The Axis is back

More BS amateur geopolitical thinking from yours truly.

In 2002, David Frum came up with one of the more boneheaded rhetorical blunders in American speechwriting history when he coined the term "Axis of Evil" to describe a motley collection of totally unrelated rogue states. Evil it was in varying degrees, but it was no Axis. The states were not allies, and two of them were actually bitter enemies. Nor did they pose any threat to the United States.

But while we were messing around in Iraq, babysitting Sunnis and Shiites, burning our international prestige with a blowtorch, and spending trillions, something very ominous was happening. The actual Axis - something very like the coalition we faced in World War 2 - was reconstituting itself, like some sort of demonic fantasy-novel creature that gets defeated and dispersed but never really dies.

Of course, I'm talking about Russia and China, which have occasionally been dubbed the "Axis of Authoritarianism", though Frum's boneheadedness has probably soured people on "Axis" nicknames for a while. But nevertheless, I think the analogy is apt.

What happened in World War 2 was basically this: Two small, powerful states (Germany and Japan) tried to conquer the large Asian land empires next to them (Russia and China) while those giga-empires were in a moment of weakness. Eventually the little guys would have lost, but the U.S. hastened that loss by intervening on behalf of the big countries. The U.S. conquered the Axis countries and reconstituted them as economically strong but military weak mostly-isolationist states, setting them up as buffers against the two now-very-pissed-off empires. The big empires, Russia and China, opted for a system (communism) that was economically non-viable in the long term but in the short term gave them organizational capacity that allowed them to repel external military threats (obviously this happened earlier in Russia). The system they adopted put them in ideological conflict with America, the country that had just saved their butts, and America won the ensuing ideological struggle when communism turned out to be a long-term loser. This outcome was hastened by a bitter split between Russia and China, which showed that shared ideology is never a guarantee of durable geopolitical friendship.

OK, that brings us to 2000. Post-Cold War, Russia and China have both adopted systems that look a little bit like the systems of the countries that whooped up on them in World War 2. Putin's Russia is a nationalist country that places a lot of emphasis on race, and scapegoats minorities like gays, while not really having an economic ideology - a little like Nazi Germany, but far less insane, and much more dependent on natural resource exports. China is now a bureaucratic directed-capitalist state with a strong independent confident military, a feeling of national resentment over past mistreatment by powers near and far, and a feeling that its destiny is to dominate East Asia - a little like Imperial Japan, though less beset by domestic terrorism.

Meanwhile, the strategies being used by Russia and China are a little similar to those used by the actual Axis. Russia is gobbling up co-ethnic neighboring states, much as Hitler gobbled Austria and the Sudetenland. China is bullying the neighbors (though not grabbing territory outright quite yet, as Japan did). And the two have formed a friendship of convenience rather than a strong cooperative alliance, much like Germany and Japan did in the Axis. The similarity is probably because Europe and East Asia each lends itself to a certain geopolitical power-building approach.

Ideologically, neither Russia nor China is interested in foisting a universalist ideology on the world - but neither were Nazi Germany or Imperial Japan. Hitler didn't want everyone to agree that Germans were racially superior, he just wanted people to bow to him and do what he said (or die, or both). Same with Japan. It wasn't until the Cold War that competing trans-national global ideology really came into play (though it had been in play in some other conflicts in history.) The new Axis is generally more authoritarian than its opponents, generally respects human rights less, generally favors less stable borders (despite Chinese B.S. rhetoric about national sovereignty), and is generally more militarily aggressive (Iraq notwithstanding). These characteristics are what make the Axis the Axis and the Allies the Allies. But that's not what the conflict is about.

What the conflict is about, is domination of Eurasia, the big continent. I don't know why countries want to dominate this landmass - it seems kind of dumb to me - but they do. This time instead of unusually tough periphery countries trying to conquer and replace the core, the big core countries have got their act together (more or less) and are ready to retake their "rightful" place as emperors of the big continent. Meanwhile the little countries on the periphery, in Europe, East Asia, and Southeast Asia, just want to be independent from the power of the core countries. The U.S., halfway around the world, tries to play balancer and stabilize everything. The "Axis" is just whoever is trying to dominate Eurasia this week, and the "Allies" are just the U.S. plus whoever in Eurasia would rather not be dominated. Until either A) everyone realizes that dominating the vast expanses of interior Asia is pointless, or B) those expanses become populated and economically self-sufficient and divided up into a bunch of stable countries, an Axis will periodically form, and be countered by some Allies.

