Sunday, November 29, 2015

Why teach kids macro at the intro level?

I've been writing some posts about Econ 101 (post 1, post 2, post 3). The basic theme is that kids need to learn a lot more evidence at the intro level, including methods. One response has been that it's actually very hard to teach kids even the simplest methods like OLS. At best, it would take a lot of time, and a one-semester intro course is just not long enough.

That got me thinking: What are the kids doing in the second semester of a year of intro economics? At a lot of schools, they're taking intro macro, often called Econ 102. I used to teach that class at Michigan, actually. And to be honest, I'm starting to think that this class is not really necessary. I think econ departments should think seriously about turning 102 from a macro class into a data/econometrics class.

Why should undergrads learn macro in their first year of econ? If they go on to be econ majors they can easily start out with intermediate macro and not miss anything important. If they just take the first-year econ sequence and then go into the business world, what do they really need to know?

In terms of growth theory, they might as well know the Solow model, so they can understand that capital accumulation by itself won't be a sustainable source of economic growth. Really, the Solow model is just a convenient way of teaching growth accounting, introducing ideas like capital, labor, human capital, and total factor productivity. And it's the one time in intro econ where you use a differential equation, so that could be useful for general math skill. Other than that, there's not really much growth theory an intro student needs.

How about business cycle theory? When kids go into the business world, it will probably help to know the standard Milton Friedman, New Keynesian, AD-AS, accelerationist Phillips Curve theory of monetary policy. That doesn't mean the standard theory is right (maybe Neo-Fisherian theory is better!), but since most people in the business world and at central banks sort of think it's right, kids will benefit from knowing it. It's easy and quick to teach to 101 students, since AD-AS fits right into the supply-and-demand graph stuff they're doing anyway. And if you want to mention RBC, you can just take the AD-AS graph and draw a vertical AS curve.

That's all I can really think of, and it's only about two weeks of material.

We have a lot of macro theories, but none that really work well unless you pick your data set very carefully and squint very hard. We have some methods for gathering evidence, but none that are very satisfying, and none that are simple enough for most intro level kids to understand.

And to make it worse, most of the macro theories that economists take halfway seriously are too hard for intro kids, so they end up learning silly stuff like Mundell-Fleming and Keynesian Cross that no one even halfway believes. Do we want kids going out in the business world and making deals as if interest rates will eventually equalize across all countries? God, I hope not.

So devoting 50% of the first-year econ sequence to macro just seems like a giant waste to me. We tend to think of macro and micro as symmetric things, but really "micro" is a lot bigger and more general than "macro". It affects a lot more policy questions, it has a lot more abundant and reliable evidence, it has a lot more interesting theoretical methodologies (game theory!), and it is more directly relevant to what students will eventually encounter in the business world.

So here's my new proposal for the first-year intro econ sequence. Replace useless macro with useful micro empirics. Either:

A) make 101 about theory and 102 about micro evidence, and stick Solow and AD-AS into 101, or

B) make 101 and 102 both predominantly micro (with Solow and AD-AS thrown in), and intersperse theory and evidence while stretching the sequence over 2 semesters.

And just kill the all-macro 102 course. It's not really doing anyone any good. It's kind of a barbarous relic.


1. On Twitter, Matt Yglesias says that econ probably has too much prestige tied up in macro to ditch the intro macro class. Maybe that's true. But I wonder if intro macro might now be generating negative prestige for the profession. Since the crisis there have been millions of words written in the media about how macro is bunk, macroeconomists don't know anything, etc. Killing intro macro might actually be saving the field some embarrassment, because a lot of those 102 theories really are obvious bunk, and most of the rest have taken a beating since 2008.

2. Some people (in the comments and on Twitter) have suggested that simply teaching kids the meaning of GDP, inflation, etc., and how these things are measured, could fill a whole semester. My response is: Maybe, but why go looking for ways to fill a whole semester? It sounds to me like status quo bias - because we've always taught an intro semester called "macro", we had better go find some "macro"-y stuff to teach. Sure, learning about growth accounting and NIPA calculations and whatever is cool. But there's a whole bunch more super duper useful stuff they could be learning instead: data analysis! Data analysis is becoming more and more important in econ, and more and more important in the business world. We're doing students a disservice by not teaching it in intro classes, and if we're going to correct that, something will have to make way. And I think the best "something" is macro.

