Russ Roberts predicts my policy positions

Earlier this year, there was an interesting debate between Russ Roberts of EconTalk and Adam Ozimek of Forbes about ideology and economics. Basically, Roberts (mostly on Twitter) took the cynical position that ideology governs much of people's stances on policy positions, that this is inevitable, and that we should just accept it. Ozimek said no, economists aren't as ideological as Roberts thinks, even commentators in the public sphere. He also said that if you find that your own positions are driven by ideology, it's a sign that maybe you should rethink how you form your positions.

More recently, the argument flared up again. Roberts declared the following:

Then one day I realized that if I knew one policy position of an economist, I could predict the others ones. 3/

— Russell Roberts (@EconTalker) October 20, 2015

I then challenged Russ to predict my positions on various policies. Initially I suggested that I would tell him three of my positions, and then name three other issues and ask him to predict the second three. He counter-suggested that he would merely pick a bunch of issues and predict my positions on all of them. I agreed, despite the fact that this was not as good a test of Russ' thesis.

Anyway, though, Russ did come through with the promised predictions, and posted them on Twitter. Here they are (sorry for the weird embedding of reply-tweets):

1/ I suggested I could predict an economist's policy positions if I knew one of them. @Noahpinion challenged me to pick his.

— Russell Roberts (@EconTalker) October 25, 2015

2/ Not really fair. I could read a bunch of his stuff. But I will try to be honest and let him respond. What do I know about him?

— Russell Roberts (@EconTalker) October 25, 2015

3/ Don't read him regularly. But I know he considers libertarians to be dogmatic and loony. He thinks econ is more scientific than I do.

— Russell Roberts (@EconTalker) October 25, 2015

4/ I follow him on twitter. So I know he is somewhat left-leaning politically. So this should be easy. But maybe he'll surprise. Here goes.

— Russell Roberts (@EconTalker) October 25, 2015

5/ He is happy ACA passed. Supports an increase in mw to either $12 or $15. Thought the stimulus was a good idea. Maybe wishes it had been >

— Russell Roberts (@EconTalker) October 25, 2015

6/ Generally thinks Bernanke did good job. Thought bailouts were necessary. Would support higher taxes on rich. Thinks CFPB was good idea.

— Russell Roberts (@EconTalker) October 25, 2015

7/ Wants unemployment insurance extended. Opposes school vouchers. Wants more govt $ spent on education. Likes idea of Fannie and Freddie.

— Russell Roberts (@EconTalker) October 25, 2015

8/8 Wants stricter gun control. Probably basically pro on trade and immigration but not for fully open borders. So, @Noahpinion--how'd I do?

— Russell Roberts (@EconTalker) October 25, 2015

OK, here is a scorecard. Russ named 13 policy issues and predicted my positions on all of them. I will give 1 point for a correct prediction, 0 points for an incorrect one, and 0.5 points if I don't really have a position or am not really sure. I will also include brief explanations of why I hold the various positions - not because I love hearing myself dispense opinions, but so I can prove that I'm being honest about what I think. Here goes:

1. ACA (Obamacare): I'm not sure. I don't really know much about health care policy. My instinct says that the most important health care problem in America is high excess cost of care, not the number of the uninsured. Obamacare does do some things to try to address the cost problem, and costs do seem to have decelerated somewhat in the last few years, but I just don't know how big of a factor Obamacare has been, or whether the cost slowdown is a permanent thing.

Score: 0.5 pts.

2. Minimum Wage Increase: I favor local experiments with $12 or $15 minimum wages but not a national minimum wage hike - at least, not until the results of the experiments have come in, which will take years. Even then, national minimum wages are generally not great because they don't take local cost differences into account. Also I think EITC dominates minimum wage in most respects, and if paid as a wage subsidy instead of a tax credit would dominate in all respects.

Score: 0 pts.

3. 2009 Stimulus: Yes, probably a good idea. The temporary tax credits didn't do a whole lot, but support for state spending probably did do substantial good. And the stimulus included a substantial amount of money to shore up our badly underfunded infrastructure. Moreover, the deficit (and spending as a percent of GDP) has since come down to normal levels, quieting people's worries that the stimulus was a cover for permanent increases in spending and/or deficits.

Score: 1 pt.

4. Bernanke: Yes, Bernanke did a good job. Monetary policy was probably a factor in averting a Second Great Depression.

Score: 1 pt.

5. Bailouts: Probably something like that was necessary. But I think bailouts were handled badly in the heat of the moment; should have been much harder on management of big banks, to avoid future moral hazard. Still, long-term net costs to the government of most of the bailouts (with the exceptions of AIG and GM) were zero. So I'll give Russ the point.

Score: 1 pt.

6. Higher Taxes on the Rich: I don't have a moral problem with raising taxes on the rich, and I doubt the efficiency cost would be that high (rich people aren't really working to consume). However, I am very pessimistic about our chances of actually getting the money from the rich people, who are very good at avoiding taxes. Taxes on the rich used to be much higher, but the share of tax revenue as a percent of GDP was about the same. I do, however, think a higher inheritance tax would be a great idea. Not only would it tax unproductive "trust fund babies", but it would also probably raise the happiness of many rich people themselves in the long run. I think most rich people - or at least, most "self-made" rich people - don't realize how much their kids will be spoiled by large inheritances. So inheritance taxes can help save rich people from their own mistakes!

Score: 0.5 pts.

7. CFPB: Seems like it has been doing good so far, though too early to tell whether it will remain effective in the long run.

Score: 1 pt.

8. Unemployment Insurance Extension: No. We're way past the recession. Unemployment insurance is an automatic stabilizer, but it does discourage work. And the more work gets discouraged, the more people's skills and resumes and work ethic decays, and the more danger they are in of falling into the ranks of the long-term unemployed.

Score: 0 pts.

9. School Vouchers: My God, what a terrible idea. Privatized education just fails, fails, fails whenever it's tried. History is clear: It does not work. Vouchers are also a form of faux-privatization, where the government pays the bills but doesn't administer the service. That is a clear and unequivocal recipe for ineptitude, waste, fraud, corruption, and inefficiency. Russ is totally right about my position on this one.

Score: 1 pt.

10. More Govt. Funding of Education: Not sure. Don't know how effective this is. It would probably depend crucially on how the money was spent, though I don't know enough to know what the "good" way is.

Score: 0.5 pts.

11. Fannie & Freddie: Bad. These agencies seem like yet another example of faux-privatization. Government provides the funding (in this case, in the form of a guarantee), but doesn't do the administration, leading to bad incentives. Also, I think we incentivize homeownership way too much in this country.

Score: 0 pts.

12. Stricter Gun Control: Probably not. I grew up in small(ish)-town Texas, where tons of people had guns and there weren't any shootings that I ever heard of (though probably some accidents). Canada has relatively high gun ownership and very little crime, including few mass shootings. Brazil has a small fraction of the gun ownership we have, and much higher crime. Meanwhile, we've had a huge drop in crime in the last two decades with no real increase in gun control. Let's try to replicate that success before we start disarming the populace. I will admit that my stance on this has wavered recently, in light of the rash of mass shootings, but I still don't think gun control is likely to have a huge effect. A much, much more important policy for reducing gun death would be to end the War on Drugs.

Score: 0 pts.

13. Trade and Immigration: Russ is right. I'm basically pro-trade and immigration, but not for open borders. I'm definitely more skeptical of free trade than the average economist - I think industrial policy can be useful for developing countries, and I think that trade with countries that manipulate their currencies can sometimes be self-defeating. I also think that international capital flows can be destabilizing and can reduce productivity in some countries. But I will still give Russ the full point.

Score: 1 pt.


Total score: 7.5 out of 13


That is slightly better than random chance. But remember, Russ follows me on Twitter, which gives him an advantage. Also, he was able to choose the issues, which gives him a number of additional advantages - he can choose positions on which a substantial majority of Americans agree, he can select several issues correlated to those on which he is most sure about my position, etc. Given this, I don't think Russ was able to predict my positions that well.