So that's kind of how I see things. The Axis is, for all intents and purposes, back. That doesn't mean we need to fight it in an apocalyptic war like last time. In fact, that would be a singularly bad idea. With nukes now involved, the cost is way too high. But we are probably in for a protracted struggle, unless the big core Eurasian countries suffer another falling-out or suffer some kind of surprising internal collapse.

Thursday Roundup, 8/28/2014

Ride em, cowblogs!

Me on BV

1. Japan needs the hammer of private equity to smash the rotting edifice of corporate inefficiency

2. RBC models: The null hypothesis that there is no business cycle

3. Let's make sure not to discriminate against Chinese-Americans if we go to war with China

4. In which I cast doubt on a study about marriage

5. Economics is neither science nor literature, but a third intellectual culture

6. Different groups are treated differently under the law in America


From Around the Econ Blogosphere

1. Acemoglu and Robinson think that people want central governments to protect people from local bullies. Libertarians, take note. Speaking of libertarians, it turns out that many American "libertarians" don't hold very libertarian beliefs.

2. Cathy O'Neil on why the Fields Medal is st00pid. She is correct. And by "correct" I mean "I agree". Also see Frances Coppola on why we give too much respect to Nobelists relative to other scholars.

3. Surveys claim to have found that Americans are a lot more conformist, and less individualistic, than Europeans. Hive minds, indeed.

4. Kevin Grier unleashes a hellacious rhetorical slap at Market Monetarism. OUCH OUCH OUCH

5. Tim Harford: Are monopolies quietly taking over our economy? Unsettling.

6. A well-known econ blog commenter gives a list of reasons not to believe Shiller's CAPE-based warnings about an overpriced stock market.

7. Scott Sumner claims that the switch to true fiat money (post-Bretton Woods) was the mother of all black swans. But he's wrong: Nassim Taleb is the mother of all black swans. See, I just called Nassim Taleb a girl, ha ha ha.

8. John Cochrane says the Fed has mostly done the right thing since the financial crisis. John Taylor's head just exploded. But his hair, curiously, is intact.

9. Michael Strain of AEI argues that we need better infrastructure. If conservatives really jump on this bandwagon, then I say it's morning in America.

10. A great list of quotes by economists dissing economics. It's not clear if they're just talking about macro, though.

11. Is active management dying? Sometimes these days it feels like the whole finance industry is a non-pressurized balloon with a hole in the side, slowly losing air. If so, will that hold down the salaries of econ profs, for whom the finance industry is one of the main outside options? But this question would take us too far afield.

12. Dan McFadden might be my favorite economist. Watch him give a talk about decision-making. Then bow before his awesome awesome-itude.

13. Tyler Cowen says that the way economists measure "trends" and "cycles" has some major problems. Tyler Cowen is quite correct. And by "correct" I mean "the data seem to agree".

14. Tim Harford: 4% inflation target 4% inflation target 4% inflation target 4% inflation target 4% inflation target 4% inflation target 4% inflation target 4% inflation target 4% inflation target...oh dash it all, we'll never get a 4% inflation target.

15. All MMT people should watch Chris Sims talk about how he thinks money and inflation work. Also, all MMT people should dress in gold spandex and throw tomatoes at cars while playing "She Loves You" by the Beatles on kazoos and doing a little bow-legged jig.

16. Josh Brown talks about how the toughest part of being a financial adviser is helping people curb their behavioral biases. Even harder than drinking liquid magma while wrestling a python.

17. Mark Buchanan asks why economists are so obsessed with the Arrow-Debreu result. My answer: Because a cabal of gynecologists and realtors has been secretly promoting Arrow-Debreu since the end of World War 2.

