Tuesday, June 30, 2015

What if Uber goes unter?

Recently, a California court ruled that Uber has to treat its drivers as employees, with all the regulatory costs that entails. Most people think that this will hamper Uber a bit but not kill it. But a few, like Megan McArdle, think that the ruling spells Uber's demise. What if McArdle is right? What do we conclude?

First of all, it's important to point out that Uber might die for reasons totally unrelated to the California decision. Companies die all the time for reasons totally unrelated to regulation. Recent financial statements show Uber taking a pretty big loss at some point in the recent past, which might mean that competition has been a lot stiffer than expected. So if Uber dies, disentangling causality will be very difficult.

But IF the California ruling, and others like it, are what put a stake through Uber's heart, then I think we conclude two things:

1. Uber wasn't actually that amazing of an idea.

2. Our labor regulation is too stringent.

Why do we conclude #1? Because there are lots of ideas that absorb the cost of labor regulations and manage to keep on turning a profit. Wal-Mart does it. McDonald's does it. If you can't even clear that hurdle, your idea wasn't really creating that much value.

Why do we conclude #2? Because Uber is providing lots of people with work. Many people who would not otherwise be driving taxis are now becoming Uber drivers. That they are choosing to do this means that Uber is good for labor markets. In the interests of improving our labor markets, we should reduce regulations that keep people from doing jobs they'd be willing to do, as long as those jobs are safe and meet other minimum standards of quality (such as paying overtime). Assuming that Uber driving is a safe job that meets minimum standards of quality - which I'm willing to assume - we don't want to regulate the job out of existence. 

I suspect that neither (1) nor (2) is true. I suspect that Uber actually creates more than a tiny sliver of value, with its network effect and its circumvention of the local monopoly of taxicabs. And I also suspect that American labor regulations are not so onerous that they are putting large numbers of people out of a job.

Thus, I predict that the California ruling will not kill Uber. Uber may still die of other causes, but I don't think that being forced to call its employees "employees" will do it in.

Saturday, June 27, 2015

I.Q. and the Wealth of States

One of the simplest theories of human prosperity is the idea that societal wealth comes from an intelligent populace. Obviously this is true to some degree; if you went around and forced everyone in the country to take a bunch of brain-killing drugs, economic activity would definitely decline. The question is how much this currently matters on the margin.

Some people think it matters a lot. Richard Lynn, a British psychologist, wrote a book called I.Q. and the Wealth of Nations, suggesting that average population I.Q. drives differences in national wealth. Garett Jones of George Mason University is writing a book called Hive Mind that suggests much the same thing, asserting that there are production externalities associated with high I.Q. Motivated by this hypothesis, there is a line of research in development economics dedicated to finding interventions that boost population I.Q.

Well, here is some new and relevant evidence. Eric A. Hanushek, Jens Ruhose, and Ludger Woessmann have a new NBER working paper in which they look at U.S. states. From the abstract:
In a complement to international studies of income differences, we investigate the extent to which quality-adjusted measures of human capital can explain within-country income differences. We develop detailed measures of state human capital based on school attainment from census micro data and on cognitive skills from state- and country-of-origin achievement tests. Partitioning current state workforces into state locals, interstate migrants, and immigrants, we adjust achievement scores for selective migration...We find that differences in human capital account for 20-35 percent of the current variation in per-capita GDP among states, with roughly even contributions by school attainment and cognitive skills. Similar results emerge from growth accounting analyses.
Note that the authors control for selective immigration, an oft-neglected factor in debates about I.Q.

So the upper bound for the amount of state income differences that can be explained by population I.Q. differences is about a third. If we assume that achievement scores are a good measure of I.Q. and that school attainment doesn't improve I.Q. very much, then the number goes down to about one-sixth.

Now, it's important to remember that this study, well-executed though it is, doesn't isolate causation. It doesn't show the degree to which state average I.Q. can be raised by raising state income.

What it shows is that the vast majority of differences in state income are not due to variations in state average I.Q. If we had an I.Q.-boosting device, boosting the average I.Q. of Ohioans by 1% would raise Ohio's average income by at most around around 0.17%.

Of course, that's a marginal effect. If we boosted the average I.Q. of Ohioans by 400%, we might see much more (or much less) than a 68% increase in their income. And if we gave Ohioans brain-killing drugs (insert Ohio State football joke here) that cut their I.Q. in half, we might see much more (or much less) than an 8.5% decrease in state income.

But anyway, what this really shows is that there is Something Else that is driving state income differences. My personal guess is that this Something Else is mainly "external multipliers" from trade (the Krugman/Fujita theory). Institutions probably play a substantial role as well (the Acemoglu/Robinson theory). That's certainly relevant for the debate about different models of capitalism, where we often compare the U.S. to Scandinavia and other rich places.

In any case, this result should be sobering for proponents of I.Q. as the Grand Unified Theory of economic development. Average I.Q. is not unimportant for rich countries, and we should definitely try to raise it through better nutrition, education, and (eventually) brain-boosting technologies. And it still might matter a lot for some poor countries. But for rich countries, there are things that matter a lot more.

Sunday, June 14, 2015

Deirdre McCloskey Says Things

Some sadistic person or another referred me to this 51-page Deirdre McCloskey review of Thomas Piketty's book. I must remember to find who that person is and either play a mean prank on them in return, or demand that they buy me an expensive lunch. Fair is fair.

Deirdre McCloskey is the kind of writer who can take a perfectly fine sentence like "Capitalism has made humanity rich," and mutate it into a horror show like this:
Since those founding geniuses of Classical economics, a trade-tested betterment (a locution to be preferred to “capitalism,” with its erroneous implication that capital accumulation, not innovation, is what made us better off) has enormously enriched large parts of a humanity now seven times larger in population than in 1800, and bids fair in the next fifty years or so to enrich everyone on the planet.
I don't know about you, but I bid fair to give up well before page 51 of that locution.

But my main problem with Ms. McCloskey is not the poorly executed flowery baroque writing style, or even the reminder that plenty of people mistake flowery baroque writing for good writing. It's that McCloskey frequently makes declarations that are, to put it politely, in contradiction of the facts. She says these things with utmost confidence but without evidence or support, making it clear that the fact that she has said them is evidence enough. She argues from authority, and the authority is always herself.

This is NOT a post about Piketty or his arguments (of which I already have more than enough reason to be skeptical). It is NOT a post about McCloskey's rebuttal to those arguments. This is a post about McCloskey's style of argumentation.

Reading and critiquing McCloskey's thoughts on Piketty would be a bad move for me. First of all, it would require me to read dozens more pages of McCloskey than I have already read. Second, it would require me to know more about Piketty than I do (I haven't read Capital, nor do I own it). Third, it would turn the discussion political, which would detract from the main point of this post, which is that McCloskey is prone to silly-talk. Fourth, it would get very very very long, and you would get very very very bored.

So instead, I will simply critique the first three pages of the review, which are an introduction to the rest of the piece. McCloskey uses this introduction to praise Piketty, to compare him to physicists, and to insult most of the economics profession.

Here are nine excerpts that made my head explode:

1. p. 2:
[E]conomic history is one of the few scientifically quantitative branches of economics. In economic history, as in experimental economics and a few other fields, the economists confront the evidence (as they do not for example in most macroeconomics or industrial organization or international trade theory nowadays). 
And with a wave of her pen, Deirdre McCloskey dismisses the entire existence of the vast fields of empirical industrial organization, trade empirics, and empirical macro. Such is the power of argumentum ad verecundiam sui.

So I guess it was useless for Liran Einav, a Stanford economist who studies empirical IO, to write this in 2010:
The field of industrial organization has made dramatic advances over the last few decades in developing empirical methods for analyzing imperfect competition and the organization of markets. These new methods have diffused widely: into merger reviews and antitrust litigation, regulatory decision making, price setting by retailers, the design of auctions and marketplaces, and into neighboring fields in economics, marketing, and engineering. Increasing access to firm-level data and in some cases the ability to cooperate with governments in experimental research designs is offering new settings and opportunities to apply these ideas in empirical work.
After all, what does Einav know of his field? Deirdre McCloskey has said that Einav's field does not look at the evidence, and thus it is Truth.