The only obvious cluster of predictive success was on policies relating to the financial crisis. Russ correctly predicted my positions on Bernanke, the bailouts, and the CFPB.

I think this exercise shows a number of different "failure modes" of attempting to model people's policy positions based on an assessment of their ideology. For example:

1. You may fail to assess people's ideology correctly. Russ probably didn't expect that I'd intrinsically value the personal liberty of owning guns. He also probably thought I would be more eager to tax the rich simply in order to reduce inequality (regardless of its efficacy).

2. Your model of ideologies may have errors. Russ probably assumed I'd have ideological reasons to support Fannie and Freddie, because he thinks I'm a liberal, and liberals support Fannie and Freddie. But I'm not sure this is true - I've never seen liberals defend those agencies. Maybe some have, but it doesn't seem to be a pillar of liberal ideology.

3. No model of ideology is perfect. "Liberal" is a name given to a cluster of ideas, but few people precisely fit that cluster. Most people have at least one or two positions that don't toe the ideological or party line. Each individual's ideology is complex, and the standard clusters, like "liberal" and "libertarian", are only approximate models. Russ probably didn't guess that my values would be "liberal" on the CFPB, "libertarian" on gun control, etc. Even I don't know what to call myself, ideologically.

4. People disagree on the facts, not just on values. In general, people with heterogeneous priors about the state of the world will fail to reach agreement even after seeing all of the same evidence. And when people form their policy positions, they consider efficacy of policies, not just whether the intended effect would be a good thing. Russ probably didn't bet that I would be pessimistic about the efficacy of taxing the rich, the usefulness of the ACA's tax credits, or the effectiveness of gun control. He also probably underestimated my uncertainty about the effect of Obamacare on health costs, the usefulness of education spending, and the employment effects of minimum wage hikes.

So anyway, this was a fun exercise, and thanks to Russ for taking the time to do it. I'm not sure how it really relates to the original Roberts-Ozimek debate, but it was interesting nonetheless.


Updates

A few people have suggested I was too hard on Russ in my scoring. I gave him 0 points on minimum wage, despite the fact that I like the idea of conducting natural experiments with local minimum wages. And I gave him only 0.5 points on taxing the rich, despite the fact that I favor a higher inheritance tax.

Well, maybe; it's hard to score precisely. Some things are closer to 0.7 or 0.3 than 0.5. I did the best I could. On minimum wages, my opposition to a national minimum wage, and my belief that EITC is just better, made me give it 0 instead of 0.5. In reality it's more like 0.2, rounded down. On taxes-on-the-rich, I gave 0.5, because it really depends on what we use the revenue for. If it's for inefficient subsidies or boondoggles like the F-35, I say *cut* overall taxes on the rich, while shifting from income to inheritance taxes. I don't want to raise taxes on the rich just to "soak the rich" and stamp out inequality, as many do. So I don't think this deserves more than a 0.5. 0.6 at most.

Then there were a couple where I rounded *toward* Russ' prediction. For example, on bailouts, I gave him 1 point, even though I think the bailouts were not executed well and created moral hazard. So that's really more like 0.8, rounded up. And on the stimulus, I think about half of it went to utterly useless (but not particularly harmful) tax credits. So that's more like 0.8 or 0.9, rounded up. My skepticism about the pro-trade consensus probably makes that a 0.9 as well, rounded up.

So overall I think I was fair, and my inevitable roundings came out a wash. Plus, this isn't a scientific test, so changing to 7/13 or 8/13 wouldn't change the basic message, which is about how "ideology cluster" models can fail.

How China got rich

I do not understand this Tyler Cowen post about Chinese catch-up growth:

It seems obvious to many people that Chinese growth is Solow-like catch-up growth, as the country was applying already-introduced technologies to its development. 

But how many other economies have grown at about ten percent for so long?  Was there not a secret ingredient added to the mix? 

Increasing returns to scale?...Something about Communist Party governance which enabled the corruption to be channeled productively into building more infrastructure rather than holding up progress?  Tiger Mom parenting combined with a relatively meritocratic exam system?... 

More radically, is there some “natural,” culture-neutral rate at which innovations trickle down from the world leaders to the poorer countries?  The diversity of growth rates would seem to indicate not.  Is each country then not innovating — with varying degrees of success — by building its culture-specific net for catching and transmitting global innovations throughout the nation?

I don't know about Tiger Mom parenting, effectively channeled corruption, or "culture-specific nets", whatever those are. I do know, however, that Solow catch-up growth is not about TFP increase or the diffusion of innovation!

There are basically two kinds of catch-up growth. The first is where you cheaply copy innovations from countries at the technological frontier. That's what Tyler is talking about. But the second, Solow catch-up growth, is far simpler - it's just about capital accumulation.

Countries don't start out with capital - they have to build it. So they save some of their production each year and use it to build productive capital (or trade it to other countries for capital). They do this until they have so much capital that they hit the point of diminishing returns, and depreciation starts to get so costly that it doesn't make sense to build any more capital (per worker).

Really simple. Save money, build capital. And that's exactly what China has been doing. Here's a graph from a Federal Reserve Board discussion paper from 2013:

A very smooth exponential increase in the capital-to-labor ratio.

Now of course, in the Solow model, that red line should flatten out and turn into an S-curve eventually, as the K/L ratio reaches the steady state. That day of flattening will be delayed by productivity improvements - i.e., by the other kind of catch-up growth (plus any original innovation China does along the way).

But a lot of Chinese catch-up growth - about two-thirds, according to a standard decomposition - looks just like the classic save-money-and-build-capital thing. China has many more roads, many more railroads, many more cars, many more trucks, many more buildings, many more machine tools, and many more computers per person than it did in 1980 or 2000.

We don't need Tiger moms, culture-specific nets, or increasing returns to scale to explain that.

In fact, though China's growth looks more productivity-driven than some other Asian economies, It is probably less productivity-driven than Japan's catch-up was. If you want to look for Asian countries with cultural secret sauces, I'd start with Japan instead of China. Remember, when we talk about China, we're talking about a country whose per capita GDP is still only about a quarter of the countries at the frontier. And it's not yet clear how rich China will get before its growth slows dramatically.

The question of how technology diffusion happens is, of course, one of the great unsolved and under-studied mysteries of economics.


Update: This paper seems relevant.

Econ critique scorecard

I wrote a post about lazy econ critiques, so some folks on Twitter were asking me "Which critiques do you think are good, and which are not?" So since I'm overjoyed when someone actually cares what I think enough to ask, I decided to make a list! Naturally, the critiques will be simplified and a bit straw-mannish, but you get the idea.


Bad Critiques

1. "Econ should stop pretending to be value-neutral."

Call me crazy, but I think researchers should try to keep facts and values ("positive" and "normative" econ) separate. They won't completely succeed, but they ought to try their best. No matter what your values are, you'll be better able to implement them if you know the facts as much as possible. That doesn't mean economists shouldn't have values, it just means they should try not to let those values interfere with their assessment of the facts.

"But dude, being anti-ideological is an ideology too!"

Mmm, an insightful and trenchant observation. Now go take another bong hit and leave me alone.


2. "Econ should stop pretending to be a science. It's just a SOCIAL science."

What does it even mean to "pretend to be science"? Does history pretend to be science? Does anthropology? Does literature? Social science has different kinds of data from the lab sciences, but you do the best with what you have.

As for the idea that human beings can't be studied scientifically - well, you hear a lot of people say that, but it seems blatantly and obviously wrong. There are lots of models that predict human behavior very well in various areas. Not just in econ, either, but in operations research and other fields. So this critique is just incorrect.


3. "Econ has physics envy."

Nah.


4. "Economists failed to forecast the financial crisis."

Hey, if you can't forecast, you can't forecast. We can't forecast earthquakes at all (except aftershocks). We can't forecast hurricanes very well. Maybe crises and big recessions are just really hard to predict.

Of course, the argument that econ ignored the importance of the financial system, leverage, etc. was totally valid, but much has changed since 2008 (see next section).