18. Bob Murphy thinks Scott Sumner is using the EMH like a just-so story to "explain" anything he sees in financial markets. Bob Murphy, perhaps a bit uncharacteristically, makes a really good point.

19. Are red-light cameras a form of tax farming? I wouldn't have asked that question if I didn't think the answer was "yes"...

20. Cardiff Garcia summarizes, and dares to gently critique, Autor's Jackson Hole paper.

I still don't understand the philosophy of Bayesian probability

Brad DeLong is having an extremely fascinating conversation with an E.E. Doc Smith deus ex machina character, an emulation of a Princeton professor, looser emulations of two famous dead probabilists, and a made-up Greek mediator himself about the philosophy of Bayesian probability (see also here). DeLong focuses on the question of whether probabilities should be "sharp" - i.e., whether we should always say "I believe the probability of the event is x%" (as Bayesians always do), or whether we should say something along the lines of "I believe the probability of the event is between x% and y%."

But I want to focus on a deeper question, which is: What is a probability in the first place? I mean, sure, it's a number between 0 and 1 that you assign to events in a probability space. But how should we use that mathematical concept to represent events in the real world? What observable things should we represent with those numbers, and how should we assign the numbers to the things?

The philosophy of Bayesian probability says that probabilities should be assigned to beliefs. But are beliefs observable? Only through actions. So one flavor (the dominant flavor?) of Bayesian probability theory says that you observe beliefs by watching people make bets. As DeLong writes:

Thomas Bayes: It is simple. [Nate Silver assigning a 60% probability to a GOP takeover of the Senate in 2014] means that Nate Silver stands ready to bet on [Republican] Senate control next January at odds of 2-3. 

Thrasymakhos: “Stands ready”? 

Thomas Bayes: Yes. He stands ready to make a (small) bet that the Majority Leader of the Senate will [not] be a Republican on January 5, 2015 if he gets at least 2-3 odds, and he stands ready to make a (small) bet that the Majority Leader of the Senate will not be a Republican on January 5, 2015 if he gets at least 3-2 odds.

DeLong is very careful to write "a (small) bet". If he wrote "a bet", we would have to introduce Nate Silver's risk aversion into our interpretation of the observed action, if the bet size were large. DeLong is assuming that a small bet will get rid of Silver's risk aversion.

However, there's a problem: DeLong's assumption, though characteristic of the decision theory used in most economic models, does not fit the evidence. People do seem to be risk-averse over small gambles. One (probably wrong) explanation for this is prospect theory. Loss aversion (one half of prospect theory) makes people care about losing, no matter how small the loss is. To back out beliefs from bets, you need a model of preferences. And that model might be right for one person at one time, but wrong for other people and/or other times!

But isn't that just a practical, technological problem? Why do we need real-world observation in order to define a philosophical notion? Well, we don't. We already defined a probability as a real number between 0 and 1 (which gets assigned to the latter slot in the tuples that are the elements of a probability measure). That's fine. But the Bayesian philosophical definition of probability, if it is to be more than "a number between 0 and 1," seems like it has to include a scientific component. The Bayesian notion of "probability as belief" explicitly posits a believer, and ascribes the probability to that real, observable entity (note: This is also why I think the "Weak Axiom of Revealed Preference" is not an axiom). If we can't observe the probability, then it doesn't exist - or, rather, it goes back to just being "a number between 0 and 1".

So can't we just posit a hypothetical purely rational person, and define beliefs as his bet odds? Well, it seems to me that this will probably lead to circular reasoning. "Rational" will probably be defined, in part, as "taking actions based on Bayesian beliefs." But the Bayesian beliefs, themselves, will be defined based on the actions taken by the person! This means that imagining this purely rational person gets us nowhere. Maybe there's a way around this, but I haven't thought of it.

Does all this mean that the definition of Bayesian probability is logically incoherent? No. It means that defining Bayesian probability without reference to preferences (or other decision-theoretical rules that stand in for preferences) is scientifically useless. In physics, a particle that interacts with no other particles - and is hence unobservable, even indirectly - might as well not exist. So by the same token, I claim that Bayesian probabilities might as well not exist independently of other elements of the decision theory in which they are included. You can't chop decision theory up into two parts; it's all or nothing.