Saturday, November 28, 2015

Econ 101 and data (reply to David Henderson)

I wrote a post for Bloomberg View about how Econ 101 needs more empirics (a favorite hobbyhorse of mine). They titled it "Most of What You Learned in Econ 101 is Wrong", which was a catchy but inaccurate title, since the word "wrong" is often unhelpful in describing scientific theories. For example, in the post, when writing about minimum wages, I wrote:
That doesn't mean the [Econ 101] theory is wrong, of course. It probably only describes a small piece of what is really going on in the labor market.
Sometimes you test a theory by looking at policy experiments, and what you find is that the treatment effect is in the direction the theory predicts, but the fit is poor - the percent of the variance explained is small. Does that mean the theory is "right", because the treatment effect is in the expected direction? Or does it mean the theory is "wrong", because the fit is poor? 

The answer, of course, is that "right" and "wrong" are not very descriptive, helpful adjectives in this situation. 

Anyway, there's the question of what to teach kids. Personally, I think that you should teach kids empirics no matter how good your theories are. High school physics and chem classes teach simple theories that are amazingly good at explaining a lot of real phenomena, but they also make sure to include lab experiments, so that kids can see for themselves that the theories work. And those are high school kids; college kids will be even more capable. There's no reason a college econ student shouldn't learn how to run regressions in 101.

But I think this becomes even more important when Econ 101 theories have poor fit. People tend to confuse treatment effects with goodness of fit, so if you teach kids a bunch of theories with poor fit but which get the sign of the treatment effect right, the kids will leave class thinking that these theories explain a lot more of the world than they really do.

This distinction is what some critics of my Bloomberg View post don't seem to get. For example, David Henderson writes:
In other words, in most cases there is a small, presumably negative, effect on employment. And presumably in the other cases there is a large effect. How, exactly, does this contradict the claims that Mankiw makes and that many of us teach in our equivalents of Econ 101? It doesn't.
In this case, the theories that Econ 101 books (like Mankiw's) teach tend to get treatment effects of the right sign - minimum wage hikes of the typical size probably do have a (very small) negative effect on employment. When Henderson says that the evidence doesn't "contradict" the theory, he means that the theory gets the sign of the treatment effect right.

The problem is that by emphasizing theory so much, and by relegating evidence to some brief asides, Econ 101 textbooks (and classes) will tend to trick kids into thinking that the theories have better fit than they do. When you make people learn a theory in detail, I think they naturally tend to believe that the theory has strong empirical fit unless they see evidence to the contrary. 

My other example was welfare. Studies show that the effects of the implicit tax rates in welfare programs like the EITC are very small. That's consistent with the relatively small Frisch elasticity of labor supply found in most micro studies. Even when you get welfare programs with very large implicit tax rates (100%!), the effect is generally not as big as you might expect (with 100% implicit tax rates, you'd expect AFDC to leave income unchanged, when in fact it does boost it somewhat). That implies that welfare affects labor supply through channels other than implicit tax rates and lump-sum payments. For example, Moffitt's survey of theory and evidence on traditional (TANF and AFDC) welfare programs discusses the idea of "welfare stigma". That's an idea that is difficult to explain with an Econ 101 type theory. But it may be important in practice. Thus, it is an idea that can only really be presented by looking at the evidence. (Note that this is a reason welfare programs are probably worse than the labor supply effects would imply!)

Now Mankiw doesn't disregard evidence, and Henderson gives an example of the way that Mankiw presents it:
Although there is some debate about how much the minimum wage affects unemployment, the typical study finds that a 10 percent increase in the minimum wage depresses teenage employment [by] between 1 and 3 percent.
Evidence is given, but it is relegated to a brief aside. The kids don't see the data for themselves. They don't learn how to work with it. They don't learn how the studies tested what they tested. They don't learn how to go verify for themselves how useful econ theories are.

To these kids, econ theories must seem like received wisdom. Even evidence, when presented only as a brief aside with no understanding of methodology, must also seem like received wisdom. Again and again, I talk to econ students who complain that they are expected simply to swallow what they are taught - unlike in their science classes. College kids are smart, and many of them are skeptical. They grow up learning that "science is the belief in the ignorance of experts." That doesn't tend to sit well with the kind of "received wisdom" approach that almost every intro econ textbook takes. Nor should it.

So while I definitely don't want to pick on Mankiw - his books really are excellent, my personal favorites - I think that most intro econ textbooks use this "received wisdom" style of theory-centric education with only brief references to empirical findings. That tends to result in students who either A) believe too much in the power of the theories they learn, or B) disbelieve and distrust econ in general. I see a lot of examples of both (A) and (B). Both of those outcomes do a disservice to the world.

Friday, November 27, 2015

A big sweeping theory of modern history

Here's a Big Sweeping Theory that I've been toying with. There are lots of theories of the cycle of rise and decline of empires in the agricultural, premodern world. I'd like to create a parallel theory of low-frequency cycles (or, more accurately, long-term impulse responses to stochastic technology shocks) in the modern, industrialized world.