And I guess I'd like to see more academic macroeconomists express concern about the forecasting problem, but instead they've decided to just leave the job of forecasting entirely to the private sector (where tons of people are working on it).


5. "Econ focuses too much on equilibrium, which doesn't really exist."

I've got some news for the outside world. Economists have redefined the word "equilibrium" to mean "any solution of a system of equations." Every solution of every model is called an "equilibrium".

Now, some kinds of economic equilibria probably don't exist very much (see later section).


Critiques That Used To Be Valid But No Longer Are 

1. "Econ ignores the financial system."

Not anymore, they don't!


Critiques That Are Less True Nowadays But Still Somewhat Valid

1. "Econ relies too much on theory, and not enough on data."

Empirics are on the rise. Theory is a smaller part of what econ does these days. I still see large numbers of wanky theory papers at seminars and such. But it seems like more and more of them are either A) job market candidates proving they're smart, or B) old folks having fun because they can. Nowadays, as Paul Romer says, "[I]n the new new equilibrium, empirical work is science; theory is entertainment."

But despite the decreasing flow of new theory, or at least prominent new theory, some econ literatures are still crammed with mutually contradictory models for which the scope conditions are neither known nor specified. And the stock of existing theories is still enormous. In some areas, especially in macro, economists really do have theories that make almost any prediction, with no real way to choose between them except priors and politics. And many economists still have very little problem using modeling assumptions that have already been taken to the data with discouraging results.

Also, as someone pointed out in the comments, econ models often sacrifice too much realism for the sake of tractability. If you have to publish theory papers, but it's too hard to get a result using solid assumptions, you go with silly assumptions. Hopefully the decreasing importance of model-making will decrease the pressure to pump out this kind of silliness.


2. "Econ uses too much math."

Go back and read some papers from the 70s and 80s. They are much more obsessed with pointless mathematical rigor and aping the style of math papers.

Of course, that doesn't mean that econ uses math for good purposes. There's a lot of what Paul Romer calls "mathiness" going around.


3. "Econ is a front for neoliberal/laissez-faire politics."

This was definitely somewhat true for a while. Especially in the Cold War, where economists became part of the ideological opposition to communism. Milton Friedman and Friedrich Hayek really were the public face of the profession for a while. But since then, the profession seems to have drifted in a leftward direction, in terms of economists' views, the profession's public face, and probably the implications of the results in econ papers.

There are still a few old Cold Warriors left, of course. There is still a lot of Koch money being funneled to certain econ departments and think tanks. There is probably still a subset of economists who were drawn to the profession because it seemed more conservative than other areas of academia. And there are still the Austrians, running around pretending to have something to do with the profession.


4. "Econ is sexist."

Yep, but it's clearly getting better, thanks to increased awareness and to the efforts of the AEA and other organizations.


5. "Econ colonizes other social sciences while ignoring their input."

My sense is that the Gary Becker project, of trying to understand social/cultural phenomena with standard econ models, is not doing so hot these days. You still see a lot of this on blogs and in pop econ books, but within the profession it seems generally recognized that things like norms and social preferences drive a lot of social phenomena. The problem with Becker stuff, as I see it, was that it focused too much on very standard, classic types of utility. Once you start bringing in new kinds of utility like norms and social preferences, those utility choices end up driving the results completely, and fancy econ techniques become only marginally useful. But it still sells pop books.

As for not taking input from the other social sciences, econ is still very siloed. Behaviorists have taken some input from psych. And poli sci methods and econ methods are converging so much that they are often indistinguishable at this point, in certain fields. But econ still ignores the existence of sociology entirely. Hopefully, as empirical methods become unified in sociology and econ, this will change.


6. "Econ is enslaved to the financial industry."

There has definitely been some corruption. Incentives matter, obviously. I don't think it was ever that widespread - most economists have nothing to do with finance - but there was a bit. But the AEA instituted a stricter ethics code in 2012, and there is more scrutiny of economists who do sponsored research. So the problem seems like it's being addressed.


7. "Economists assume Rational Expectations, which is B.S."

RE doesn't seem to be a very good assumption, except sometimes in the long run when you also have some lucky properties like time-invariant stochastic processes. It is very true that in the past, economists - especially in macro - were essentially forced to assume RE. Nowadays we are definitely seeing more deviation from that orthodoxy - Bayesian and non-Bayesian learning models, bounded rationality models, and other stuff. This critique is still mostly valid, though.


Valid Critiques

1. "Econ spends too much energy on macro."

Yep. Seems like macro is about a quarter of the econ profession. But given data limitations, a lot of that effort seems to go into making useless models. Macro is the glamour division of econ, but maybe more economists should avoid the glamour and get down in the muck where there are real conclusions to be had.


2. "Econ is obscurantist."

Definitely. This is a problem plaguing much of academia. In math and physics there are natural barriers to entry, because getting stuff right, though possible is just really hard, so only really smart people can enter those fields. In lab sciences, huge fixed costs are the barrier, with a fairly high degree of smarts also required. But in social sciences and humanities, there are fewer natural barriers, so the practitioners have to create them in order to increase their monopoly rents.

One way to do this is hyper-specialization. You see a lot of this in history, for example. Another way is to make up a ton of bullshit neologisms and spend all day arguing over what they mean, which requires defining them in terms of other neologisms, ad infinitum. This seems to constitute most of "critical theory". But a third method is to artificially increase the level of intelligence needed to do work in your field. This seems to be the approach taken by econ, where people who will spend their careers digging up natural experiments to test simple linear models are nevertheless forced to learn what a sigma algebra is. It also might be the reason for the use of purely mathematical methods to study every possible problem, even when those methods may not help or illuminate. It might even be one reason for the turgid, impenetrable style of many econ papers...


3. "Economists are arrogant."

Well, when you get paid more than almost any other academics, constantly sought after for policy advice, and treated as a sage on every conceivable topic from how to find a good restaurant to how to find a good spouse, you do tend to get a little full of yourself! :-)


4. "Economists believe their theories too much."

"Models are just tools for understanding specific situations," says every economist who believes his own models are The Truth And The Way.


5. "Welfare economics is silly."

Yeah, pretty much. Add realistic non-standard preferences and everything changes wildly. Add time-inconsistency and it becomes utterly hopeless.


Critiques Of Whose Validity I Am Not Really Sure

1. "Econ makes people bad, selfish, and immoral."

There's some evidence to this effect, but it doesn't seem conclusive.


2. "Economists need to get out and have more contact with the real world."

I hear people say this, but I really don't know how much contact the average economist has with the real world. I know some who seem to have essentially none, and some who seem to have a lot.

3. "Economies are complex adaptive systems, hence you will never be able to understand them."

...Maybe. *shrugs*

4. "Econ 101 is filling kids' heads with bad ideas."

I'm not sure about this, since Econ 101 must be taught very differently at different schools. The only thing I really know that is constant across schools is the identity of the most popular 101 textbooks. And Mankiw and Krugman's textbooks are pretty good, I think, although they're almost all theory and very little about empirical evidence. That's something I'd like to see change at the 101 level, for sure.

5. "General equlibrium/Walrasian equilibrium sucks."

I'm not sure. I haven't seen a lot of general equilibrium models that look like they've had a high degree of success in explaining observed phenomena. But it's a big, big world out there, and there are LOTS of general equilibrium models, and people studying how these models fit the data.


Anyway, off the top of my head, there's my list. Anyone have any more you'd like me to add? Leave them in the comments!

Racial bias in police killings

There's a very interesting debate going on between Harvard's Sendhil Mullainathan and Barnard's Rajiv Sethi, on racial bias in police shootings.

Mullainathan looked at the data and found that police likelihood of shooting a black person in a given encounter was no higher (or barely higher) than their likelihood of shooting a white person. He concluded that while police may be racially biased in terms of how often they go after black people, they're not very biased in terms of how likely they are to shoot the people they go after.