I assume philosophers and decision-theory people thought of this long ago. In fact, I'm probably wrong; there's probably some key concept I'm missing here.

But does it matter? Well, yes. If I'm right, it means the argument over whether stock prices swing around because of badly-formed beliefs or because of hard-to-understand risk preferences is pretty useless; there's no fundamental divide between "behavioral" and "rational" theories of asset pricing.

It's also going to bear on the more complicated question Brad is thinking about. If you're talking to people who make decisions differently than you do, it might not be a good idea to report a number whose meaning is conditional on your own decision-making process (which your audience does not know). So that could be a reason not to report sharp probabilities to the public, even if you would make your own decisions in the standard Bayesian-with-canonical-risk-aversion way. But what you should do instead, I'm not sure.

A slight clarification about the "end of labor"

MIT prof and economic policy advisor David Autor has written an excellent new paper about labor market polarization, which you should read. In that paper, he cites an article I wrote for The Atlantic last year, discussing the possibility of "the end of labor." Mr. Autor makes it sound as if I believe the "end of labor" is coming, but in fact, I only think this is one possibility among many. The point of my article - which was inspired by this Larry Summers talk - was that the "end of labor" is something we should prepare to deal with, even if there is only a low probability of it happening. The mechanism for the "end of labor", of course, could be such a huge degree of skills-based labor market polarization that even small labor market frictions would be capable of creating huge amounts of equilibrium unemployment; alternatively, it could be a continuation of the trend of increasing capital share of income, as discussed in this paper.

The Atlantic, of course, got to pick the title of my piece (as all magazines do with all pieces), and understandably went with something attention-catching rather than something that would reflect the uncertainty I tried to express in the article itself.

But in any case, thanks to Mr. Autor for the mention.

RBC models we can believe in?

At Bloomberg View, I wrote an article trying to explain the basics of RBC models to the masses, and give a little history-of-thought. Of course anyone who actually knows the situation will realize that my treatment is pretty simplistic, but you try explaining RBC in 800 words to people who know nothing about modern academic macro, in a way that's entertaining and grabs eyeballs. It is harder than it sounds. ;-)

Anyway, the post only talked about the original, historical RBC model, and mentioned a couple follow-ups, such as news shock models. But if you define "RBC" as "any macro models where aggregate uncertainty is mainly driven by productivity shocks," then the field gets a lot wider. 

In fact, if you put a gun to my head and asked me why recessions happen, first I'd kiss my ass goodbye, but then I'd say that some of them happen because of sector-specific productivity shocks, amplified by network effects and by some departures from Rational Expectations. Actually, there are a number of models popping up that try to model something like this, and I think it's a hugely interesting literature. Here are a couple examples, with abstracts.

"Noisy Business Cycles", by George-Marios Angeletos and Jennifer La'O (2009)

This paper investigates a real-business-cycle economy that features dispersed information about the underlying aggregate productivity shocks, taste shocks, and, potentially, shocks to monopoly power. We show how the dispersion of information can (i) contribute to significant inertia in the response of macroeconomic outcomes to such shocks; (ii) induce a negative short-run response of employment to productivity shocks; (iii) imply that productivity shocks explain only a small fraction of high-frequency fluctuations; (iv) contribute to significant noise in the business cycle; (v) formalize a certain type of demand shocks within an RBC economy; and (vi) generate cyclical variation in observed Solow residuals and labor wedges. Importantly, none of these properties requires significant uncertainty about the underlying fundamentals: they rest on the heterogeneity of information and the strength of trade linkages in the economy, not the level of uncertainty. Finally, none of these properties are symptoms of inefficiency: apart from undoing monopoly distortions or providing the agents with more information, no policy intervention can improve upon the equilibrium allocations.