It's possible to see the convulsions of the World Wars and the Great Depression as a one-time event - part of the growing pains of the industrial revolution, not to be repeated. But what if some of the core features of those events are actually part of a cycle? Here's a sketch of how that cycle might work:

Phase 1: Technological Change. A huge burst of new stuff gets invented. Growth accelerates. 

Phase 2: Globalization. New tech and growth create new global supply chains. Trade and migration accelerate.  

Phase 3a: Inequality. New tech and globalization offer lots of opportunity for rich people to deploy their capital. New supply chains, products, and markets allow entrepreneurs to evade incumbents, vested interests, and governments. First movers make fortunes. Rich people deploy their wealth to restrain government attempts at regulation and redistribution, to keep the party going. Meanwhile, workers are forced to compete with foreigners and immigrants, and are also forced to pay the costs of reskilling in response to tech changes and globalization. Widespread inequality results.

Phase 3b: Cultural Change. New economic opportunities allow previously disempowered groups to gain power and status. Tech disrupts traditional family structures. Culture changes rapidly.

Phase 3c: Financialization. The need to finance new tech industries and new global supply chains expand the size of the finance sector. This results in large asset bubbles.

Phase 3d: Geopolitical Shifts. New supply chains and new tech mean some previously poor countries are now able to become rich. With wealth comes power. New great powers destabilize the geopolitical order.

Phase 4: Rise of Extremism. Economic inequality precipitates the rise of "leveling" (leftist) movements. Anger at cultural change and fear of competition with immigrants, mixed with displaced anger over inequality, precipitate the rise of reactionary (rightist) movements. Rightists and leftists feed off of each other, each portraying the other as an existential threat in order to frighten the populace into turning to the opposite extreme. Extremist politicians abuse veto points in political systems to paralyze governments and make countries effectively ungovernable.

Phase 5: Economic Slowdown. The collapse of a global bubble (from 3c) begins a protracted worldwide economic slowdown. For whatever reason - overhang of debt? extrapolative expectations? hysteresis? secular stagnation? some weird disruption to trade networks? - the economy does not recover quickly to previous growth rates. Because of extremist control of veto points, policy is unable to respond to the slowdown. Centrists on both the left and right are discredited and toppled. 

Phase 6: War. Extremists may fight each other in civil wars. Alternatively, geopolitical disruptions may lead to international conflict between new and incumbent powers. Extremists push their governments toward fighting external enemies, assassinating or toppling moderate leaders who refuse to fight. If a country is too weak to fight external enemies, or if no such enemies are close by, civil war results instead.

Phase 7: New Order. Out of the chaos and destruction of the wars emerges a new stable geopolitical order. Left-right extremist conflicts cause society to be exhausted by violence, and moderates slowly return to power. The exigencies of war cause governments to reestablish control over their economies, creating a new set of vested interests and protected incumbents. Inequality is dramatically reduced by destruction of wealth in wars. New incumbents provide a new "social model" that creates economic security for the masses.

This is basically a description of what happened in the late 19th and early 20th century, along with a number of assumptions about why it happened. Obviously there will never be enough data to confirm or refute this complex, slow, and sweeping of a theory - not in our lifetime, anyway. 

But it's interesting to think about recent events as possibly corresponding to this sort of cycle. Here's how the modern world fits into the pattern:

Phase 1: Technological Change. The IT revolution, computers, the internet, automation, mobile communication.

Phase 2: Globalization. The huge wave of global growth between 1990 and 2008. Globalized supply chains. A huge Latin American immigration flow into the U.S., and a huge Middle Eastern immigrant flow into Europe.

Phase 3a: Inequality. Rising income and wealth inequality everywhere. Stagnating wages in rich countries. An explosion in the number of billionaires. Soaring college tuition as workers desperately try to get skills. 

Phase 3b: Cultural Change. Greater economic opportunity and equality for women, due to the service economy. A rise in divorce and single parenthood, and a drop in marriage. Sex culture spreading via the Internet. The decline of religion.

Phase 3c: Financialization: The explosion of financial profits and output as percentages of the total.

Phase 3d: Geopolitical Shift: The rise of China and the recovery of Russia, and (most importantly) the de facto alliance between the two.

Phase 4: Rise of Extremism. The steady polarization of American politics. Skyrocketing use of the filibuster. The Tea Party. The debt ceiling crisis. Trump. Sanders. Fox vs. MSNBC. Le Pen. The British National Party. Syriza and Golden Dawn. The Zaitokukai. Campus anti-speech movements. Online wars between leftist "SJWs" and rightists (GamerGate, etc.). The normalization of the terms "fascist" and "socialist". Illiberalism on both sides of the political spectrum.

Phase 5: Economic Slowdown: The 2008 crisis and the Great Recession, the Euro crisis and the China slowdown and the emerging markets slowdown. 