Sethi said: Not so fast. Mullainathan just looked at the killing rate conditional on an encounter, but Sethi wants to also condition on the type of encounter, which probably differs on average across races. Police might be more likely to misinterpret nonthreatening encounters with black people as threatening, and therefore be more likely to pull the trigger. Sethi's hypothesis says that police basically give black people a hard time, initiating disproportionately many encounters for innocuous things (racial profiling), and then pull out the gun when they interpret those innocuous encounters as threatening situations.

Sethi might be right. But it seems to imply some odd psychology on the part of cops. It implies that cops routinely go after the people who scare them the most. It implies that cops routinely and preferentially launch themselves into what they expect to be threatening situations.

That would be really weird. It could be true, of course - maybe cops have an incredibly strong sense of courage and duty, forcing them to bravely stand up to the (not actually) threatening, dangerous black people time and time again. Or maybe there is some institutional pressure from higher-ups forcing cops to do racial profiling. These explanations were both suggested by a sociologist friend to whom I posed this question. But they feel like quite a stretch. Cops get a lot of discretion in who they stop. And I doubt they are usually driven by an almost pathological sense of duty and courage.

Let me offer an explanation I see as more likely: Cops often tend to shoot (or otherwise brutalize) people not out of fear, but out of wrath.

My hypothesis goes like this. Cops pull out their guns and their nightsticks when they see suspects as having challenged their authority. They are determined to maintain power and control at all costs (i.e., South Park nailed it). Black people are more commonly seen as challenging cops' authority, probably because a lot of black people grew up in a state of relative anarchy and therefore lack other people's conditioned response of instant meek submission to police.

This seems to be exactly what happened with Eric Garner. He wasn't threatening at all; he's obviously a big teddy bear, he doesn't have any weapon, and he wasn't making any move to attack anyone. But he's an insubordinate teddy bear, who thinks he can reason his way out of an unfair arrest. So the cops grab him and choke him to death.

It also explains why so many suspects get shot in the back. For example, Walter Scott. A man who's running away is not a threat. He is not a source of fear. He is, however, flouting authority. Same with Samuel Dubose. Type "police shoot black man" in Google, and "police shoot black man in the back" is one of the first results that come up.

Here the police shoot a black guy in a wheelchair.

This psychologically plausible hypothesis is also parsimonious, because it allows police racism to explain both racial profiling and excess unjustified brutalization of black people. It also implies that in areas with entrenched racial conflict - say, the South - white police will be more likely to kill black people, because they view blacks as socially subordinate (hence any backtalk or resistance will be seen as more unacceptable if it comes from a black person than if it comes from a white person). So that would be an interesting test.

Anyway, to sum up, I think Sethi is right to say that equal rates of shooting per encounter don't imply that police are unbiased. But I think his explanation - police fear of blacks - isn't as likely as a wrath-based explanation.

Of course, if you drag a cop in front of a judge (or the media) and ask "Why did you shoot that guy?", of course they're going to say they were afraid. Fear generates sympathy. But color me skeptical.

In the MISO soup

Robin Hanson declares that thanks to Big Data, we will soon discover the SUPER FACTORS that drive all of human differences:

In a factor analysis, one takes a large high-dimensional dataset and finds a low dimensional set of variables that can explain as much as possible of the total variation in that dataset. A big advantage of factor analysis is that it doesn’t require much theoretical knowledge about the nature of the variables in the data or their relations – factors are mostly determined directly by the data... 

[P]eople vary in far more ways than intelligence, ideology, and personality, and factor analyses have been applied to many of these other human feature categories. For example, there have been factors analyses of jobs, brands, faces, body shape, gait, accent, diet, leisure behavior, friendship networks, physical health, mortality, demography, national cultures, and zip codes. 

[F]actors found in different feature categories are often substantially correlated with one another. This suggests that if we put together a huge super-dataset describing many individual people in as many ways as possible, a factor analysis of this dataset may find important new super-factors that span many of these features domains. Such super-factors would be promising candidates to use in a wide range of social research, and social policy... 

I’d guess that the super-factors found in a super dataset of human details will instead be revolutionary. We will afterward see uncovering them as a seminal milestone in our progress in understanding human variation. A Nobel prize worthy level of seminality, or more. All it will take is lots of tedious work to collect a super dataset, and then do some straightforward number crunching.

Here's an object lesson in the perils of analyzing data without theory to guide you! Yes, it's easy to do a principal component analysis on a multidimensional data set and find some relatively small set of "factors" that "explain" most of the data. If we do what Robin says and throw everything we know about human characteristics into one massive data set and hit the PCA button, the STATA of the future will pop out our "super-factors" in short order.

One of the biggest super-factors will be income.

See, factor analysis doesn't tell you whether the factors cause all the other stuff, or are effects of the other stuff. In the world, there can be effects with multiple causes, and causes with multiple effects. In signals theory (a very different kind of signaling than the kind Robin is used to thinking about!), this might be called Multiple-Input-Single-Output and Single-Input-Multiple Output, or MISO and SIMO.

An example of SIMO would be anxiety disorder. A penchant for severe anxiety is going to affect your working life, your interpersonal life, your hobbies, etc. in statistically predictable ways. One cause, many effects.

An example of MISO would be income. Our marvelous market economy allows people to make money using a dizzying myriad of talents, skills, and resources. Some people make money by hitting a ball with a stick and running around a field. Some people make money by making big macro bets in financial markets, getting the first one right by luck, and then taking in billions of dollars in management fees. Some people make money by being friends with the right politician. Some people make money by inventing new kinds of semiconductors. And so on, and so on. One effect, many causes.

Since money can buy a ton of stuff, everyone wants money. And since money can buy a ton of stuff, almost anything valuable can be sold for money. So if income is among the set of characteristics in Robin's ultimate data set, it will undoubtedly emerge as one of the most important factors.

You can already see evidence of this in the media. Barely a day goes by without an announcement by Quartz or the Huffington Post that income differences predict differences in...you name it. School success, romance, self-confidence, frequency of weird eyebrow twitches. The assumption, of course, is that wealth privileges people in innumerable ways - i.e., that income is a SIMO kind of thing. But whether that's true, it's also likely true that income is a MISO kind of thing, where almost any positive or desirable trait can be leveraged - or is correlated with something that can be leveraged - to produce income. That, really, is why income is going to be correlated with almost any desirable human trait, no matter how little "privilege" remains in society.

So Robin's "super-factors" are quite possibly going to be very mundane things. MISO processes will cause a few desirable goals to be highly correlated with a large number of human traits that are useful in obtaining those goals.

Interesting, but hardly worthy of a Nobel. And a reminder that pure statistical analysis, without explicit theory to guide it, will be guided by implicit, simplistic theories.


P.S. - One thing Robin wrote that I didn't understand was the following:

As many people know, intelligence is the main factor explaining variation in cognitive test performance, ideology is the main factor explaining variations in political positions, and personality types explain much of the variation in stable attitudes and temperament.

Aren't these basically just labels? "Intelligence" is our word for cognitive test performance. "Personality type" is our word for stable attitudes and temperament. Seems to me that simply isolating a principal component and labeling it is a far cry from actually understanding what you're looking at.

State price indices! Get em while they're hot!

Martin Beraja, Erik Hurst, and Juan Ospina have constructed state price indices from retail scanner data! That's pretty badass. Nice job, guys.

I don't know what state-level price indices already exist, but these look pretty good, so if you need state-level price data for your research, you might want to mail these guys! It's only from 2006, of course, and it's biased because it only includes stuff that people buy in stores.

Anyway, Beraja et al. use their state-level data to help make a model of regional shocks. (I don't really believe the model that much, but that's not the point.) This kind of micro-flavored macro - "dissagregated" macro, if you will - seems to be getting more important. I've heard a number of other macro folks talk about making these sorts of models, and there seems to be a lot more focus on collecting region-, industry-, and firm-specific data. Related trends include models with heterogeneity, network models, and institutional models (for example, this one that I just saw presented).

That's cool. A lot of macro people seem to have woken up to the fact that their old model paradigms (NK, RBC, and the like) weren't really working, and new stuff is needed. And also, at the same time, woken up to the fact that the available data aren't very informative. The new micro-focused macro models, and new data sets, seem to be ways of trying to chip away at the problem. The new stuff hasn't taken over yet, but it's spreading.