"The Network Origins of Aggregate Fluctuations", by Daron Acemoglu et al. (Econometrica 2012)

This paper argues that in the presence of intersectoral input-output linkages, microeconomic idiosyncratic shocks may lead to aggregate fluctuations. In particular, it shows that, as the economy becomes more disaggregated, the rate at which aggregate volatility decays is determined by the structure of the network capturing such linkages. Our main results provide a characterization of this relationship in terms of the importance of different sectors as suppliers to their immediate customers as well as their role as indirect suppliers to chains of downstream sectors. Such higher-order interconnections capture the possibility of “cascade effects” whereby productivity shocks to a sector propagate not only to its immediate downstream customers, but also indirectly to the rest of the economy. Our results highlight that sizable aggregate volatility is obtained from sectoral idiosyncratic shocks only if there exists significant asymmetry in the roles that sectors play as suppliers to others, and that the “sparseness” of the input-output matrix is unrelated to the nature of aggregate fluctuations.

And just for fun, I'm going to throw in "Intermediate Goods, Weak Links, and Superstars: A Theory of Economic Development", by Charles I. Jones (2008), which bills itself as a theory of development, but seems like it could pretty easily be modified to be a business-cycle theory for developed countries.

(Also there's this Gabaix paper, which is about firm-level heterogeneity. I originally included it here, but it doesn't really fit with the others so I took it out. Heterogeneity is a very different story from networks and complexity. Still, good to see heterogeneity getting more attention.)

The basic idea here is actually pretty simple. Angeletos actually said it, when he came to present his paper at Michigan: "One firm's productivity determines other firms' demand." In other words, these network models go way beyond the traditional, typical framework of aggregate supply and aggregate demand. (Other models also do this, but usually across time rather than across firms or sectors.) 

Like I said, if you held a gun to my head, I would say that something like this is actually going on in the actual economy. Why? Because aggregate shocks are sometimes really hard to identify. There were the oil price shocks in the 1970s and Volcker's tightening in the early 1980s, but a lot of recessions don't seem to be externally provoked. So maybe that means there is some kind of random mass-psychological sentiment thing going on, or maybe it means that recessions are sunspots caused by the interaction of a whole bunch of frictions, and thus completely unknowable. But this network/linkage idea seems like a promising alternative to those unhappy possibilities. That doesn't mean I think any of these models is right - they're all going to have empirical issues, because they are basically proof-of-concept papers. But I suspect they're on to something that many have expected for a long time - the idea that economic fluctuations are the result of the complexity of economic systems.

But explaining to Bloomberg View readers that these models may or may not deserve the moniker "RBC" would have distracted from my main point, which is to teach people a little about the history of macroeconomic thought (read: academic politics in the macro field), so someday I can explain my theory of why Mike Woodford is the most important macroeconomist in the world. But now I'm getting ahead of myself...

Thursday Roundup, 8/14/2014

Thursday Roundup is back! Saddle up, blog junkies.

Me on BV

1. Silicon Valley is solving the big problems (warning: sappiness)

2. The trend is your friend til the bend at the end (or, why "put option illusion" fools investors)

3. Barack Obama is no foreign policy wimp

4. Why I don't mind if someone calls me "stupid"

5. How hedge funds can "sharpen their Sharpe ratios" at investors' expense (featuring cool papers by Goetzmann et al. and Agarwal & Naik)


From Around the Econ Blogosphere

1. Alex Tabarrok continues to sound the alarm on FDA over-regulation of biomed technology. See also here.

2. Mark Thoma: The perennial disagreement among macroeconomists is due to a toxic mix of bad data and politics. Old news, but useful to repeat.

3. Miles Kimballl on how to turn your kid into a math person. No cyborg enhancements involved.

4. Mencius Moldbug has quit blogging. Street protests explode in cites across the globe. Antidepressant use spikes. Just kidding.

5. Roger Farmer thinks Mike Woodford is wrong about the irrelevance of QE. Good to see people realizing that Mike Woodford is the world's most important macroeconomist.

6. Data scientists are out there earning more than econ profs. Actually, data scientists have similar skill sets to empirical econ researchers.

7. Brad DeLong thinks about the philosophical problems of Bayesianism. This is something I've wondered about for a while, and I'm still not satisfied.

8. Bryan Caplan wonders if economics is based on common sense or not. This is something I've often wondered about. Most sciences prize "counterintuitive" findings. Does econ? Should econ? Should the other sciences, for that matter?