Phase 6: War. Let's hope not...

I know this big sweeping theory, like all such theories, is untestable hand-waving and blatant overfitting. But it's kind of interesting, isn't it? And also disturbing.

Monday, November 23, 2015

Japanese promises (a reply to John Cochrane)

John Cochrane comments on a recent Bloomberg post of mine. In that post I wrote:
[I]nflation reduces the burden of debt. Japan’s enormous government debt represents the government’s promise to transfer resources from young people (who work and pay taxes) to old people (who own government bonds). Since Japan is an aging society, there are more old people than young people. That makes the burden especially difficult to bear. Young people also tend to have mortgages, the repayment of which is another burden. 
Sustained higher inflation would represent a net transfer of resources from the old to the young. That would increase optimism, and hopefully raise the fertility rate, helping with demographic stabilization.
John agrees that (unexpected) inflation is a partial debt default that has (among many other effects) the net effect of transferring real resources from the old to the young. But he believes this to be unfair, and also cruel:
[L]et us remember where debt actually comes from. The Japanese government borrowed a lot of money from people who are now old, when they were young. Those people consumed less -- they lived in small houses, made do with fewer and smaller cars, ate simply, lived frugally -- to give the government this money. The promise they received was that their money would be returned, with interest, to fund their retirements, and to fund their estates which young people will inherit. 
Noah is advocating nothing more or less than a massive government default on this promise, engineered by inflation. The words "default,"  "theft," "seizure of life savings," apply as well as the anodyne "transfer." I guess Stalin just "transferred resources." 
Yes, Japanese Baby Boomers did make real sacrifices in exchange for the promise of future transfers. Yes, inflation (or cutting pensions, or cutting health care spending) does represent a partial default on those promises. It does indeed represent seizure of life's savings. As for "theft", that's a legal term, but if you want, then sure.


Economics involves tradeoffs. I wish it didn't. I wish resources were infinite, but they're not. And sometimes promises can't be kept as easily as you thought they could be when you made the promise. Imagine - as a limiting case - that an entire generation of fifty million produces only one hundred children. The older generation made real sacrifices when they were young, in exchange for government bonds (and suppose the real resources they gave up were spent on useless bridges to nowhere). In order to keep its promise of resource transfer, the government must now pay back those bonds by taxing just one hundred people.

It's not going to happen, no matter how much people want it to happen. One hundred cannot pay back fifty million. Inflation or default will happen.

In Japan's case, the situation is not so extreme, but the principle is similar. The Boomers, who sacrificed real resources (much of which was indeed spent on bridges to nowhere) in exchange for government bonds, had very few children. Japan's population is shrinking by hundreds of thousands per year, and the rate of decrease is set to accelerate. Paying back the older generation will be very, very hard for those less numerous young people. And forcing the young people to make those payments may well cause them to have fewer kids, helping to perpetuate the problem.

Therefore, hard choices must be made. Resources must be allocated - not the way that Stalin did it, thank God, but in a way that will undoubtedly earn the resentment and disappointment of many honest hard-working citizens, and which will undoubtedly cause hardship for many who do not deserve it.

But if you feel the desire to moralize against this "theft", remember that when the promises were made, the younger generation was not yet able to vote. The seizure of the fruits of their labor, in the form of taxes, goes to pay for expenditures that were made without their consent.

In other words, one way or another, some cruel unfairness is going to happen in Japan. And I think our job is to minimize the cruelty and unfairness as best we can - to "spread the pain" as much as possible while minimizing the pain's overall size.

Some more Cochrane points:
Amazingly, to Noah (and the views he ably summarizes here) this "transfer" will "increase optimism." Hmm. Let's look at the evidence for that. We have seen many large inflations, which wiped out middle-class savings along with government debts. Those events have generally been regarded as economically, politically, and psychologically destabilizing tragedies, not FDR-fireside-chat "optimism"-raising sessions. No surprise that few societies have voluntarily signed up for such treatment as Noah recommends. I would be curious to hear of a single happy historical antecedent. (I mean that. Perhaps I am mistaken in my understanding of Noah's proposal. A successful example might correct me.)
The historical example I had in mind was the sustained high inflation between 1945 and 1955, which substantially reduced the debt that the U.S. had incurred during WW2.
How does a government default benefit young people anyway? It does so if a large amount of tax revenue is being used to pay interest or principal on the debt, and the default is accompanied by a large tax cut for young families. Not by the same level of taxes and increased government spending on more railway-to-nowhere stimulus projects.  Without tax cut, there is no transfer. Noah is strangely silent on the essential big tax cut aspect of his plan.
Let me be silent no more! Yes, tax cuts are the plan! Taxes are crushing the youth!!