Also, Beraja et al.'s data set demonstrates quite clearly how the IT revolution has dramatically increased data availability. I think everyone realizes that that's the big force changing econ right now.

Lazy econ critiques

Hey, you know, I like a good econ critique as well as the next person. Goodness knows, econ needs some critiquing. The profession is still too soft on wanky (i.e. useless or untestable) theory, still sloppy with the evidence, still focused too much on macro, still too enamored with libertarian ideas, and still too accepting of sexism. But compared to a lot of fields out there, econ is really on an upward trajectory. Theoretical particle physics is in the process of abandoning empiricism for wanky string theory, psych has a huge reproducibility crisis, anthropology has degenerated into leftist activism, and sociology appears to be in danger of following. Compared to those guys, econ looks like it's in pretty good shape, with much better data, more of an applied micro focus, and rapid innovation in empirical methodology.

BUT, it's Econ Nobel season, and so someone needs to do the job of standing up and repeating all the old disses. This year, it's Joris Luyendijk in The Guardian. Here are a few of the tired old chestnuts that we see trotted out from time to time (chestnuts can trot because they're horse chestnuts, so shush).


1. "Econ isn't a real science."

Luyendijk:

And yet on Monday the glorification of economics as a scientific field on a par with physics, chemistry and medicine will continue. 

The problem is not so much that there is a Nobel prize in economics, but that there are no equivalent prizes in psychology, sociology, anthropology. Economics, this seems to say, is not a social science but an exact one, like physics or chemistry – a distinction that not only encourages hubris among economists but also changes the way we think about the economy.

Are the Nobels glorifying peace and literature, and setting these fields up as "on a par" with the natural sciences? If so, it's just one more reason why Nobel prizes are silly. If not, then shush.

Sure, econ is (mostly) empirical instead of experimental. It relies mostly on real-world data and natural experiments instead of laboratories. So what? The same is true of ecology and astronomy. I don't see people writing articles every year saying that these aren't real sciences and shouldn't get big gold medals.


2. "Social science isn't science."

Luyendijk:

A Nobel prize in economics implies that the human world operates much like the physical world: that it can be described and understood in neutral terms, and that it lends itself to modelling, like chemical reactions or the movement of the stars. It creates the impression that economists are not in the business of constructing inherently imperfect theories, but of discovering timeless truths.

Um...almost all theories in all disciplines are imperfect. Newton's Laws don't describe all motion. The Germ Theory of Disease doesn't describe all disease. Our understanding of almost any subject is incomplete, and our leading ideas flawed.

And where is this law of the Universe that says that the human world can't be modeled like the world of particles or the world of cells and DNA? Does anyone have evidence to back up that contention? How the heck do you know that human behavior doesn't lend itself to modeling? If humans are so unpredictable, tell me why Google auctions get so much money from advertisers, or how economists can predict how many people will ride a train before the train is built. If you think social science can never be science, explain to me why these successes were possible.


3. "Economics caused the financial crisis."

Luyendijk:

To illustrate just how dangerous that kind of belief can be, one only need to consider the fate of Long-Term Capital Management, a hedge fund set up by, among others, the economists Myron Scholes and Robert Merton in 1994...Markets, it seemed, didn’t always behave like scientific models. 

In the decade that followed, the same over-confidence in the power and wisdom of financial models bred a disastrous culture of complacency, ending in the 2008 crash. Why should bankers ask themselves if a lucrative new complex financial product is safe when the models tell them it is? Why give regulators real power when models can do their work for them?

Someone doesn't know the difference between econ and financial engineering! The kind of neoclassical econ, based on rational agents and utility maximization, that gets so much grief on the blogs was not even involved in the models that brought down the financial system. Financial engineering is more applied math than econ - no assumptions of individual rationality, just a bunch of assumptions about statistical relationships. Yes, an unjustified belief in market efficiency helped people get complacent and ignore the gathering risks. No, economists were not the only, or even the loudest, voices telling people not to worry.

4. "Econ uses too much math."

Luyendijk:

Over the past decades mainstream economics in universities has become increasingly mathematical, focusing on complex statistical analyses and modelling to the detriment of the observation of reality.

Complex statistical analyses, eh? What do you think they are analyzing? Data. And what is data? Systematic observation of reality.

5. "Economics tries too hard to be value-neutral. In fact, it's always ideological."

Luyendijk:

Perhaps the most pernicious effect of the status of economics in public life has been the hegemony of technocratic thinking. Political questions about how to run society have come to be framed as technical issues, fatally diminishing politics as the arena where society debates means and ends. Take a crucial concept such as gross domestic product. As Ha-Joon Chang makes clear in 23 Things They Don’t Tell You About Capitalism, the choices about what not to include in GDP (household work, to name one) are highly ideological. 

So everything economists do is ideological, and instead of trying to pretend to be objective, economists should embrace the ideological nature of their discipline and try to have an ideology of Good instead of one of Evil. How many times have I heard this one?

There's just a small problem with that. If you embrace ideology, people won't take your ideas seriously unless they buy into the same ideology. If you discard objectivity in favor of activism, people will know that you are not an honest broker of ideas and evidence. 

Sure, it's impossible to eliminate all ideology from science (any science!), but you should at least try. 

Luyendijk:

The same applies to inflation, since there is nothing neutral about the decision not to give greater weight to the explosion in housing and stock market prices when calculating inflation.

Lujendijk, you don't have any idea what that even means. You want to say that the value of your retirement portfolio going up is the same as the price of milk going up at the grocery store?? Seriously?? Or did you just hear from someone that QE was causing "asset price inflation", and that this was Dangerous and Bad, and so you decided to toss that out there??

Before you criticize technocracy for hiding its politics, you should at least have a working understanding of what those politics are. 

Anyway, this litany of critiques, repeated ad infinitum since the crisis, strikes me as mostly pretty lazy. There are good critiques out there. These are not they. 

That said, I like Luyendijk's idea of adding a general social science prize to the Nobel roster. Nobels are silly anyway, so why not have one for every field? While we're at it, how about one in math and computer science, and one in psych/neuro/cognitive science? And one in visual arts? And one in writing snarky point-by-point rebuttals in blog posts?

Theory vs. Data in economics

OK, I promised a more pompous/wanky followup to my last post about "theory vs. data", so here it is. What's really going on in econ? Here are my guesses.

First of all, there's a difference between empirics and empiricism. Empirics is just the practice of analyzing data. Empiricism is a philosophy - it's about how much you believe theories in the absence of data. You can be a pure theorist and still subscribe to empiricism - you just don't believe your theories (or anyone else's theories) until they've been successfully tested against data. Of course, empiricism isn't a binary, yes-or-no-thing, nor can it be quantitatively measured. It's just a general idea. Empiricism can encompass things like having diffuse priors, incorporating model uncertainty into decision-making, heavily penalizing Type 1 errors, etc.

Traditionally, econ doesn't seem to have been very empiricist. Economists had strong priors. They tended to believe their theories in the absence of evidence to the contrary - and since evidence of any kind was sparse before the IT Revolution, that meant that people believed a lot of untested theories. It was an age of great theoryderp.

That created a scientific culture that valued theory very highly. Valuable skills included the ability to make theories (math skill), and the ability to argue for your theories (rhetorical skill). Econ courses taught math skill, while econ seminars taught rhetorical skill.

Then came the IT Revolution, which dramatically reduced the costs of gathering data, transmitting data, and analyzing data. It became much much easier to do both high-quality empirical econ and low-quality empirical econ.

But at the same time, doing mediocre theory became easier and easier. The DSGE revolution established a paradigm - an example plus a framework - that made it really easy to do mediocre theory. Just make some assumptions, plug them into an RBC-type model, and see what pops out. With tools like Dynare, doing this kind of plug-and-chug theory became almost as easy as running regressions.