Also, the Gravity Model of trade, often praised (by lesser lights, naturally) as one of the most empirically successful theories of all time, must now sadly be consigned to the graveyard, since Deirdre McCloskey has declared that trade theory fails to confront the evidence.

2. p. 2:
When you think about it, all evidence must be in the past, and some of the most interesting and scientifically relevant is in the more or less remote past... 
[Piketty] does not get entangled as so many economists do in the sole empirical tool they are taught, namely, regression analysis on someone else’s “data” (one of the problems is the very word data, meaning “things given”: scientists should deal in capta, “things seized”). 
Let's forgive the flamboyant vacuousness of the statement "When you think about it, all evidence must be in the past". Let's briefly mention the fact that that trivially true statement in no way implies the second part of the sentence. And let's move on to the fact that the two halves of the above quote are diametrically opposed to each other.

If scientists should seize "capta" instead of receiving "data", doesn't this make economic history unscientific? I mean, you can't do any experiments on history, can you? Are there any historical capta? McCloskey is barely finished praising her own field for looking at evidence when she scorns other fields for looking at very similar kinds of evidence!

3. p. 2-3:
Piketty constructs or uses statistics of aggregate capital and of inequality and then plots them out for inspection, which is what physicists, for example, also do in dealing with their experiments and observations. 
Physicists make graphs of things! Piketty makes graphs of things! Piketty is just like a physicist!

I wonder what else physicists do in dealing with their experiments and observations. Use computer software programs to display the statistics? Print out their plots on paper sheets for inspection? Sip coffee and check Twitter? I could be like a physicist too! Except I hate coffee, dammit.

4. p. 3:
Nor does [Piketty] commit the other sin, which is to waste scientific time on existence theorems. Physicists, again, don’t. If we economists are going to persist in physics envy let’s at least learn what physicists actually do. 
Wow, I'm glad that I have Deirdre McCloskey to tell me what physicists actually do. I'd hate to rely on an unreliable source like Google Scholar, who sneakily tries to convince me that physicists write papers with titles such as:

"Existence theorem for solitary waves on lattices"

"Vortex condensation in the Chern-Simons Higgs model: an existence theorem"

"General non-existence theorem for phase transitions in one-dimensional systems with short range interactions, and physical examples of such transitions"

"Existence theorem for solutions of Witten's equation and nonnegativity of total mass"

"A global existence theorem for the general coagulation–fragmentation equation with unbounded kernels"

"A Sharp Existence Theorem for Vortices in the Theory of Branes"

etc. etc. etc....

Thanks to Deirdre McCloskey's expansive sentence structure and snappish wit, I can safely assume that the 699,000 results for my Google Scholar search for "physics existence theorem" do not, in fact, exist (while the 417,000 results I get for "economics existence theorem" must be regarded as real). In addition, I can get a partial tuition reimbursement for the portion of my college physics education I spent watching professors prove existence theorems on the board.

5. p. 2:
[Piketty] does not commit one of the two sins of modern economics, the use of meaningless “tests” of statistical significance[.]
Is McCloskey unaware of the fact that physicists regularly use statistical significance testing, of the classic R.A. Fisher type?

6. p. 3:
Piketty stays close to the facts, and does not, say, wander into the pointless worlds of non-cooperative game theory, long demolished by experimental economics. 
Oh, right. Noncooperative game theory was demolished. Apparently Google and a bunch of other tech companies failed to get the memo when they hired auction theorists to design their online auctions for them.

Or perhaps by "demolished," McCloskey means "embraced by mathematicians, computer scientists, and engineers."


7. p. 3:
True, the book is probably doomed to be one of those more purchased than read...younger readers will remember Stephen Hawking’s A Brief History of Time (1988).
Deirdre McCloskey realizes that A Brief History of Time is only 212 pages long and has a lot of pictures, right?

It's always good to remember that just because you talk about books without having read them doesn't mean that everyone else does the same.

8. p. 4:
To be fair to Piketty, a buyer of the hardback rather than the Kindle edition is probably a more serious reader, and would go further.
This comes immediately after McCloskey claims that people buy books in order to display them on their coffee tables - something that you can't do with a Kindle version. Yet McCloskey now claims that hardback readers are more likely to be serious readers - utterly without evidence, of course.

9. p. 4:
I shall say some hard things, because they are true and important
This pretty much sums it up, folks.

So let me recap: All of these quotes came from the first three pages of a review that is 51 pages long. In three short pages, McCloskey manages to unfairly malign almost every branch of economics, make mutually contradictory assertions about how economists should use evidence, make false statements about physics that could have been corrected with a 5-second Google search, randomly insult a good popular physics book, and randomly insult Kindle readers, all in a mass of tangled, overwrought prose.

Yeah, there's no way I'm going to read 48 more pages of that. In fact, I'm not sure why I clicked on this link at all, given that everything else I've read of McCloskey's has been in the same vein (here's another example). Fool me twice, shame on me. Fool me five or six times, and I need a better hobby.

As a side note, John Cochrane agrees with my critique of the first 3 pages of McCloskey, and (more politely) notes several of the same errors. Yay!! He notes that McCloskey has written a writing guide, and failed to follow her own advice. (He also says that the review gets much better when it gets to the actual Piketty-related substance. So I suppose I'll put pages 4 through 51 on my "to read" list...possibly far down on the list...)

There is a clear lesson in all this: Do not believe things that Deirdre McCloskey says just because she says them. Google them. Find the facts. Do not nod your head in mute, placid agreement. Do not be seduced by the turgid prose style into thinking that here is an Authority.

Store of value

Two interesting posts about bitcoin by JP Koning (post 1, post 2) got me thinking about the function of money. Usually we say that money serves three functions: unit of account, medium of exchange, and store of value. But what does it mean to be a "store of value"? More specifically, what does it mean for a form of money to be a "good store of value," i.e., performing this function well?

Suppose, for simplicity's sake, that an asset's value (defined in consumption terms) follows a geometric Brownian motion with constant percentage volatility and drift. So it satisfies:

 dS_t = \mu S_t\,dt + \sigma S_t\,dW_t

Does "good store of value" mean that sigma, the volatility, is low? Or does it mean that mu, the drift, is high? Remember that in the short term, volatility dominates drift, while in the long term, drift dominates. Also remember that there should be a tradeoff between these two - assets with higher volatility will tend to have higher systematic risk, and thus will tend to have higher expected returns (drift). In other words, in general an asset can be either a good long-term store of value, or a good short-term store of value, but not both.

Stocks are a good example of an asset with high positive drift and high volatility. Their value bounces around a lot, but it tends to increase over time. If "store of value" means "value tends to rise over time", then stocks would be a very good candidate. Stocks are a good long-term store of value.

Fiat money with a 2%-inflation-targeting central bank is a good example of an asset with negative drift and low volatility. Over time, you can expect this currency to lose value, since there will tend to be about 2% inflation every year. But the value is highly predictable - it doesn't fluctuate very much at all from day to day. Fiat-money-with-2%-inflation-targeting is a good short-term store of value.

Looking out at the world, I see a whole lot of countries that use fiat money, with something like inflation targeting, as their medium of exchange (i.e., what they use to pay for stuff). And I see zero who use stocks as the medium of exchange, even though the technology now exists for us to make payments in stock shares quite easily (it's just the same as exchanging dollars electronically, really).

So I conclude that we want the medium of exchange - i.e., money - to be a good short-term store of value (i.e., to have low volatility), and that we don't need it to be a good long-term store of value (i.e., we don't care about its expected return).

Why is this the case?

It makes sense if you think about the way that we use money. People don't know exactly when they are going to need to spend money, or how much. If they keep their wealth in assets with high expected returns and high volatility - stocks, etc. - they run the risk of having to sell in a down market in order to pay for unexpected expenses. So it makes sense to keep some of their wealth in a low-volatility, low-expected-return asset like fiat-money-with-2%-inflation-targeting, in the expectation that they'll probably have to use it to pay for something. The low expected return - the fact that cash falls in value a little bit every year - doesn't matter so much, because you don't keep the cash around that long before you spend it.

(Note that this ignores correlations, but those won't end up mattering here.)

So this is why money should be a short-term store of value rather than a long-term store of value. This is why, as David Andolfatto pointed out, gold makes such a lousy form of money.

