - observes how well the person is living up to the positive narrative, and tries to correct deviations.

But sometimes, for some reason, people become fixated on a negative personal narrative. Instead of the protagonist or hero of the story of your life, you become the villain, or the tragedic failure. Instead of Luke Skywalker, you become Oedipus. And because we construct our narratives to have false consistency, the negative narrative starts to color absolutely everything you do. You start to see every action you take as backed by bad motives, or as doomed to failure. You perceive every emotion as base and reprehensible. The "internal performance review" part of yourself, whose task it usually to keep you toeing the line of the positive narrative, begins to throw up its hands and wish that it could just get rid of you completely.

Obviously, this could lead to some very bad things.

I believe that many depressed people are constantly afflicted by the crushing negative feedback of a negative personal narrative. And I've found that the biggest single thing that helps people out of depression is the scrapping of the negative narrative and its replacement with a positive alternative narrative. This is usually possible, because narratives are mostly constructed out of bullshit - replace the bad bullshit with good bullshit, and you win. But that is much easier said than done.

If you have depressed friends, you can, in theory, help them construct a new, positive narrative for themselves. But this is a very difficult thing to do, because a coherent, believable narrative is a rare thing, and you never quite know what will stick and what will be rejected. The good news is, if you try and fail, your depressed friend will be no worse off. Remember, depressed people are weak-willed, they have low volition and little initiative; to help your depressed friend construct a new narrative, you have to be pro-active. You've got to spontaneously volunteer positive perspectives on his or her life, without being asked to do so. 

This goes against our social instincts, since with a normal, non-depressed sad friend, doing this is kind of a mean thing to do; the friend just needs you to listen and understand, not to contradict, reinterpret, and dismiss their pain. But a depressed person is not sad, and what they need is very different from what a non-depressed sad friend needs. I'm not saying you should be an aggressive jerk, and berate your friends for thinking negative thoughts. Nor am I saying you should project fake sunny optimism about your friend's life. It takes a lot more honesty than that, not to mention finesse and creativity and careful guesswork about the nature of your friend's "negative narrative". So go slowly and carefully.

As for what kind of positive narrative to help your depressed friend construct...well, this will be very different for each person, and it will depend on what kind of negative narrative they've constructed for themselves. In general, though, I'd say that it's good to reinterpret past "failures" as necessary steps on the road to future successes. And it's important to emphasize how much potential the depressed person still has in their future - like in the movie City Slickers, when Billy Crystal convinces his depressed friend that he gets to have a "do-over" in life. In general, if you can help a depressed person visualize a different and positive future, he or she will entertain the notion that his or her past "mistakes" might have just been "Act Two" in a three-act romance, instead of the final act in a Greek tragedy.

Now, I am not saying that construction of this "new narrative" is a cure for depression. It is a complement to things like cognitive behavioral therapy, constant low-pressure human interaction, a healthy lifestyle, etc.

7. Depressed people always need to be vigilant against a relapse. Depression is like cancer - once you have it, it remits, possibly forever, but you are never "cured". Relapses are not certain, but the danger will always be there. Therefore, after recovering from a depressive episode, a depressed person must change his or her life completely and permanently. The things that you did to get out of depression, you must never stop doing for the rest of your life. You must permanently place a greater emphasis on human contact and on meaningful, positive, healthy relationships of all kinds. You must constantly think about what makes you happy and how to get it, and you must constantly take steps toward a positive future that you envision for yourself. If you allow yourself to coast, or get stuck in a rut, you will fall back into the pit and have to start all over again. And if therapy helped you, keep going to therapy forever. What's more, if you get out of depression, do lots of things to remind you about what got you out of it. Turn it into a story of personal triumph, and repeat that story to yourself. And never forget to solidify, cement, embellish, and elaborate a positive narrative of your life.

Anyway, that's the short version of my thoughts on depression. The long version could fill books. Maybe someday it will. In the meantime, remember, depression is real. It's among the worst things that can happen to you. But it is beatable.

Is Shinzo Abe the Great Keynesian Hope?