But Dynare and RBC didn't make it any easier to do really good theory. Really good theory requires either incorporating new math techniques, or coming up with new intuition. Computers still can't do that for us, and the supply of humans who can do that can't be easily increased.

So the supply of both good and mediocre empirics has increased, but only the supply of mediocre theory has increased. And demand for good papers - in the form of top-journal publications - is basically constant. The natural result is that empirical papers are crowding out theory papers.

But - and here comes some vigorous hand-waving - it takes some time for culture to adjust. Econ departments were slow to realize that these supply shifts would be as dramatic and swift as they were. So they focused too much on teaching people how to do (mediocre) theory, and not enough on teaching them how to do empirics. Plus you have all the old folks who learned to rely on theory in a theory-driven age. That probably left a lot of economists with skill mismatch, and those people are going to be mad.

At the same time (more hand-waving) the abruptness of the shift probably creates the fear that older economists - who review papers, grant tenure, etc. - won't be able to tell good empirical econ from mediocre. Hence, even empirical economists are quick to police the overuse of sloppy empirical methods, to separate the wheat from the chaff.

Now add two more factors - 1) philosophy, and 2) politics.

People have a deep-seated need to think we know how the world works. We have a very hard time living with uncertainty - most of us are not like Feynman. When all we have is theory, we believe it. We hate Popperianism - we recoil against the idea that we can only falsify theories, but never confirm them.

But when we have both facts and theory, and the two come into a local conflict, we tend to go with the facts over the theory. The stronger the facts (i.e. the more plausible the identification strategy seems), the more this is true.

The data revolution, especially the "credibility revolution" (natural experiments), means that more and more econ theories are getting locally falsified. But unlike in the lab sciences, where experiments allow you to test theories much more globally, these new facts are killing a lot of econ theories but not confirming many others. It's a Popperian nightmare. Local evidence is telling us a lot about what doesn't work, but not a lot about what does.

In physics it's easy to be a philosophical empiricist. As a physics theorist, you don't need to be afraid that the data will leave you adrift in the waters of existential uncertainty for very long. Physics is very non-Popperian - experimental evidence kills the bad theories, but it also confirms the good ones. In the early 20th century, a bunch of experimental results poked holes in classical theories, but quickly confirmed that relativity and quantum mechanics were good replacements. Crisis averted.

But that doesn't work in econ. A natural experiment can tell you that raising the minimum wage from $4.25 to $5.05 in New Jersey in 1992 didn't cause big drops in employment. But it doesn't tell you why. Since you can't easily repeat that natural experiment for other regions, other wage levels, and other time periods, you don't get a general understanding of how employment responds to minimum wages, or how labor markets work in general. Crisis not averted.

So philosophical empiricism is far more frightening for economists than for natural scientists. Living in a world of theoryderp is easy and comforting. Moving from that world into a Popperian void of uncertainty and frustration is a daunting prospect. But that is exactly what the credibility revolution demands.

So that's probably going to cause some instinctive pushback to the empirical revolution.

The final factor is politics. Theoretical priors tend to be influenced to some degree by politics (in sociology, that's usually left-wing politics, while in econ it tends to be more libertarian politics, though some left-wing politics is also out there). A long age of theoryderp created a certain mix of political opinions in the econ profession. New empirical results are certain to contradict those political biases in many cases. That's going to add to the pushback against empirics.

So there are a lot of reasons that the econ profession will tend to push back against the empirical tide: skill mismatch, the limitations of natural experiments, and the existing mix of political ideology.

Of course, all this is just my hand-waving guess as to what's going on in the profession. My guess is that econ will be dragged kicking and screaming into the empiricist fold, but will get there in the end.

A bit of pushback against the empirical tide

There has naturally been a bit of pushback against empiricist triumphalism in econ. Here are a couple of blog posts that I think represent the pushback fairly well, and probably represent some of the things that are being said at seminars and the like.

First, Ryan Decker has a post about how the results of natural experiments give you only limited information about policy choices:

[T]he “credibility revolution”...which in my view has dramatically elevated the value and usefulness of the profession, typically produces results that are local to the data used. Often it's reasonable to assume that the "real world" is approximately linear locally, which is why this research agenda is so useful and successful. But...the usefulness of such results declines as the policies motivated by them get further from the specific dataset with which the results were derived. The only way around this is to make assumptions about the linearity of the “real world”[.] (emphasis mine)

Great point. For example, suppose one city hikes minimum wages from $10 to $11, and careful econometric analysis shows that the effect on employment was tiny. We can probably assume that going to $11.50 wouldn't be a lot worse. But how about $13? How about $15? By the time we try to push our luck all the way to $50, we're almost certainly going to be outside of the model's domain of applicability.

I have not seen economists spend much time thinking about domains of applicability (what physicists usually call "scope conditions"). But it's an important topic to think about.

Ryan doesn't say it, but his post also shows one reason why natural experiments are still not as good as lab experiments. With lab experiments you can retest and retest a hypothesis over a wide set of different conditions. This allows you to effectively test whole theories. Of course, at some point your ability to build ever bigger particle colliders will fail, so you can never verify that you have The Final Theory of Everything. But you can get a really good sense of whether a theory is reliable for any practical application.

Not so in econ. You have to take natural experiments as they come. You can test hypotheses locally, but you usually can't test whole theories. There are exceptions, especially in micro, where for example you can test out auction theories over a huge range of auction situations. But in terms of policy-relevant theories, you're usually stuck with only a small epsilon-sized ball of knowledge, and no one tells you how large epsilon is.

This, I think, is why economists talk about "theory vs. data", whereas you almost never hear lab scientists frame it as a conflict. In econ policy-making or policy-recommending, you're often left with a choice of A) extending a local empirical result with a simple linear theory and hoping it holds, or B) buying into a complicated nonlinear theory that sounds plausible but which hasn't really been tested in the relevant domain. That choice is really what the "theory vs. data" argument is all about.

Anyway, the second blog post is Kevin Grier on Instrumental Variables. Grier basically says IV sucks and you shouldn't use it, because people can always easily question your identification assumptions:

First of all, no matter what you may have read or been taught, identification is always and everywhere an ASSUMPTION. You cannot prove your IV is valid...

I pretty much refuse to let my grad students go on the market with an IV in the job market paper. No way, no how. Even the 80 year old deadwoods in the back of the seminar room at your job talk know how to argue about the validity of your instruments. It's one of the easiest ways to lose control of your seminar. 

We've had really good luck placing students who used Diff in diff (in diff), propensity score matching, synthetic control, and even regression discontinuity. All of these approaches have their own problems, but they are like little grains of sand compared to the boulder-sized issues in IV.

He's absolutely right about the seminar thing. Every IV seminar degenerates into hand-waving about whether the instrument is valid. He doesn't mention the problem of weak instruments, either, which is a big problem that has been recognized for decades.

Now, Kevin is being hyperbolic when he categorically rejects IV as a technique. If you find a great instrument, it's really no different than regression discontinuity. And when you find a really good instrument, even the "deadwoods" in the back of the room are going to recognize it.

As for IV's weakness in the job market, that's probably somewhat due to the fact that it's been eclipsed by other methods that have not been around as long as IV. If and when people overuse those methods, it's highly probable that people will start making a lot of noise about their limitations. And as Ed Leamer reminds us, there will always be holes to poke.

Anyway, these posts both make good points, though Kevin's is a little over-the-top. Any research trend will have a pushback. In a later, more pompous/wanky post, I'll try to think about how this will affect the overall trend toward empiricism in econ... (Update: Here you go!)

Is the EMH research project dead?

Brad DeLong:

[I]t is, I think, worth stepping back to recognize how very little is left of the original efficient market hypothesis project, and how far the finance community has drifted--nay, galloped--away from it, all the while claiming that it has not done so... 

The original EMH claim was...[y]ou can expect to earn higher average returns [than the market], but only by taking on unwarranted systematic risks that place you at a lower expected utility... 

[But f]inance today has given up any preference that the--widely fluctuating over time--expected systematic risk premium has anything to do with [risk]...It is very, very possible for the average person to beat the market in a utility sense and quite probably in a money sense by [buying portfolios of systematically mispriced assets].