How about bitcoin? If it keeps experiencing high volatility, then it's not going to become the medium of exchange in the U.S. or other countries with inflation targets. But if volatility falls in consumption terms - in other words, if the bitcoin prices of goods and services become very stable - then bitcoin will have a good chance of becoming the medium of exchange.

One problem, though, is that there's a bit of a chicken-and-egg situation here. The more merchants use bitcoin, the less volatile its consumption value will probably be. But in order for merchants to use it, customers have to use it, and they'll only start using it if there's low volatility.

But if bitcoin eventually manages to solve this chicken-and-egg problem, its promoters hope that it will be able to offer about the same volatility as fiat money but with a higher expected return. That would make bitcoin dominate fiat money, and would kick fiat money right out of the universe of investible assets - or, more realistically, it would force central banks to adopt an inflation target lower than the rate at which bitcoin is mined. That, I think, is the hope of bitcoin enthusiasts who say that bitcoin will "compete with central banks."

So for bitcoin to become money, it has to figure out how to massively reduce the volatility of bitcoin prices of goods and services.


Eli Dourado has a good response. I think we agree on the volatility thing. I glossed over other kinds of transaction costs, which Koning addresses somewhat; on those matters, I'm pretty ignorant, so I will let Eli and JP work it out...

Tyler Cowen thinks Bitcoin's volatility is a bad sign for its chances of future adoption, because it reflects a consensus that Bitcoin will never really catch on. I disagree with Tyler. Suppose, for simplicity's sake, that milk was the only good that people consumed. And suppose that in the future, bitcoin becomes the universal medium of exchange, and that at that time the bitcoin price of milk is about the same as it is today. In this case, there is no benefit to buying a lot of bitcoin today, even if you know for certain that it's going to become universally adopted. Because the price of bitcoin is already "right", in consumption terms. Hoarding a bunch of bitcoin right now doesn't actually improve your tradeoff between future milk and present milk. So the lack of bitcoin speculation doesn't necessarily mean that people have decided that bitcoin is doomed. It could even mean the exact opposite.

Thursday, June 11, 2015

A paradigm shift in empirical economics?

Empirical economics is a more and more important part of economics, having taken over the majority of top-journal publishing from theory papers. But there are different flavors of empirical econ. There are good old reduced-form, "reg y x" correlation studies. There are structural vector autoregressions. There are lab experiments. There are structural estimation papers, which estimate the parameters of more complex models that they assume/hope describe the deep structure of the economy.

Then there are natural experiments. These papers try to find some variation in economic variables that is "natural", i.e. exogenous, and look at the effect this variation has on other variables that we're interested in. For example, suppose you wanted to know the benefits of food stamps. This would be hard to identify with a simple correlation, because all kinds of things might affect whether people actually get (or choose to take) food stamps in the first place. But then suppose you found a policy that awarded food stamps to anyone under 6 feet in height, and denied them to anyone over 6 feet. That distinction is pretty arbitrary, at least in the neighborhood of the 6-foot cutoff. So you could compare people who are just over 6 feet with people who are just under, and see whether the latter do better than the former. 

That's called a "regression discontinuity design," and it's one kind of natural experiment, or "quasi-experimental design." It's not as controlled as a lab experiment or field experiment (there could be other policies that also have a cutoff of 6 feet!), but it's much more controlled than anything else, and it's more ecologically valid than a lab experiment and cheaper and more ethically uncomplicated than a field experiment. There are two other methods typically called "quasi-experimental" - these are instrumental variables and difference-in-differences.

Recently, Joshua Angrist and Jorn-Steffen Pischke wrote a book called Mostly Harmless Econometrics in which they trumpet the rise of these methods. That follows a 2010 paper called "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics." In their preface, the authors write:
[T]here is no arguing with the fact that experimental and quasi-experimental research designs are increasingly at the heart of the most influential empirical studies in applied economics. 
This has drawn some fire from fans of structural econometrics, who don't like the implication that their own methods are not "harmless". In fact, Angrist and Pischke's preface makes it clear that they do think that "[s]ome of the more exotic [econometric methods] are needlessly complex and may even be harmful." 

But when they say their methods are becoming dominant, Angrist and Pischke have the facts right.Two new survey papers demonstrate this. First, there is "The Empirical Economist's Toolkit: From Models to Methods", by Matthew Panhans and John Singleton, which deals with applied microeconomics. Panhans and Singleton write:
While historians of economics have noted the transition toward empirical work in economics since the 1970s, less understood is the shift toward "quasi-experimental" methods in applied microeconomics. Angrist and Pischke (2010) trumpet the wide application of these methods as a "credibility revolution" in econometrics that has finally provided persuasive answers to a diverse set of questions. Particularly influential in the applied areas of labor, education, public, and health economics, the methods shape the knowledge produced by economists and the expertise they possess. First documenting their growth bibliometrically, this paper aims to illuminate the origins, content, and contexts of quasi-experimental research designs[.]
Here are two of the various graphs they show:

The second recent survey paper is "Natural Experiments in Macroeconomics", by Nicola Fuchs-Schuendeln and Tarek Alexander Hassan, It demonstrates how natural experiments can be used in macro. As you might expect, it's a lot harder to find good natural experiments in macro than in micro, but even there, the technique appears to be making some inroads.

So what does all this mean?

Mainly, I see it as part of the larger trend away from theory and toward empirics in the econ field as a whole. Structural econometrics takes theory very seriously; quasi-experimental econometrics often does not. Angrist and Pischke write:
A principle that guides our discussion is that the [quasi-experimental] estimators in common use almost always have a simple interpretation that is not heavily model-dependent.
It's possible to view structural econometrics as sort of a halfway house between the old, theory-based economics and the new, evidence-based economics. The new paradigm focuses on establishing whether A causes B, without worrying too much about why. (Of course, you can use quasi-experimental methods to test structural models, at least locally - most econ models involve a set of first-order conditions or other equations that can be linearized or otherwise approximated. But you don't have to do that.) Quasi-experimental methods don't get rid of theory; what they do is to let you identify real phenomena without necessarily knowing why they happen, and then go looking for theories to explain them, if such theories don't already exist.

I see this as potentially being a very important shift. The rise of quasi-experimental methods shows that the ground has fundamentally shifted in economics - so much that the whole notion of what "economics" means is undergoing a dramatic change. In the mid-20th century, economics changed from a literary to a mathematical discipline. Now it might be changing from a deductive, philosophical field to an inductive, scientific field. The intricacies of how we imagine the world must work are taking a backseat to the evidence about what is actually happening in the world.

The driver is information technology. This does for econ something similar to what the laboratory did for chemistry - it provides an endless source of data, and it allows (some) controls. 

Now, no paradigm gets things completely right, and no set of methods is always and universally the best. In a paper called "Tantalus on the Road to Asymptopia," reknowned skeptic (skepticonomist?) Ed Leamer cautions against careless, lazy application of quasi-experimental methods. And there are some things that quasi-experimental methods just can't do, such as evaluating counterfactuals far away from current conditions. The bolder the predictions you want to make, the more you need a theory of how the world actually works. (To make an analogy, it's useful to catalogue chemical reactions, but it's more generally useful to have a periodic table, a theory of ionic and covalent bonds, etc.)

But just because you want a good structural theory doesn't mean you can always produce one. In the mid-80s, Ed Prescott declared that theory was "ahead" of measurement. With the "credibility revolution" of quasi-experimental methods, measurement appears to have retaken the lead.

Update: I posted some follow-up thoughts on Twitter. Obviously there is a typo in the first tweet; "quasi-empirical" should have been "quasi-experimental".

Friday, June 05, 2015

Economic arguments as stalking horses

On Twitter, Russ Roberts said something I tend to agree with:
Just a curious coincidence that economists who like stimulus want bigger government and those who oppose it prefer smaller. 
In fact, he said something very similar back in 2011:
The evidence for the Keynesian worldview is very mixed. Most economists come down in favor or against it because of their prior ideological beliefs. Krugman is a Keynesian because he wants bigger government. I’m an anti-Keynesian because I want smaller government. Both of us can find evidence for our worldviews[.]
Now, Roberts doesn't actually know Krugman's motives - he's necessarily making a guess. But he definitely does know his own! Basically, he's saying that he adopts an anti-Keynesian stance not because be thinks stimulus actually fails to fight recessions, but because he wants to shrink the size of the government in the long term. 