A lot of people were very excited about Shinzo Abe's talk of revoking the Bank of Japan's independence and forcing the Bank to adopt a far more expansionary/easy/inflationary monetary policy. I was not among them. I said that Abe was just "talking down the yen". This now seems to have become the conventional wisdom in the press, though as Paul Krugman points out, talking down the yen is a good (if not revolutionary) idea in its own right.

Now, here comes Abe with some Keynesian magic: an "emergency stimulus" package worth over $100 billion.

Is this for real? Well, sure, it's for real. And it will probably continue. So Keynesians should be happy. But they should also realize that the reason for Japan's new "stimulus" has nothing to do with Keynesian ideas. Instead, it has to do with re-establishing traditional back-scratching relationships between the LDP and its grassroots supporter base.

Shinzo Abe's party, the "Liberal Democratic Party" (the name of which always reminded me of "Holy Roman Empire"), held onto power for 55 years. It was supported by the bureaucracy and big business - the other legs of the so-called "iron triangle". But Japan is a democracy, so the LDP needed to get votes...and with Japan's extremely restrictive campaign financing and advertising laws, this was difficult to do the way Americans did it. 

So instead, as political scientist Ethan Scheiner explains in his classic book Democracy Without Competition in Japan: Opposition Failure in a One-Party Dominant State (see a summary here) the LDP resorted to a system called "clientelism". Basically, Japan's central government gave pork directly to groups who would go and campaign for them. Chief among these were construction companies. These companies employed a bunch of blue-collar dudes, usually in the rural areas (which, like in the U.S., wield disproportionate electoral power). Some of these dudes worked as part-time farmers; some of them belonged to right-wing Tea Party type groups. Most of the companies themselves were mafia-owned. The LDP would dish out pork, and the construction companies would basically become campaign staff for LDP politicians - knocking on doors, putting up posters, making calls, etc. It was a tit-for-tat relationship, and it worked for decades. In the 1990s, Japan's massive (and famously wasteful) construction spending binge, billed as fiscal stimulus, went mostly to these groups.

In the early 2000s, things changed, with the ascent to power of Junichiro Koizumi, the LDP's famous maverick reformer. He tweaked Japan's electoral system to make it much harder to win office by using private armies of door-knockers (Update: A commenter helpfully reminds me that reform of this system actually began in the early 90s, when an opposition coalition briefly took power due to an LDP split). He also cracked down hard on construction spending. This austerity was offset by much looser monetary policy; the Bank of Japan embarked on a program of quantitative easing (actually the world's first). 

Anyway, the tweaked electoral system, lower "clientelist" pork spending, and the disastrous unpopularity of Abe's first tenure as prime minister helped ushed the DPJ into power, breaking the LDP's 55-year run. But now the LDP is back, and they need to re-establish their base of support. This means re-establishing the back-scratching relationship with those construction firms (and, by extension, rural Japan, right-wing Tea Party type groups, and the mafia). The LDP needs to say "Hey, guys, things are back to the way they were." This, I suspect, is the main reason for the "emergency stimulus".

All of which doesn't mean that fiscal stimulus isn't a good idea for Japan. After all, money is still getting spent! But it does mean that we can expect construction pork spending to continue if and when Japan's economy recovers. That knowledge should affect businesses' expectations in the present, making the stimulus somewhat less effective in the present.

(Also there's the side question of whether Japan needs stimulus right now. On one hand, I think there's evidence that pork-barrel spending in the 1990s, while not necessarily worth the ultimate costs, did make Japan's post-bubble slump a lot less painful than it otherwise would have been. And of course interest rates are at the Zero Lower Bound, and Japan could use a little inflation. On the other hand, Japan's unemployment rate is only 4.2%, meaning there might not be that much actual slack in Japan's economy. And a lot of the stimulus spending is likely to be wasteful (much more so than, say, infrastructure spending in the U.S.), both because Japan's infrastructure (unlike ours!) is overbuilt, and because of the political nature of the spending. That will lower the multiplier.)

To sum up: Once again, I think that Abe's appearance as a bold Keynesian experimenter is a cover for a program of traditional mercantilism and corporatism. I guess we'll see how well that program works.


Update: A Japanese translation of this post is available here.