Of course, given the large tax hikes that will be required to balance the Japanese budget if transfer payments to old people are not cut, even keeping taxes at their current level would constitute a tax cut. But yes, it's about tax cuts.
Quiz: Find in Japanese (or American) government finances the actual "promise to transfer resources from young people (who work and pay taxes) to old people." If you say "government bonds," you (like Noah) got the wrong answer. The right answer is Social Security, Medicare, and public employee pensions. If Noah wishes to reduce the "burden" of intergenerational transfers, no matter that governments have promised to make those transfers and people have planned their lives around them, the silence on these promises is deafening.
I think Japan should absolutely cut transfer payments to the elderly (I said so in this other post, and will say it again, and said it to the Ministry of Finance people when I met them the other day). The problem is that transfer payments are politically hard to cut, while monetary policy is (probably) much more out of the public eye.

But note that government bonds are another promise to transfer resources from young to old. It's not the wrong answer, it's just part of the total answer.
If the purpose is default, why not just advocate default? 
It's one option. But it's an incredibly extreme option, since it would cause lots of business failures, which would cause massive economic disruption. That would put the country in danger of a coup. Sovereign default is a last-ditch option, but I think it would be better than hyperinflation.
So, according to Noah, a self-induced hyperinflation to generate an economy-wide debt default is necessary
No! Hyperinflation is the worst sort of default, since it causes business failures. What I want is sustained moderate inflation of 4-6 percent.

Anyway, that should answer most of John's points. He describes me as having an "insouciant willingness" to upend the lives of millions. I think I'm anything but insouciant. The lives of millions are going to get upended one way or another - Japan's government has made promises that it can't keep. That's not my choice or my doing. I just want to help figure out ways to minimize the overall suffering and spread it around as fairly as possible.

Hopefully that does not make me Stalin.

Friday, November 20, 2015

Unlearning economics

"Just then the floating disembodied head of Colonel Sanders started yelling
Everything you know is wrong"
- Weird Al Yankovic

The problem with discovering how the world works by intuition alone is that the model space is just enormous. Humans are really really smart, but very rarely are we smart enough to just sit down and think about how the world might work and actually get it right. Our most spectacularly successful leaps of theoretical insight - Newton's Principia, Einstein's relativity stuff, Mendel's theory of inheritance - were all very closely guided by data. The general pattern was that some new measurement technology would be invented - telescopes, plant hybridization experiments, etc. - that would provide some new unexplained data. Then some smart theorists would come up with a new theoretical framework (paradigm?) to explain it, and the new framework would then also explain a bunch of other stuff besides, and so people would switch to the new theory.

How about econ, though? Auction theory - a big empirical success - seems like it came out of pure intuition (though that could just be my ignorance of history). But if econ is like natural sciences, then we should expect that sort of success to be very rare. Usually, theories developed from armchair intuition - no matter how mathematical - will be wrong, just because wrong theories outnumber right theories by such a huge margin.

Right now we're in the middle of an empirical revolution in econ, and - unsurprisingly - a ton of standard, common theories are just not matching reality very well. For example:

1. If you slap some quick supply-and-demand graphs on the board, it looks like minimum wages should harm employment in the short term. But the data shows that they probably don't

2. If there's any sort of limits to mobility, then simple labor demand theory says that a big influx of immigrants should depress the wages of native-born workers of comparable skill. But the data shows that in many cases, especially in the U.S., the effect is very small

3. A simple theory of labor-leisure choice predicts that welfare should make recipients work less. But a raft of new studies shows that in countries around the world, welfare programs barely reduce observable work effort.

4. Most standard econ theory doesn't assume the existence of social norms. But experiments consistently show that social norms (or morals, broadly conceived) matter to people. 

Again and again, standard ideas - the stuff that most of the undergrad kiddos learn in their Econ 101 classes - are being smacked down by the heavy hand of new data. We're slowly unlearning economics.

Of course, much of the new empirical literature will eventually prove to be non-replicable or poorly designed, but much of it will prove to be solid and reliable; generations of empirical economists will carefully replicate findings and try to extend them to other contexts to see how well they hold up. And the good results will hold up, and theories will be killed as a result.

(Ultimately, that's good for econ theory, since the usual pattern is for better data to produce better theories. And it means more work for econ theorists, since simple theories will be killed first, and the better newer theories will take a lot of effort to make - so there will be jobs and money for theorists. Still, I expect some theorists to complain, because making simple theories is easy and making useful theories is hard.)

But anyway, what this means is that Econ 101 courses around the country probably need an overhaul. New data is rapidly producing a raft of new theoretical facts that students should be learning. Teachers should still teach the simple, classic theories that the new facts are beginning to kill...but mainly as a way to show how data can tell us when we're wrong.