Furthermore, he strongly implies that he will selectively display evidence against the effectiveness of stimulus as a stabilizer, in order to ward off the long-term expansion of government. That's motivated reasoning.

I have long believed that stuff like this happens in economics arguments all the time. It's probably not (usually) an intentional subterfuge, but more of an unconscious bias. An economist is presented with the proposition that countercyclical fiscal policy (stimulus in recessions, austerity in booms) increases overall efficiency. He is generally against increasing the size of the government. So when he sees that countercyclical fiscal policy will (temporarily) increase the size of the government in a boom, it triggers warning sirens in his subconscious. "What? Increase the size of government? Never!", says his subconscious. And so that motivates him to argue against the proposition that countercyclical policy is effective at stabilizing booms and recessions. 

So Russ Roberts is being honest and introspective, which is good. Introspection is difficult and often unflattering, so not enough people engage in it.

In fact, this is similar to the first part of Paul Romer's "mathiness" argument. Romer argues that some economists make their modeling choices for reasons related to academic politics - for example, he says that researchers who want to believe in a world without market power will construct growth theories that make silly assumptions just to avoid putting market power in the equation. 

This effect is a lot stronger if there's no skin in the game. As Matt Yglesias pointed out back in 2011, you see Republican politicians - who probably want to shrink the government - doing Keynesian policies fairly often. Bush enacted stimulus in 2008, and probably Reagan in the early 80s. 

Another example would be the fact that nearly everyone on Wall Street was eager to tell you back in 2012 that QE would cause a big rise in inflation. But when you looked at TIPS spreads, it was clear that the marginal investor wasn't putting his money where his mouth was.

This is consistent with the finding that partisan belief gaps go away when you pay people to get things right. A bet really is a tax on bullshit (although not the optimal tax). Or, as Nassim Taleb so memorably put it, macrobullshitting is reduced by having skin in the game. The cynical side of me says that Romer's "mathiness" manifests mainly in fields where the data is not good enough to exert discipline on theory.

So when you read econ arguments, always be a little wary of the motivations of the arguers.

P.S. - This is unrelated to the main point of my blog post, but an alternative, non-Keynesian theory of stimulus is that it boosts output because it expands the government, in the ways that need expanding (public investment).


Paul Krugman responds to Russ Roberts.

Adam Ozimek responds to Roberts, defending Paul Krugman, and the econ profession, from Roberts' cynical allegations. The two have an interesting (but brief) twitter debate about how evidence should interact with ideology.

Roberts writes an additional tweet that I like:
Conceding the reality of self-deception isn't cynical. It's realistic. Leads to humility and caution.
I agree, but just because some nonzero degree of self-deception is inevitable doesn't mean it's benign. Instead of just accepting it, I say people should try to fight against it. And if you realize that you yourself engage in a considerable degree of self-deception, I say you should focus on reducing it, rather than focusing on demonstrating that your rhetorical opponents are equally self-deceptive.

Tuesday, June 02, 2015

Fun with formality

The Paul Romer "mathiness" debate isn't about mathematical formalism in econ. Romer says:
T/F: Romer thinks that economists should not try to use the mathematics of Debreu/Bourbaki and should instead use math in the less formal way that physicists and engineers use it... 
[H]and-waving and verbal evasion...is the exact opposite of the precision in reasoning and communication exemplified by Debreu/Bourbaki, and I’m for precision and clarity.
But that comment got me thinking about formalism in econ math, and I thought I'd share some thoughts.

I've never actually read any Bourbaki papers, but Bourbaki was a club of mostly French mathematicians who got together in the 1930s and insisted that mathematicians be very formal. They got their wish, and the result is the rigorous, formalistic style of modern math papers. But physicists and engineers never followed this convention, preferring to derive essential results and let mathematicians pick up after them by putting in the formality.

There are economists who follow both conventions. You see some papers that use a very formal, terse, axiom-theorem-proof style similar to what you'd see in a mathematics journal. And you see some papers that use a more informal, "here's an equation that I think describes something" methodology that you might see in an engineering journal. 

An example of the formal style would be "The Simple Theory of Temptation and Self-Control," by Farak Gul and Wolfgang Pesendorfer. This paper introduces a wrinkle to the standard classical theory of intertemporal consumer decision-making - they allow people to have preferences over the sets of choices they are given, such as when people on a diet might not want to see the dessert menu. This wrinkle is inserted in the form of a new "axiom", called the Axiom of Set Betweenness. The presentation in the paper tends to look like this:

An example of the informal style would be "Golden Eggs and Hyperbolic Discounting," by David Laibson. This paper also introduces a wrinkle to the classical theory of intertemporal consumer decision-making. The wrinkle is a new functional form for the consumer's discount function. The presentation in the paper tends to look like this:

In fact, both of these papers are motivated by some of the same empirical phenomena. But they go about it in very different ways. Gul and Pesendorfer introduce an entirely new framework, while Laibson tweaks a functional form. In other words, Gul and Pesendorfer rewrite all of the rules for how decision-making is thought to operate, while Laibson sticks in something that works. As a result, it's natural for Gul and Pesendorfer to use a very formal framework, since formal things are more general and can build a foundation for many other theorists to work with. Laibson doesn't have any need to be so formal.

I imagine that some people complain about the formalism in Gul and Pesendorfer because it's hard for them to read. But after you learn to speak that language, it's actually easy to read - in many ways, easier than English. Formal math language forces you to read like a computer, which means you don't miss anything, while English tempts you (heh) to gloss over important parts as you scan through paragraphs.

In general, I think formal math style is no worse or better than informal engineering style. It's just a matter of personal preference.

Another thing that might annoy people about Gul and Pesendorfer's formalism is the clunkiness of doing economics this way. Do we really want to have to re-axiomatize all of consumer decision-making every time we see people doing something weird? Isn't the overhead of formalism a big waste of time and effort?

Well, maybe. If we take the Laibson paper seriously, all we have to do is to introduce a hyperbolic discounting function whenever we suspect it might make a difference in a model. That's equivalent to just setting the parameters of the hyperbolic discounting function to approximate a classic, non-hyperbolic discount function whenever we don't think it's interesting. But if we take the Gul and Pesendorfer paper seriously, we might have to reformulate all our theories. It's just not clear when the Axiom of Set Betweenness might apply. An axiom is just a lot more general than a parametrization. It seems to me that that's what you can lose from formalism - a clear sense of when the new stuff might make a difference. 

But in the end, I bet that people use the Gul & Pesendorfer stuff in the exact same way they use the Laibson stuff - they apply it when they think it might make a difference, and forget about it at all other times. So formalism vs. informalism again just comes down to a matter of personal preference.

Monday, June 01, 2015

Feminist Mad Max is real, y'all

At the website Return of Kings, econ blogger Aaron Clarey reviles Mad Max: Fury Road as a trojan horse for feminist ideas:
This [movie] is the vehicle by which they are guaranteed to force a lecture on feminism down your throat. This is the Trojan Horse feminists and Hollywood leftists will use to (vainly) insist on the trope women are equal to men in all things, including physique, strength, and logic.
Clarey is talking about the fact that a number of the female characters in the movie - including Charlize Theron's female lead - are tough warrior types who spend a lot of time shooting and otherwise killing big tough male baddies. He thinks that's unrealistic - in the real world, he seems to be saying, war is a man's job.