9. Robert VerBruggen thinks helping poor women delay childbearing could be a way to fight poverty.

10. John Cochrane and Anat Admati continue to fight the good fight for increased bank capital requirements. Thought: How about making them dependent on bank size, as a way of discouraging TBTF? (Not a new thought, but still a thought.)

Chris House on stimulus spending

Back in March, Chris House wrote a blog post explaining why he thinks that tax rebates make better stimulus than government spending. He concludes that tax rebates are the best form of stimulus, and that government spending projects should only be undertaken if the projects would pass a cost-benefit test in the absence of any stimulus effect. House:

If a project doesn’t meet the basic cost / benefit test, then it shouldn’t be funded, regardless of the need for stimulus...If the social value of a government project exceeds its social cost then we should continue to fund the project whether we are in a recession or not. If the social value falls short of the social cost then, even if the economy is in “dire need” of stimulus we should not fund it. If we really need stimulus but there are no socially viable projects in the queue then the government should use tax cuts... 

If the direct social benefit of a bridge is $100, then all the government needs to consider is whether the cost of building the bridge is greater or less than $100. If you then tell me that, because we are in a recession, there are additional stimulus benefits from the project (e.g., the workers who build the bridge take their new wage income and buy goods and services from other businesses further stimulating demand, increasing employment, and so on.), the government should exclude these additional benefits from its calculation.

I don't understand this assertion at all. It makes no sense to me.

Let's consider a simple numerical example. Suppose that the economy is in a recession. And suppose that, because of the Zero Lower Bound or whatever, the pure fiscal "multiplier" is substantial. Specifically, suppose that $100 of tax rebates will increase GDP by $110. In this case, stimulus spending is a "free lunch."

Now suppose that instead of doing tax rebates, the government can build a bridge. The social benefit of the bridge is $90, and the bridge would cost $100. In the absence of stimulus effects, therefore, the bridge would not pass a cost-benefit analysis. For simplicity's sake, suppose that spending money on the bridge would create exactly the same stimulus effect as doing a tax rebate - spend $100 on the bridge, and GDP goes up by $110 from the stimulus effect.

In this case, the net social benefit of spending $100 building the bridge is $90 + $110 - $100 = $100.
And the net social benefit of spending $100 on a tax rebate is $110 - $100 = $10.

Bridge wins!

In fact, it turns out that the bridge wins even with a pure multiplier of less than 1! As long as the multiplier is greater than 0.2, in fact, it's worth it for the government to build the bridge. This will mean that the apparent multiplier of bridge-building will far exceed the "pure" multiplier. In this case, the apparent multiplier from bridge-building will be 2.

This fits the results of Auerbach and Gorodnichenko (2012). It also fits with the simple Keynesian theories you'd read in an Econ 102 textbook. It also fits the results of Bachmann and Sims (2011). And if true, it means Chris House is completely wrong.

Now let's relax the assumption that the pure stimulus effect is equal for the two cases. Suppose that government spending creates waste, for example. Or suppose that due to the particular nature of the mechanism that makes stimulus effective in the first place, the people who build the bridge will tend to stick most of their fee in a bank instead, rather than spending it as people would do if they got a tax rebate. Concretely, suppose that due to government waste or reduced stimulus effect, the pure stimulus benefit of building the bridge is only $30 instead of $110 (a pure multiplier of only 0.3 for government spending vs. 1.1 for tax rebates).

In that case, the net social benefit of building the bridge is $90 + $30 - $100 = $20. Bridge still wins! House is still wrong!

The difference between bridge-building and tax rebates can be stated in simple terms. If you give people a tax rebate, they may stick the whole thing in the bank, completely negating the stimulus. If you pay unemployed people to build a bridge, they may stick 100% of their earnings in the bank - but now you have a new bridge.

So basically, I don't see how House is doing his cost-benefit analysis. His conclusion is diametrically opposed to Econ 102 textbook Keynesianism, which is fine, but I feel like there should be some justification. Almost everyone - even John Taylor! - thinks that infrastructure spending makes better stimulus than tax rebates, not worse. Chris House asserts that the exact opposite is true, and that's fishy.