DeLong cites the interesting new paper "Mispricing Factors", by Robert Stambaugh and Yu Yuan. The paper puts sentiment-based mispricing into the form of a traditional factor model.

Is DeLong right? Is the Efficient Markets research project dead?

Well, no. Models that explain time-varying risk premia (really, time-varying excess returns) as the result of time-varying utility are far from dead. The finance academia community doesn't use these models exclusively, but they are still very common. Probably the most popular of these is the "long-run risks" model of Bansal and Yaron (2004), which relies on Epstein-Zin preferences to produce time-varying risk aversion. As far as I am aware, lots of people in finance academia still consider this to be the best explanation for "excess volatility" (the time-series part of the EMH anomalies literature). In a different paper from around the same time, Bansal et al. claim that this approach can also explain the cross-section of expected returns.

(Note: As Brad mentions in the comments, Epstein-Zin preferences are different from Von Neumann-Morganstern expected utility. It represents a departure from the standard model of risk preferences, but not from the core idea of the risk-return tradeoff.)

So the idea of explaining asset returns with funky risk preferences is not dead by any means. But this literature does seem to have diverged a bit from the literature on factor models.

As soon as multifactor models like Fama-French started coming out, people pointed out that they weren't microfounded in economic behavior. There was no concrete reason to think that size and value should be associated with higher risk to the marginal investor. EMH-leaning supporters of the models - like Fama himself - waved their hands and suggested that these factors might be connected to the business cycle, and thus possibly to risk preferences. But in the end, it didn't really matter. The models seemed to work - they fit the data, so practitioners started using them.

But since factor models aren't explicitly connected to preferences, there's no reason not to simply treat apparent mispricings as factors in a factor model. Really, the first example of this was "momentum factors". But the new Stambaugh and Yuan paper takes this approach further. From their abstract:

A four-factor model with two "mispricing" factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four- and five-factor alternative models...The mispricing factors aggregate information across 11 prominent anomalies...Investor sentiment predicts the mispricing factors...consistent with a mispricing interpretation and the asymmetry in ease of buying versus shorting. Replacing book-to-market with a single composite mispricing factor produces a better-performing three-factor model.

Stambaugh and Yuan take the "mispricing factors" approach further than in the past, by looking at limits to arbitrage and at investor sentiment. Limits to arbitrage and investor sentimennt are microfoundations - they are an explanation of mispricing factors in terms of deeper things in the financial markets. In other words, Stambaugh and Yuan aren't just fitting curves, as the momentum factor people were. This is behavioral finance in action.

Now this doesn't mean that the EMH research project is dead. First of all,  Stambaugh and Yuan still have to compete with papers by Bansal and other people working on the EMH research project. Second of all, increased attention to the "mispricing factors", or decreases in the institutional limits to arbitrage, may make them go away in the future. Third, risk-preference-based factors may still coexist with mispricing factors. And fourth, even if the mispricing factors are robust, the EMH is still a great jumping-off-point for thinking about financial markets.

So I think the rise of mispricing factors doesn't really signal the death of the EMH research project. What I think it signals is that finance researchers as a group are open-minded and eclectic, unwilling to restrict themselves to a single paradigm. Which I think is a good thing, and something econ people could stand to learn from...

Whig vs. Haan

If you want to understand Whig History, just look at the difference between the traditional European and the Disney versions of The Little Mermaid (spoiler alert!). Up until the end, they're pretty much the same - the mermaid dreams of love, and makes a deal with the evil witch, but she fails to get the prince to kiss her, and as a result she forfeits her life to the witch. In the European version, the mermaid dies and turns into sea foam, her dreams dashed. In the American version, however, the mermaid and the prince simply stab the witch in the chest with a broken bowsprit, and everyone lives happily ever after.

I think this difference is no coincidence. Around 1800, history had a structural break. Suddenly, the old Malthusian cycle of boom and bust was broken, and living standards entered a rapid exponential increase that is still going today. No wonder Americans love the Hollywood ending. In an economic sense, that's all we've ever really known. 

So Whig History - the notion that everything gets better and better - overcame Malthusian History. But there's another challenge to historical optimism that's much less easy to overcome. This is the notion that no matter how much better things get, society is fundamentally evil and unfair. 

I know of only one good name for this: the Korean word "Haan". (It's often spelled "Han," but I'll use the double "a" to avoid confusion with the Chinese race, the Chinese dynasty, and the Korean surname.) Wikipedia defines Haan thus:

Haan is a concept in Korean culture attributed as a unique Korean cultural trait which has resulted from Korea's frequent exposure to invasions by overwhelming foreign powers. [Haan] denotes a collective feeling of oppression and isolation in the face of insurmountable odds (the overcoming of which is beyond the nation's capabilities on its own). It connotes aspects of lament and unavenged injustice. 

The [writer] Suh Nam-dong describes [haan] as a "feeling of unresolved resentment against injustices suffered, a sense of helplessness because of the overwhelming odds against one, a feeling of acute pain in one's guts and bowels, making the whole body writhe and squirm, and an obstinate urge to take revenge and to right the wrong—all these combined."... 

Some scholars theorize the concept of [Haan] evolved from Korea's history of having been invaded by other neighboring nations, such as Han China, the Khitans, the Manchu/Jurchens, the Mongols, and the Japanese.

Though Korean writers claim that Haan is a uniquely and indescribably Korean experience, there seem to be parallels in certain other cultures. A number of Koreans have told me that "Korea is the Ireland of the East," comparing Korea's frequent subjugation to the domination of Ireland by England. 

Now, I am hugely skeptical of cultural essentialism. I doubt Haan is either unique to certain cultures or indelible. In fact, I bet that economic progress will drastically reduce it. There are signs that this is already happening - young Koreans are much, much less antagonistic toward Japan than the older generation.

But in a more general sense, Haan seems to describe an undercurrent of thought that runs through many modern, rich societies. You see it, for example, in leftist resistance to Steve Pinker's thesis that violence has decreased hugely. Pinker brought huge reams of data showing that violent crime and war have been in a long-term decline for centuries now. Leftist critics respond by citing anecdotal examples of war, atrocity, and injustice that still exist. 

This seems like a Haan view to me. The idea is that as long as examples of serious violence exist, it's not just incorrect but immoral to celebrate the fact that they are much more rare and generally less severe than in past times. 

Actually, talking about Pinker can often draw out what I think of as Haan attitudes. I was talking about Pinker to a friend of mine, a very sensitive lefty writer type. Instead of citing ISIS or the Iraq War as counterexamples, she talked about the problem of transphobia, and how "trans panic" legal defenses were still being used to excuse the murder of transsexual people. I checked, and this has in fact happened once or twice. My friend presented this as evidence that - contra Pinker - the world isn't really getting better. Injustice anywhere, under Haan thinking, invalidates justice everywhere else.

Another example of Haan is Ta-Nehisi Coates' view of history. The subheading of Coates' epic article, "The Case for Reparations," is this:

Two hundred fifty years of slavery. Ninety years of Jim Crow. Sixty years of separate but equal. Thirty-five years of racist housing policy. Until we reckon with our compounding moral debts, America will never be whole.

Now unless Coates gets to write his own subheadings, he didn't write those words. But they accurately sum up the message of the piece. The idea is that these wrongs against African Americans cause a moral debt that need to be repaid. It's not clear, of course, how the debt could be repaid, or what "reparations" actually would entail. But what's clear is the anti-Whig perspective. Progress does not fix things. The fact that Jim Crow was less horrible than slavery, and that redlining was less horrible than Jim Crow, and that today's housing policy is less horrible than redlining, does not mean that things are getting better. What matters is not just the flow of current injustice, but the stock of past injustices.

Haan presents a vision of stasis that is different from the Malthusian version. By focusing on the accumulated weight of history instead of the current situation, and by focusing on the injustices and atrocities and negative aspects of history, it asserts that the modern age, for all its comforts and liberties and sensitivity, is inherently wrong.