But actually, I can think of at least one good real-life analogue of the badass women of Mad Max (and of much of modern pop culture). It's the war in Syria and Iraq. The Kurdish militias who have been beating the crap out of ISIS in the north of Syria have substantial numbers of women in their ranks. Here, via War Nerd, are pictures of a couple of the women killed in combat with ISIS:


Normally, women are kept in noncombatant roles in Kurdish militias. But the pressure of the ISIS assault forced women to join the fight directly, and they have apparently been quite effective in battles like the one in Kobane. In fact, a woman is the commander of the Kurdish militias in Syria:
Meet Nassrin Abdallah. With her diminutive height and broad smile, it doesn't seem like she should strike fear into the hearts of hardened Islamic State jihadists. But this 36-year-old Syrian Kurd woman has been at the tip of the spear of the Kurdish forces that last month liberated the symbolic city of Kobane from IS militants... 
As the head of the armed wing of the Kurdish PYD, "commander" Nassrin has led both men and women into battle against Islamic State fighters who have overrun large areas of Iraq and Syria... 
According to Nassrin, around 40 percent of the Kurdish fighters battling over the town on the Syrian-Turkish border were women.. 
Some, like her, are hardened warriors but also joining their ranks were mothers who sent their children over the border to the safety of Turkey, then rushed off to join their sisters in arms...Fighting alongside Nassrin are other powerful female commanders who have achieved legendary status on the battlefield. 
Women like Narine Afrin, who played a key role in the defence of Kobane. Or Arin Mirkan, who blew herself up on October 5, killing dozens of IS fighters encircling the town, according to Kurdish sources. 
In total, there are 4,000 women fighting in the armed wing of the PYD [militia], say Kurdish officials, who refuse for strategic reasons to disclose the total number of people who have taken up arms. 
Over and beyond the military aspect of the victory over IS in Kobane, it has been seen as a triumph for women, who are repressed in areas under IS control, obliged to wear the veil and, in the case of the Yazidi minority, forced into slavery.
In fact, this pretty closely parallels the plot of Mad Max: Fury Road! Nassrin Abdallah is the real-life Imperator Furiosa, while ISIS is the real-life version of Immortan Joe and the Warboys.

And it's important to note that the women of the Kurdish militias haven't just been fighting, they've been winning. ISIS massively outnumbered and outgunned the Kurdish militias in a number of battles in northern Syria, but were soundly defeated.

So if men's natural physical advantages are not decisive (at least in the age of guns and explosives), why have most armies throughout history been mostly or exclusively male?

One reason is that men can't bear children. Over time, a warlike society's success depends on the number of soldiers it can throw at the enemy. If a male soldier gets killed, the loss of his sperm will not adversely impact the overall fertility of the tribe. But if a female soldier gets killed, the fertility of the tribe will go down, reducing the number of future soldiers. You really need to think of things in terms of expected discounted total soldiers. The math of protracted warfare favors sending men to die on the front lines, and keeping women in the rear to pump out new soldiers. (Yes, it sucks to live in a warlike society.)

Another reason is preference. Men, on average, are far more violent and aggressive than women. This means that more men will want to go to war, or at least hate it less.

So Aaron Clarey is wrong. Mad Max: Fury Road is not a piece of unrealistic feminist propaganda (though the Tumblr site Feminist Max Max is funny). What it actually is is a movie about - to use a Clarey phrase - "one man with principles, standing against many with none."

Saturday, May 16, 2015

Paul Romer on mathiness

Top growth theorist Paul Romer has an essay in the AER Papers & Proceedings, in which he comes down harshly "mathiness" in growth theory. "Mathiness" is his term for when people (allegedly) use math in a sloppy way, to support their preferred theories. Romer warns direly that the culture of econ theory has become a lot more tolerant of mathiness:
If mathiness were used infrequently,...it would do localized, temporary damage. Unfortunately...as the quantity increases, mathiness could do permanent damage because it takes costly effort to distinguish mathiness from mathematical theory. 
The market for mathematical theory can survive a few...articles filled with mathiness. Readers will put a small discount on any article with mathematical symbols, but will still find it worth their while to work through and verify that the formal arguments are correct, that the connection between the symbols and the words is tight, and that the theoretical concepts have implications for measurement and observation. But after readers have been disappointed too often by mathiness that wastes their time, they will stop taking seriously any paper that contains mathematical symbols. In response, authors will stop doing the hard work that it takes to supply real mathematical theory. If no one is putting in the work to distinguish between mathiness and mathematical theory, why not cut a few corners and take advantage of the slippage that mathiness allows? The market for mathematical theory will collapse. Only mathiness will be left. It will be worth little, but cheap to produce, so it might survive as entertainment. 
[I]n the new equilibrium: empirical work is science; theory is entertainment. Presenting a model is like doing a card trick. Everybody knows that there will be some sleight of hand. There is no intent to deceive because no one takes it seriously. Perhaps our norms will soon be like those in professional magic; it will be impolite, perhaps even an ethical breach, to reveal how someone’s trick works. 
When I learned mathematical economics, a different equilibrium prevailed. Not universally, but much more so than today, when economic theorists used math to explore abstractions, it was a point of pride to do so with clarity, precision, and rigor...If we have already reached the lemons market equilibrium where only mathiness is on offer, future generations of economists will suffer.
Romer has now joined the chorus of old famous guys - Krugman, Solow, Stiglitz, Farmer - who are very vocally mad about the way mainstream economics theory is done.

Romer is not afraid to name names. Interestingly, although he's talking only about growth theory and not about business cycle theory, most of the people he's mad at are the same guys that the Keynesians are mad at - Robert Lucas, Ed Prescott, and David K. Levine. He also calls out Thomas Piketty.

Romer gives specific examples of what he calls mathiness (links are to working-paper versions):

1. Prescott and McGrattan (2010): Romer says that this paper includes a term that the authors label "location," but that doesn't correspond to any real measure of location.

2. Boldrin and Levine (2008): Romer criticizes this paper for assuming that a monopolist would also be a price-taker, and for making various hand-wavey arguments.

3. Lucas (2009): Romer criticizes this paper for making a hand-wavey argument to dismiss the idea that investment in embodied technology (books, blueprints, etc.) can be a source of sustained growth, when there are well-known models in which it can. Romer also points out a random math error in the paper, and uses this to argue that reviewers don't pay close attention to math.

4. Lucas and Moll (2014): Romer criticizes this paper especially harshly. Lucas and Moll claim that their model, in which there is no creation of new knowledge, is "observationally equivalent" to models in which new knowledge arrives very slowly. Romer shows that the truth of this claim depends on which order you use when taking a double limit. He reveals that he told the authors about the problem, but that they ignored him and left it in the paper.

5. Piketty and Zucman (2014): Romer points out the by now well-known "gross vs. net" problem in Piketty and Zucman's definition of savings.

All in all, this seems like a pretty loose collection of criticisms. Hand-wavey arguments, dubious definitions, bad assumptions, and math errors are all very different things. So this essay at first can seem like a grab-bag of gripes that Romer has with individual rivals' papers.

But I think Romer is on to something about the culture of econ theory, at least in the "macro"-ish realms of growth, business cycle, macro-labor, macro-trade, and macro-tax theory (I don't know nearly as much about the culture of the "micro"-ish fields like game theory, decision theory, I/O, etc.; and I know that finance theory has a very different culture). In these "macro"-ish fields, people seem to view math more as a tool for stylized description of ideas than as a tool for quantitative prediction of observables. 

Romer's examples of "mathiness" are all very recent examples. But going back to earlier models, I don't really see much more tight connection of variables to observables. Yes, in a Solow model you can tie capital K to observable things like structures and machines and vehicles. But you'll be left with a big residual, A. Then you can break A down and extract another term for human capital, H. Can you really measure human capital? Human capital can't be bought and sold on a market; you have to bundle it with other goods. So it's very difficult to get a clean measurement of the value of the existing stock of human capital, the way you could get a clean measurement of the existing stock of delivery trucks. Romer cites human capital as a good example of non-"mathiness", but I don't really see a huge difference between that and the "location" used by Prescott and McGrattan (2010). Maybe a minor difference, but not a huge one. As for the remaining A, there's not really any quantitative way to measure the stock of ideas except as a residual. And as for goofy assumptions, well, any growth model is going to have at least one or two assumptions that would make a newcomer to the econ field throw up her hands in disbelief.

Mathiness isn't anything new, it's just the way these econ fields work. The math is there as a storytelling aid (and possibly as a signal of intellectual ability). I think Karthik Athreya said it best:
My view is that a part of what we do is "organized storytelling, in which we use extremely systematic tools of data analysis and reasoning, sometimes along with more extra-economic means, to persuade others of the usefulness of our assumptions and, hence, of our conclusions...This is perhaps not how one might describe "hard sciences".
Do the guys Romer calls out play a little faster and looser with definitions and rely more on hand-wavey arguments? Oh, I'm sure they do - but that's because they're famous old guys. Writing down hand-wavey stuff is a privilege afforded to famous old guys in every academic discipline I know of. In econ, it gets politely published in top journals, but all the hotshot young people just sort of shake their heads anyway, and the only net effect is to pad out the length of the journals. Are the guys Romer calls out more political than the average economist? Maybe.