Update: Here's a follow-up Bloomberg post. Maybe Angrist and Mankiw should team up to write the Econ 101 textbook of the future!

Sunday, November 15, 2015

Gelman vs. Case-Deaton: academics vs. blogs, again

Case and Deaton, welcome to the blogs.

Prominent academics are often astonished at the rapidity with which the blogosphere occasionally pounces on and dissects their research findings. In this case, it happened to Case and Deaton, authors of a recent much-publicized study entitled "Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century." The pounce was done by Phil Cohen, and - most prominently - by Andrew Gelman

The TL;DR version is that rising mortality in some of the subgroups spotlighted by Case and Deaton was increased by a composition effect - the average age within the subgroups increased over the observation period, which pushed up death rates for the aggregated subgroups. If you remove the composition effect, the mortality increase among these groups was considerably less.

Anne Case responded with the consternation typical of researchers first encountering blog attacks:
Case said that she didn’t buy this argument. “We spent a year working on this paper, sweating out every number, sweating out over what we were doing, and then to see people blogging about it in real time — that's not the way science really gets done,” she said. “And so it’s a little hard for us to respond to all of the blog posts that are coming out.”
Academics are used to the cozy, staid world of academia. Responses are slow, polite, and vetted by third parties. Arguments happen in seminars, in office discussions, and at dinners. Disputes are resolved over a matter of years - when they are resolved at all. And never do intellectual adversaries take their case to the general public!

But academics are going to have to get used to blogs. The technological advances of the web have simply made it easier for crowds of outsiders to evaluate research in real time. How often that process produces the "wisdom of crowds", and how often it merely adds unhelpful noise, remains to be seen. Certainly we've seen the internet do both of those things at different times. But blog criticism of research looks like something that's here to stay, and academics whose work appears in the popular press will have to get used to it!

Blog discourse has some distinct advantages - above all, the speed of responses and the diversity of people who get involved in discussions. How often do you see two economists arguing with a sociologist and a political scientist/statistician? That's pretty cool! There is, however, a tendency for blog debates to become too antagonistic. 

I think Andrew Gelman's latest salvo against Case and Deaton falls into this category a bit. He is put out that Case and Deaton have, so far, refused to issue a public mea culpa about what he sees as a major gotcha. Gelman writes up what he thinks such a mea culpa should say, and includes these bits of snark:
Had it not been for bloggers, we’d still be in the awkward situation of people trying to trying to explain an increase in death rates which isn’t actually happening...We count ourselves lucky to live in an era in which mistakes can be corrected rapidly[.]
Gelman is dramatically overstating the importance of what he found! To say that the increase in death rates "isn't actually happening", first of all, is not quite right - Gelman's rough-and-ready composition adjustment removes all of the increase, but more careful examination shows that some portion of the increase remains.

Second, Gelman is kind of assuming that zero is the important benchmark for what constitutes an "increase". He makes sure to point out that the paper's main finding - that American white mortality increased a lot relative to various comparison groups - is not changed by the composition adjustment. But when he claims that the increase "didn't really happen", Gelman is saying that "increase" is an absolute rather than a relative term.

Andrew, you're a stats guy. You know full well that people analyzing time-series data detrend stuff all the time. Measuring increases relative to a trend is totally standard practice! 

So like many blog debates, this one ends up making a mountain out of a molehill. The composition effect was a useful and instructive observation, but it doesn't really change anything about the paper's result. And publicly demanding that the authors engage in an equally public mea culpa over such a non-issue is a little unrealistic. If it leads to rancor in the long term, that will be a shame.

I like what blogs have done for research, but I think we should work to make those discussions less about point-scoring and more about a cooperative, crowdsourced search for truth.

Friday, November 13, 2015

Black immigrants are upwardly mobile

The other day, I noticed something disturbing in a graph from a Brookings report on immigrant mobility:

Embedded image permalink

We see that Hispanics are strongly upwardly mobile from the first to the second generation. Asians are slightly upwardly mobile, but from a pretty high base. Those are both good news. But black immigrants, on average, appear to show downward mobility.

Why would black immigrants be downwardly mobile? I posed the question on Twitter. A smart person called Abraham Bloodshack immediately tweeted this to me:
generational effects? i.e., recent increase in African migration could mean second gen are all quite early in careers
That was smart. We'll follow up on that later. But first, let's review some possible explanations for the mobility disparity:

1. Household size decrease. 1st gen. African immigrant families are probably really big, since Africa is a super-high-fertility place in general, while 2nd gen. families probably have drastically lower fertility.

2. Cohort effect. Recent changes in immigration composition might account for the effect. The average age difference that Abraham Bloodshack mentioned is also a kind of cohort effect. Age differences would affect the black immigrant average much more than the Hispanic or Asian immigrant average if African immigrant families, like the typical African family, are extremely large.