And Haan asserts that the world will remain wrong, until...what? That's usually not clearly specified. For Korean Haan theorists, it's a vague notion of "vengeance." For Coates, it's "reparations". For leftists, it's usually a revolution - a massive social upheaval that will overthrow all aspects of current power, hierarchy, and privilege, and make a new society ex nihilo. The details of that revolution are usually left a bit ambiguous.

But the vagueness and ambiguity of the imagined deliverance doesn't seem to be a big problem for most Haan thinking. What's important seems to be the constant struggle. In a world pervaded and defined by injustice and wrongness, the only true victory is in resistance. Ta-Nehisi Coates expressed this in an open letter to his son, when he wrote: "You are called to struggle, not because it assures you victory but because it assures you an honorable and sane life."

Haan thinking presents a big challenge for Whig thinking.

Whig History didn't have much trouble beating the old Malthusian version of history - after a hundred years of progress, people realized that this time was different. But Haan thinking presents a much bigger challenge, because progress doesn't automatically disprove Haan ideas. Making the world better satisfies Whigs, but doesn't remove the accumulated weight of history that fuels Haan. 

Nor can all instances of injustice be eliminated. It will never be a perfect world, and the better the world gets, the more each case of remaining injustice stands out to an increasingly sensitive populace. One or two cases of "trans panic" murder would barely have merited mention in the America of 1860. But precisely because there has been so much progress - precisely because our world is so much more peaceful and so much more just now than  it was then - those cases stick out like a sore thumb now. So Whig progress makes Haan anger easier, by raising people's expectations.

There's also the question: Should Whigs even want to defeat the Haan mentality? After all, if we trust in the inevitability of progress, it may sap our motivation to fight for further progress. Optimism can lead to complacency. So Haan resentment might be the fuel that Whigs need to see our visions fulfilled.

But Haan carries some risks. Massive social revolutions, when they happen, are capable of producing nightmare regimes like the USSR. With a few exceptions, the kind of progress Whigs like is usually achieved by the amelioration of specific ills - either by gradual reform, or by violent action like the Civil War - rather than by a comprehensive revolution that seeks to remake society from scratch. In other words, as one might expect, Whig goals are usually best achieved by Whig ends.

As a character would always say in a video game I used to play, "I am a staunch believer in amelioration."

In any case, I personally like the Whig view of the world, and I want to see it triumph. The idea of a world that gets better and better is appealing on every level. I don't just want to believe in it (though I do believe in it). I want to actually make it happen. And when I make it happen, or when I see it happen, I want to feel good about that. I want to savor the victories of progress, and the expectation of future victories, rather than to be tormented by the weight of unhappy history that can never be undone. I want to be able to think not just about the people around the world who are still suffering from deprivation, violence, and injustice, but also about the people who are no longer suffering from these things.

To me, the Whig view of history and progress is the only acceptable one. But Haan presents a stern challenge to that view - a challenge that Whigs have yet to find a way to overcome.


Update: Thabiti Anyabwile, writing in The Atlantic, says similar things in reference to Coates' writings.

"Loan fairness" as redistribution

I've noticed an interesting desire, especially on the political left, to want to use loans as a means of redistribution. The idea is that lenders should be willing to make loans to poor people when the risk-return tradeoff is worse than for loans to rich people. This could mean, for example, loaning money to high-default-risk poor borrowers at the same interest rate as to low-default-risk rich borrowers. Or it could mean extending loans to poor people whose perceived default risk would previously have prevented them from getting loans. The notion that this is "fair" - or that lenders "owe" it to poor people to give them favorable lending terms - pervades such works as David Graeber's Debt: The First 5000 Years.

A more recent example is Cathy O'Neil's recent post on Big Data and disparate impact in lending:

Did you hear about this recent story whereby Facebook just got a patent to measure someone’s creditworthiness by looking at who their friends are and what their credit scores are? They idea is, you are more likely to be able to pay back your loans if the people you’re friends with pay back their loans... 

[This] sounds like an unfair way to distribute loans... 

[In the neoliberal mindset], why would anyone want to loan money to a poor person? That wouldn’t make economic sense. Or, more relevantly, why would anyone not distinguish between a poor person and a rich person before making a loan? That’s the absolute heart of how the big data movement operates. Changing that would be like throwing away money. 

Since every interaction boils down to game theory and strategies for winning, “fairness” doesn’t come into the equation (note, the more equations the better!) of an individual’s striving for more opportunity and more money. Fairness isn’t even definable unless you give context, and context is exactly what this [neoliberal] mindset ignores. 

Here’s how I talk to someone when this subject comes up. I right away distinguish between the goal of the loaner – namely, accuracy and profit – and the goal of the public at large, namely that we have a reasonable financial system that doesn’t exacerbate the current inequalities or send people into debt spirals. This second goal has a lot to do with fairness and definitely pertains broadly to groups of people.

I don't get the random swipe at "equations", but the rest all seems pretty clear, even if it is couched in vague terms like "context", "reasonable", and "pertains broadly to groups of people". The basic idea is simple: Society is more fair when lenders give poor borrowers favorable terms relative to rich borrowers.

Let's think about this idea.

One problem with the idea would be that following it might force lenders to accept negative expected returns, which would drive them into bankruptcy. But let's assume for the moment that this doesn't happen - that lenders can lend to poor people and make lower, but still positive, profit margins overall. Loan "fairness" would then act as a subsidy from lenders to borrowers - a form of redistribution via a tax on loan-making businesses.

Another problem would be a more subtle version of the first problem - the implicit "fairness tax" on lenders might reduce the amount that they lend overall, and thus hurt the economy. This would be an example of the "leaky bucket" of taxation, in which we trade efficiency losses for welfare gains.

But let's ignore that issue. Let's think not about efficiency concerns, but only about the fairness of this type of redistribution.

Obviously fairness is a a matter of opinion, but there are some things we can clarify. Who are the recipients of "loan fairness" redistribution? Answer: Poor people who ask for loans.

Some poor people ask for loans because they have businesses to start, or for standard consumption-smoothing reasons. If these people are currently subject to borrowing constraints because of asymmetric information - in other words, if they can't get a loan because lenders don't realize they can and will pay it back - then these borrowing constraints will be ameliorated by "loan fairness" redistribution. That seems like a good (and fair) thing to me.

Other poor people ask for loans that they are unlikely to be able to pay back. This might be because they don't realize that their chances of repayment are low. Or it might be because they don't really intend to pay the loans back. Both of these groups of people will benefit from "loan fairness" redistribution.

One effect of implementing "loan fairness" redistribution would be an incentive for more people to join the latter group. Once poor people realize that society's desire for redistribution has given them the opportunity to get loans on more favorable terms, some poor people - it's not clear how many, but more than zero - will certainly take advantage of this by taking out a bunch of loans that they can't or don't intend to pay back.

A final group will be those poor people who don't ask for loans. Some will probably have ideas of morality that tell them to work hard, save money, and "neither a borrower nor a lender be". Others will think it unfair to request loans that they know they are unlikely to pay back. Others will simply not need to borrow that much. These groups of poor people will not benefit from "loan fairness" redistribution, because they will not ask for loans.

This introduces what I see as a source of unfairness. Poor people who are honest, and who refuse to borrow money that they know they can't pay back, will suffer compared to poor people who are dishonest and will just borrow as much as they can without any intention of returning the money. I think one could probably find some evidence of this kind of behavior among poor-country governments that borrow money and then ask for loan "forgiveness".

That seems clearly unfair. But there also seems to be another source of borderline unfairness here. Poor people whose moral values prevent them from asking for loans will be disadvantaged relative to poor people who have no moral problem asking for loans. Morality-based redistribution sounds a little iffy to me in the fairness department.

So purely in terms of the fairness of "loan fairness" redistribution - without even talking about efficiency concerns - I see some big problems with the idea of opportunistically redistributing money to only those poor people who are willing to walk into a lender's office and ask for a loan.

A more intuitively fair method of redistribution might simply be to tax rich people and give the money to poor people. Crazy idea, I know.