But in general, the whole discipline of macro theory - in the general sense, including growth and parts of labor, trade, and tax theory - is chock full of mathiness. Even most of the best models ("best" being a highly relative term, of course). The original Solow model seems to me like a rare exception, not a typical example of the Good Old Stuff.

But in any case, I highly recommend the Romer piece, which is a master class in catching errors in models, as well as a fascinating window into the Byzantine world of academic politics.

Update: Brad DeLong has a follow-up post explaining his view of some of the history behind the argument in the field of growth economics. Basically, the idea is that George Stigler didn't like people using models with imperfect competition, since this might open up a window for government intervention. DeLong thinks that Lucas and other "freshwater" types inherited this anti-imperfect-competition bias, causing them to be too down on Romer's models. This is interesting history that I didn't really know about before.

Update 2: Paul Romer has a response on his blog. Excerpts:
Noah Smith asks for more evidence that the theory in the McGrattan-Prescott paper that I cite is any worse than the theory I compare it to by Robert Solow and Gary Becker... 
There is no such thing as the perfect map. This does not mean that the incoherent scribbling of McGrattan and Prescott are on a par with the coherent, low-resolution Solow map that is so simple that all economists have memorized it. Nor with the Becker map that has become part of the everyday mental model of people inside and outside of economics... 
Noah’s jaded question–Is the theory of McGrattan-Prescott really any worse than the theory of Solow and Becker?–may be indicative of what many economists feel after years of being bullied by bad theory. And as I note in the paper, this resignation may be why empirically minded economists like Piketty and Zucman stay as far away from theory as possible... 
For specific purposes, some maps are better than others. Sometimes a subway map is better than a topographical map. Sometimes it is the other way around. Starting with any good map, we can always increase the resolution and add detail. 
No map is perfect, but this does not mean that all maps are equal. It certainly does not mean that an internally consistent map that with so little detail that you can memorize it is on a par with incoherent scribbling.
In the rest of the post, he goes into depth about why he thinks the McGrattan and Prescott paper constitutes "incoherent scribbling." But he also notes that the other papers he goes after in his "mathiness" piece should not be let off the hook:
Noah also notes that I go into more detail about the problems in the Lucas and Moll (2014) paper. Just to be clear, this is not because it is worse than the papers by McGrattan and Prescott or Boldrin and Levine. Honestly, I’d be hard pressed to say which is the worst. They all display the sloppy mixture of words and symbols that I’m calling mathiness. Each is awful in its own special way.
He also has another short post about a Lucas paper.

It appears that Prescott, Lucas, Levine, and others of the unofficial "freshwater" club have annoyed more high-level colleagues than just Paul Krugman. Only a few months ago, Roger Farmer took to his blog to unleash an anti-Prescott blast. Romer and Farmer are not politically-minded media-engaged types like Krugman and DeLong, but their aggravation with the Lucas/Prescott school is, if anything, even more intense.

And yes, Romer is right that I'm jaded. Is it so obvious? *takes swig from hip flask, rubs beard stubble*

Tuesday, May 12, 2015

Department of "Huh yourself!": British demand edition

Brad DeLong thinks I'm nutty when I say that Britain isn't obviously suffering from a persistent shortfall of aggregate demand:
Graph Gross Domestic Product by Expenditure in Constant Prices Total Gross Domestic Product for the United Kingdom© FRED St Louis Fed
There are no signs looking at wages and prices that this is due to any adverse supply shock...there seem to be no reasons looking at wages, prices, and output to believe that the British economy right now is a full-employment at-capacity-utilization economy. And only in such an economy would monetary and fiscal policies that boost spending simply boost prices and not production...
Graph Employment Rate Aged 15 64 All Persons for the United Kingdom© FRED St Louis Fed
Does the fact that the employment share of British adults is actually high mean that the British economy is, in fact, at potential output? That stimulative monetary and fiscal policies risk rising inflation for no gain? And that it is time to normalize? Certainly Mark Carney at the Bank of England does not believe that is so:
Graph Interest Rates Government Securities Treasury Bills for United Kingdom© FRED St Louis Fed
From my point of view, why so many Britons have taken so many low-pay low-productivity jobs in the past three years is a mystery. But that they have gives us little reason to think that the British economy is now a full-employment at-capacity-utilization economy in which aggregate demand is now equal to potential output.

First of all, let's get a couple things straight. I don't think British stimulus would be particularly counterproductive, I just don't think austerity would be either. If there's not a big demand gap, multipliers shouldn't be large, so stimulus just won't do a heck of a lot (unless the UK has falling-apart infrastructure like we do), but neither will austerity. Also I doubt AS-AD is even always the right model for the macroeconomy.

But with that said...

With a demand shortfall, we ought to see high unemployment. We also ought to see low inflation.

In the U.S. we saw both of these in 2009-2014. In Britain we saw the former in 2009-11, and we never really saw the latter at all. Here is British core inflation:

The Bank of England's inflation target is 2% (whether that's a ceiling or a target is not certain). But in 2010-2013 - four years!! - UK core inflation was above that target. 

So if we stick to the good old Econ 102 AS-AD model, and we look at both prices and quantities, we can come up with the following simple story for the UK:

1. In late 2008 the UK suffered a negative AD shock.

2. Around the same time, the UK suffered a negative AS shock.

3. In early 2010 the negative AD shock began to abate.

4. In 2012 the negative supply shock began to abate.

5. The differences between the UK and the U.S. in GDP, employment, and inflation can be explained by the fact that the UK's AD shock wasn't quite as big or long-lasting, while the U.S. didn't experience a supply shock.

This story also fits what we know about British TFP, which declined from 2007-2009, then flatlined through 2011:

This story is incredibly simplified, and uses a model that probably isn't the best. A real, careful, academic analysis of the situation is certainly warranted. But is there some obvious reason we need to go looking for a story where AD is the only thing moving around here? That story is going to have a lot more moving parts, and it's going to go a lot deeper into micro stuff. 

And it will also look like reaching. Why should we demand a story where demand is the whole story? Is this about stabilization policy, or about the size of the British state?

Economists as all-purpose sages: The case of Freakonomics

The original book Freakonomics, by Steve Levitt and Stephen Dubner, was a very fun read. But it also slightly annoyed me. Why? Because there's very little actual economics in it! The quantitative empirical work is mostly reduced-form regressions with natural experiments. That's a fine and good research technique, but it's not really special to econ - it doesn't include anything about market design, structural estimation of supply and demand, game theory, search, prices, general equilibrium...nada!

That covers three of the six chapters. The other three include 1) an ethnography of drug dealer culture by a sociologist, the excellent Sudhir Venkatesh, 2) a quick gloss of statistics techniques that applied mathematicians use to catch cheaters, and 3) a historical story about the decline of the KKK.

So this book has sociology, history, stats, and some general empirical techniques that could be used by any social scientist. That doesn't make it bad - most of the research the book showcases is really cool (though Levitt's own study, on abortion and crime, ended up having some serious problems). But it means that an empirical sociologist could easily taken Levitt's place as the technical co-author of the book, alongside journalist Dubner.

But it was an economist Dubner got, and Freakonomics was billed as a pop econ book, not a pop sociology book. Why? It seems to me that it's because economists are respected as all-purpose sages. Like I said in my previous post, economists get taken seriously on any topic imaginable.

To use an even more stark example, take the sequel, Superfreakonomics. There's a chapter in that book that's all about geoengineering. That's an engineering topic. A physics topic. A climate science topic. And yet an economist is put forth as an authority on whether it will work. And this is accepted by the book's legions of fans.

People trust economists on any topic.

Why? I don't know, to be honest. Maybe it's because economists are thought to have high IQ and know a lot of math relative to other social science disciplines. Maybe it's because economists are confident in their ability to model any social phenomenon, like Gary Becker and others of the "imperialist econ" school. Or maybe it's because economists are just more willing to engage with the public and hold forth on any topic. After all, op-ed writers are the other group who are treated as all-purpose experts; maybe economists just act like really hi-tech, super-smart op-ed writers.