3. Downward assimilation. With many immigrant groups we see the 2nd generation picking up a lot of "bad" behaviors - or at least "bad" for earning power - from their decadent rich-world peers. These include things like not getting married, sponging off parents, and getting involved in the underground economy. 2nd-generation black Americans might be especially susceptible to this sort of thing. (And yes, I know "downward" might be a loaded word; if you want to sponge off your parents and play League of Legends, more power to you.*)

4. Racism. Negative attitudes toward African-Americans might not apply to people with African or Carribean accents, but might be applied toward their more American-sounding kids. (Update: See this excellent comment for more.)

I did a bit of digging on the ol' internet, and turned up this Tyler Cowen post on the subject, from two years ago. Cowen links to two papers (paper 1, paper 2) by Alison Rauh, a Chicago econ PhD, now a research associate at Cornerstone. 

The papers look at personal income, so we don't have to worry about the household size issue. They find broadly the same average income decrease as the Brookings graph, though to a lesser extent. Rauh's first paper attributes the difference to "idleness", her word for "being out of the labor force". Conditional on having a job, 2nd-generation black Americans earn a lot more than 1st-generation - for men, 29 percent more. That's roughly comparable to the average Hispanic increase from the Brookings graph, but from a much higher base. But so many 2nd-generation black Americans are out of the labor force that the overall average income goes down!

That would seem to point to the "downward assimilation" story, perhaps with some racism mixed in. Tyler goes for downward assimilation:
I take this to be a “peer effects are really really important” paper, namely that many of the virtues of immigrant culture are swallowed as the second generation assimilates.  
But this isn't the whole story. In her second paper, Rauh looks at what happens when the generations are adjusted for age, as Abraham Bloodshack might have suggested doing. Here is what she finds:
Note, however, that the average second generation black is more than 8 years younger than the first generation immigrant. Since earnings increase steeply until the mid forties, column 5 uses inverse probability weighting to equalize the age distribution of the first and second generation. Now sons of black immigrants earn $3000 or 8% more than the average first generation black immigrant. The fraction of second generation blacks with a college degree is 35% and therefore 4 percentage point higher than those of the first generation...For women both of these trends seem to be even more pronounced (Panel B). The second generation, once adjusted to have the same age distribution as the first generation, has an earnings premium of $8,600 over native blacks, $6,700 over first generation, and $3,600 over whites.
Lesson: Always read through the papers, don't just skim the Abstract/Intro/Conclusion! 

So if we adjust for age, we see that black immigrants are upwardly mobile, in terms of both income and education. And that upward mobility is from a decently high base for income and a very high base for education. 

In other words, the Brookings graph tells us the wrong story! A lot of those 2nd generation black Americans are either in college, or just starting at the bottom of the career ladder. They will eventually make a lot more money. This is great news.

But although black immigrants are upwardly mobile, they are not as upwardly mobile as they should be. Rauh observes that high incarceration rates play a large part in the fraction of 2nd-generation black Americans not in the labor force. Marriage rates are also much lower. 2nd-generation men are also much less upwardly mobile than 2nd-generation women.

These facts all point to a cultural effect - societal racism and/or downward assimilation, in some combination. Black immigrants are thriving in our society overall, but it's in spite of some headwinds.

Anyway, let this be a lesson: Before you go looking for theories to explain a fact, make sure you've gotten the fact right in the first place!

* Haha, I'm kidding of course. League of Legends sucks.

Monday, November 09, 2015

Case-Deaton and the human capital debate

Everyone is talking about the Case-Deaton paper that shows an increase in mortality among American white people. Most people have noted that the increase is concentrated among less-educated whites. Here is the relevant excerpt from the paper:
The three numbered rows of Table 1 show that the turnaround in mortality for white non-Hispanics was driven primarily by increasing death rates for those with a high school degree or less. All-cause mortality for this group increased by 134 per 100,000 between 1999 and 2013. Those with college education less than a BA saw little change in all-cause mortality over this period; those with a BA or more education saw death rates fall by 57 per 100,000. Although all three educational groups saw increases in mortality from suicide and poisonings, and an overall increase in external cause mortality, increases were largest for those with the least education... 
The final two rows of the table show increasing educational gradients from 1999 and 2013; the ratio of midlife all-cause mortality of the lowest to the highest educational group rose from 2.6 in 1999 to 4.1 in 2013.
And here is the table:

This paper provides some hard data to corroborate a story we have been seeing elsewhere: College-educated Americans are significantly healthier in their personal, family, and social lives. To me this indicates that education has acted to partially innoculate Americans against the overall negative changes that are affecting our society.