Or maybe it's because of economists' reputation as being clear-eyed and impartial observers of society. For example, in the intro to Freakonomics, Dubner describes a scene with Steve Levitt:
An elderly homeless man approaches [Levitt's car]. It says he is homeless right on his sign, which also asks for money. He wears a torn jacket, too heavy for the warm day, and a grimy red baseball cap. 
[Levitt] doesn’t lock his doors or inch the car forward. Nor does he go scrounging for spare change. He just watches, as if through one-way glass. After a while, the homeless man moves along. 
“He had nice headphones,” says [Levitt], still watching in the rearview mirror. “Well, nicer than the ones I have. Otherwise, it doesn’t look like he has many assets.”
If you didn't know Levitt was an economist, this scene would just make him sound like a rich insensitive jerk. But the fact that he's an economist imbues the scene with a different meaning altogether - suddenly, Levitt's clinical detachment seems like a sign of impartiality and rationality. Exactly the qualities we'd want in an all-purpose sage.

Anyway, I don't know the answer. But the observation that people trust economists on any social topic - and even some engineering topics - seems pretty obvious. And pretty freaky.

P.S. - If you want a book that is nothing but hardcore economics, and explains everyday economic phenomena in a way that is humble, entertaining, and useful all at the same time, I recommend Tim Harford's The Undercover Economist. The best version is the audio version. 

Saturday, May 09, 2015

Economists don't have "physics envy"

I hear all the time that economists have "physics envy". This doesn't seem even remotely true. I'm not sure whether "physics envy" means that economists envy physicists, or that economists want to make physics-style theories, or that economists wish their theories worked as well as those of physicists. But none of these are true.

Reasons why economists don't have physics envy include:

1. Economists make a lot more money than physicists.

2. Economists are treated as experts on practically anything. An economist can talk about why hipsters have moustaches, and get taken seriously. An economist can talk about which restaurants are the best, and get taken seriously (Update: NO, I'm not saying Tyler's book is bad, I haven't even read it, so HUSH). An economist can talk about politics, marriage, popular music, sex, race, or sports and get taken as seriously as any expert in those fields. An economist can talk about how much progress physicists are likely to make, and get taken seriously. Physicists get taken seriously when they invent quantitative rules for things, but otherwise are treated as just one more tribe of crazy nerds with their heads in the aether.

3. Economic theorists, traditionally, have been free from the constraints of empirical validation. Econ didn't start out with any data to speak of, so it developed a culture where data wasn't the measure of a good theory. That culture has been slowly changing, as IT and statistics allow us to do much more empirics. The wild econ theorist is being slowly tamed, though they occasionally buck against their new constraints. But economics is still nowhere near as enslaved to empirics as physics is. Ed Witten, a brilliant physicist who invented superstring theory and won a Fields Medal, will probably never get a Nobel prize, since no one has yet figured out a way to test superstring theory. In econ, though, un-validated theories - even empirically unsuccessful theories - do sometimes get Nobel prizes, especially in macro.

4. Economists and physicists have totally different reasons for thinking their theories are beautiful. Physicists tend to appreciate the symmetry of their theories, or their connection to geometry. Economists tend to appreciate the fact that their theories can be derived from axioms of human behavior. Economists don't usually see themselves as a high-up floor on the tower of science that begins with math and progresses through physics to chem, then bio, then psych. They tend to see their own field as part of an entirely different tower, unsupported by the other sciences, built on the foundation of axioms - not empirical laws or derived properties - of human behavior.

(Note for physics/math people: what economists call "axioms" are what physicists call "postulates".)

5. Economics theories aren't really much like physics theories in the first place. In particular, the word "equilibrium" means totally different things in the two fields. In econ, the word "equilibrium" is incredibly general - it just means the solution of any system of equations in an economics model, really. A few economic equilibria are similar to equilibria in physics models, but not most. A lot of people outside econ don't seem to understand how economists use the word.

So economists don't have physics envy. But there is a related field that absolutely does have physics envy: Financial engineering.

Financial engineering doesn't use the axiomatic stuff econ uses - instead it fits curves, like applied math. Often, the math is very similar to that used by physicists, and this is why physicists often go into financial engineering. But financial engineering doesn't work nearly as well as physics, which definitely leads financial engineers to wish that it did work as well.

So if you want to tease anyone for having "physics envy," tease financial engineers, not economists. The only way economists are ever going to envy physicists is if they find out how much physicists...well, never mind.

Friday, May 08, 2015

"Signaling" isn't about signaling

Robin Hanson responds to my Bloomberg View post about signaling.
More generally I call a message “signaling” if it has these features:
  1. It is not sent mainly via the literal meanings of words said.
  2. It is not easily or soon verifiable.
  3. It is mainly about the senders’ personal features, perhaps via association with groups.
  4. It is about sender “quality” dimensions where more is better, so senders want others to believe quality is as high as possible, while others want to assess more accurately. Such qualities are not just unitary, but can include degrees of loyalty to particular allies.
Cheap talk cannot send a message like this; one cannot just say such a thing, one must show it. And since it cannot be verified, one must show it indirectly, via how such features make one more willing or able to do something. And since willingness and ability track costs, these are “costly” signals.
This seems to add a few arbitrary restrictions to the set of things we might try to describe with a Spence-style signaling model. That's perfectly OK (especially since I was complaining about the overuse of the term, not the underuse!). But I think it also makes things a bit more complex than they need to be.

Let's focus on what I think are the three key characteristics of signaling models:

1. The signal must be costly to send for all types.

2. Different types must have different costs to sending the signal.

3. If you take away the cost differential there will be a pooling equilibrium.

The first condition assures us that the asymmetric information imposes costs on the economy; without (1), the model just becomes a truth-telling mechanism. Without (1), you just say which type you are, pay 0 cost, and society knows you're telling the truth.

The second condition creates the separating equilibrium. It means that signaling "works", in terms of revealing people's true types.

The third condition is why you need signaling in the first place. The separating equilibrium isn't first-best (that's guaranteed by condition 1), but it's constrained-optimal. The pooling equilibrium - the thing you avoid by creating the cost differential in (2) - is even worse than the separating equilibrium.

Robin thinks that my example of the hipster moustache is signaling, and explains why:
Let’s distinguish three different kinds of messages I might send with my waxed moustache:  
1) “I have thick shiney (sic) hair.”... 
2) “Hipster is one of my interest areas.”...Technically, this is a “cheap talk” message. 
3) “I am especially devoted to the hipster ethos” or “I especially embody hipster ideals.” That is, I am especially willing to identify myself as a hipster, and my personal features are an especially high quality match to ideal hipster features, including having a creative and contrarian yet attractive and coherent personal style that fits with current hipster fashions. These messages are hard to verify, and the interests of observers and I conflict. While observers want to accurately rank me relative to others, I may want them to estimate me as having maximal devotion and quality. Since verification and cheap talk won’t work here, I have to show, not just say, my messages. 
To show my hipster devotion, I can choose an appearance that is sufficiently off-putting to many people’s work, home, church, etc. associates. By paying the cost of putting off possible associates, I show my devotion to hipsterism. To show my hipster features, I can pay to track hipster fashions and to continually search in the space of possible appearances for a combination that simultaneously reflects current fashions while being creative, coherent, and showing off my best personal features. Not being a hipster, I don’t know how exactly that works for them. But I do know, for example, that since lipstick and tight clothes make some bodies look better while making other bodies look worse, they are costly signals of the quality of lips and body shape. There must be similar factors for showing off hipster qualities.
#3 is why Robin thinks of hipster moustaches as "signaling."

I think it's obvious that hipster moustaches satisfy my condition 2 from above - hipsters definitely pay a lower cost for having hipster moustaches, for a variety of reasons (most importantly, they like the style more than others do).

But do they satisfy my condition 1? Do hipsters pay a net cost for their moustaches? Robin suggests that they do, because the moustaches are "off-putting" to people at work, church, etc. But I doubt that this is, in fact, true. Do hipsters look in the mirror and think "Dang, I wish I didn't have to grow this stupid moustache just to prove I'm a real hipster"? I doubt it. I bet they intrinsically enjoy having the moustaches. This is very different from the experience of someone who has to work hard to get some pointless credential just so he can get a job - i.e., the situation Spence originally suggested.

I also doubt that the moustaches are particularly off-putting to most of the people hipsters want to associate with. Sure, people in some Baptist church in Alabama would be put off if I walked in with a big ol' moustache. But I bet hipsters have no desire to actually go hang out in that Baptist church. Also, I bet they tend to have jobs with people who aren't offended or repulsed by hipster moustaches, because I bet they would really hate the kind of workplace environment where people are repulsed by moustaches. So the mere fact that some people are repulsed by hipster moustaches doesn't mean that hipsters actually pay a cost from that repulsion. In fact, offending those people may give hipsters pleasure.

Next: do hipster moustaches satisfy my condition 3 from above? Are there a bunch of wannabe hipsters who would love to pass themselves off as hipsters if they just didn't have to grow that damn moustache? I doubt it. What non-hipster wants to be a hipster? Maybe a few. Maybe there's some guy out there who really has a thing for hipster girls, and who thinks that they only date hipster guys (False, btw!). But I bet these wannabes are few enough in number that distinguishing themselves from the wannabes is not a huge concern for the hardcore hipsters. (I could be wrong; perhaps America gazes upon envy at the hipster community, bitterly wishing it could be part of the fun!)

Anyway, it's possible that hipster moustaches satisfy all 3 conditions of a true signaling model, but I doubt it. More likely it's just a truth-telling equilibrium.

It also seems likely that much of the fad for labeling non-signaling mechanisms "signaling" is just a nerdy way of insulting countercultures and subcultures. It's a fancy way of saying "Hey hippie, get a haircut!" - of attempting to enforce social conformity by accusing standouts of inauthenticity. But it doesn't really seem to get the economics right, except maybe in a few scattered situations.

(P.S. - If you want mathematical models of conformity, nonconformity, subcultures, hipsters, etc., I would recommend this or this.)

Saturday, May 02, 2015

A quick history of 4chan and the rightists who killed it (guest post)

A lot of the cool funny internet stuff we know and love - LOLcats, Doge, etc. - came from a site called 4chan. But recently, 4chan has become a gathering place for online rightist movements like GamerGate and various racists. How did this come to pass?

This is a guest post by a 4chan user and Portland resident who goes by @animemoemoney on Twitter. He was also an early GamerGate supporter, and even organized one of the first real-life GamerGate meetups, before later repudiating the movement. Here, he tells the history of 4chan and the invasion of un-funny, uncreative anonymous rightists that eventually changed the nature of the site. 


Anonymous Rightists and Their Slow Resurgence on the Internet

At one time, the internet used to be a smaller place. Large social, content hosting websites like Facebook and Twitter now rival large countries in population size. It’s what people do on the internet—browse social media. It’s rare to be out in public and not see a person flip through their mobile device and maybe check their email. The internet is huge now and a ton of people use it.

Before there were advances in consumer electronics, and other forms of utility-increasing technological devices that allowed users easier access to the internet, there were enthusiast forums. Enthusiast forums are not like social media. They behave the same, but there was a far different community dynamic seen in forums of the past. Enthusiast forums are where gamers, anime watchers, or plain jokesters gathered to discuss their hobbies. An enthusiast was more likely to use a slower, now outdated version of the internet as well. 

Enthusiast forums still exist today, and they still have that handmade look of a website built by two-to-three people. The biggest differences between social media websites and enthusiast forums would be the culture and the board software. Instead of putting their real name and uploading a picture of their face, enthusiasts have taken a persona with a custom username and avatar. Enthusiasts loved to take a different persona because it made them anonymous on the internet, and thereby not be judged by their hobbies in real life.  Because of the anonymous nature of enthusiast forums, it meant users’ online behavior wasn’t judged either. 

When Christopher “Moot” Poole created 4chan, he sought to emulate the anonymous behavior of the Japanese website 2channel. Moot was a large browser of the website Something Awful, a web forum dedicated to making jokes and creating original content. Moot would bring Something Awful’s character to his soon to be popular website. He wanted 4chan to be more anonymous than the enthusiast forums of the past, by stripping away usernames and user accounts. 4chan was a great success, and was soon to represent everything Poole loved—anonymity, games, anime, and original content.  

Before 4chan, forums had a lot of rules. The board software would only allow you to do so much, such as make a thread or make a post, but there were also rules made by the moderation team. Users would be expected to obey the rules enforced by the moderation team if they didn't want to be suspended or banned. It was a particularly sad sight when a member of a community was banned forever due to racism, or trolling.  

Unlike forums before it, 4chan didn’t set (many) limits to what was considered acceptable on the website. Forums like Neogaf.com have a very strict expectation for rule following, and will ban you for subtle things like posting in an incorrect tone. The lax rules of 4chan attracted a lot of content producers, and people who loved to post without the fear of gaining a bad reputation, or being banned for behaving a certain way. On 4chan you can be banned for being off-topic, but not for making racist posts. 

There probably was never a moment were racism couldn’t be found on 4chan, but the trend of making racist posts shifted drastically from being an ironic, edgy joke to a very serious habit for a percentage of the posters. It started mostly with the news board “/n/,“ which was deleted for being too packed with race discussion. While it used to be a great place to discuss economics and politics, the board was slowly consumed by people trying to “red-pill” [i.e., convert to rightism] as many people as possible. These “red-pill” posters probably were channers, but they were a vocal minority at that time. After /n/ was deleted, posters didn’t know where to take their race discussion. They went to the firearms board, the anime board, and the video games board but were unwelcome there.
Later on, Moot decided to remake the news board as /new/, and the same process reoccurred. Some people would make threads linking to news articles, and it would be followed by a couple posters presenting the racial truth behind the story; they’d post race statistics, homicide  statistics, and ACT score graphs. Though predictable, these posters where still channers…and therefore jokesters and trolls, so there would be fun discussion even if the content was offensive. 
As time went on, /new/ got more and more radical. The free speech board attracted radicals from all over the internet. But most prominent of the radicals were the hateful plain-text rightists that would soon to dominate. Every thread was filled with racial discussion by that time. The hateful plain-text rightists did not seem to be channers—their posting style was different, they wouldn’t use images, and they wouldn’t recognize the channer language. When a hateful plain-text rightist would be called a “newfag” for example, he would claim he was very against homosexuality. Because of these plain-text hateful rightists, those who didn’t post images or news, the discussion on /new/ became very, very far right. 

Moot would soon delete /new/, probably for the same reason he deleted /n/. An opportunistic man who went by SaveTheInternet would create a website for /new/’s old user base to post at.  That website would be called 4chon, and it was basically just the /new/ forum, with some other boards for community support. People did make news threads at this forum, but it was crowded out with race discussion, conspiracy theory culture, and a very confused love for the Mises Institute. Unfortunately, the chan culture seemed to leave these posters, and they would become hateful plain-text rightists themselves. Anime posting was soon discouraged, and much of what made a 4channer in the past would be considered “degenerate.” It was very sad to watch channers take in the judgmental attitude of a mysterious group of anonymous rightist invaders and use it to dissolve their own culture. . . which is what made their image-board so special.

Moot recreated the news board as the /pol/ “Politically Incorrect” board, making it the third board where rightists gathered on 4chan. In /pol/, you weren’t expected to have to post news, just whatever politically incorrect ideas that you had at the time. This new board would slowly kill alternative boards like 4chon, which relied heavily on defected 4chan posters. Moot would claim in his 7 hour departure Q&A that creating sites like 4chon, based solely on hatred of other people or other internet forums, “didn’t really create a lot of great content.” The activity of /pol/ would soon rival the activity of the anime forum. In the word-of-mouth between posters, there was a joke that /pol/ was a containment board and just a place to keep anonymous plain-text rightist posters off of the other 4chan boards. 

Despite most of the rightist discussion being limited on /pol/, there was a website-wide rightening of 4chan culture. Memes were mostly critical of different races, and even the most progressive parts of 4chan would bemoan the identity politics of Tumblr. When dislike of identity politics reached its height, the video games forum would launch an anti-left politics movement called GamerGate to demand a reform in game journalism ethics. While GamerGate started off as a very diverse, vocal opponent to what they saw was unethical journalism (before it was debunked), many of the anonymous /pol/ rightists would take advantage of its anti-left character by creating sock-puppets. Unfortunately, activities like GamerGate would prove to be too much, and cause Moot to step down from 4chan’s admin position. 
Today it is hard to find a 4chan user that doesn’t have an attachment to far right politics. By being anonymous, rightists took advantage of their lack of identity to spread a hateful world-view. Some 4channers bought the right wing philosophy completely, others accept only some of it. Many only spread the rightist memes as a joke.