This is interesting for the debate on whether education - particularly college - creates human capital or not. Evidence is mounting that college transforms people's lives in ways that are not directly related to natural ability. I suspect that more detailed regressions would find that the difference in social and personal health persists after controlling for income, SAT scores, etc.

Here is an NBER paper by David Cutler and Adriana Lleras-Muney that supports my conjecture. I didn't find any other good-looking recent papers on the topic with a quick Google Scholar search. From the abstract:
There is a large and persistent association between education and health...The education ‘gradient’ is found for both health behaviors and health status, though the former does not fully explain the latter. The effect of education increases with increasing years of education, with no evidence of a sheepskin effect. Nor are there differences between blacks and whites, or men and women...We then consider differing reasons why education might be related to health. The obvious economic explanations – education is related to income or occupational choice – explain only a part of the education effect. We suggest that increasing levels of education lead to different thinking and decision-making patterns. The monetary value of the return to education in terms of health is perhaps half of the return to education on earnings[.]
The Cutler and Lleras-Muney paper also reviews some natural-experiment studies indicating that the effect is causal for pre-college education (though here's one paper they didn't cite, showing no effect). The authors also attempt to control for a large number of personal characteristics that might cause people to be both healthier and more likely to go to college, but find that this only marginally attenuates the relationship. They conclude that it is highly likely that the effect of education on health is, in fact, causal. (If they're right, that's in addition to whatever effect college has on income.)

A tendency toward healthy behavior is a powerful and important form of human capital. It is not at all clear that this kind of human capital can (or will) be created by MOOCs, self-study, or other forms of online learning that are being touted as replacements for college. In fact, right now it looks like the health-related human capital boost from college is all that is holding it together for our upper middle class.

Sunday, November 08, 2015

"Panics and Bubbles" reading list

Tony Yates offers his reading list on "Panics and Bubbles".

The list has some good stuff on it. Diamond-Dybvig, Geanakoplos, and Cogley and Sargent especially stand out. There's also some good stuff on how "expectation shocks" can cause economic fluctuations - for example, Angeletos and Werning, Farmer, etc.

There were one or two incongruous things. (Money search? What does money search have to do with panics and bubbles??) But mostly good stuff to read.

However, there's also a lot that I think Tony left out. His list skews heavily toward macro and money-based models, usually with rational expectations but with a few learning-based models thrown in. It is also mostly made up of theory papers, with little empirical work. This is understandable, since macro theory is what Tony does. But there are a lot of good non-macro and empirical papers out there on the topic of "Panics and Bubbles". For example:

Harrison and Kreps (1978) model how overconfidence can lead to asset price volatility. Scheinkman & Xiong (2003) follow up. Barber and Odean (2001) provide some evidence.

In fact, there are a bunch of papers, both theoretical and empirical, on heterogeneous beliefs and their role in asset pricing. Here is a good overview by Xiong. Here is a classic 1994 paper by Morris and a classic 1993 paper by David Romer. Here is a good, short, simple discussion paper by Barsky, talking about the Japanese bubble.

Heterogeneous beliefs are closely connected with learning. Tony mentioned some learning-based macro models, but I'd also point people to this elegant 1999 paper by Zeira on how learning can produce bubbles even in very simple settings.

Noise trader models are another important strain of the literature. Start with DeLong et al. (1990) and the various offshoots of that paper. Another very important paper is Abreu & Brunnermeier (2003). Mendel and Shleifer (2012) is yet another good one. Then check out Brunnermeier and Nagel (2004) on hedge funds and the technology bubble for some evidence.

A mostly forgotten but incredibly interesting strand of research was the "information cascades" literature, that models bubbles as herd behavior. Check out papers by Avery and Zemsky (1998), Chari and Kehoe (2003), and Park and Sabourian (2009).

In terms of direct tests of bubbles, and why these are so hard to do, you'd want to check out the classic 1980s literature on variance bounds tests (here is a great brief overview), as well as the literature on other kinds of bubble tests (surveyed here by Refet Gurkaynak).

And of course, check out the surveys on bubbles and crashes by Brunnermeier and by Scherbina and Schlusche.

In terms of the interactions between financial market disturbances and recessions, in addition to Kiyotaki-Moore and Bernanke-Gertler, you should check out more recent papers by Curdia and Woodford, and Christiano and Rostagno. I'm mildly surprised those or others like them didn't make Tony's list.

So there you go. I left out stuff like emerging market crashes and capital flight. I also left out economic history (Kindleberger), non-mathematical treatises (Minsky), and various "heterodox" ideas like Austrian theory.

But I think this is a good start. I think this list also shows that much of the finance theory literature has developed in parallel to the macro literature, with incomplete communication between the two. To some degree I suppose that's inevitable.

Tuesday, November 03, 2015

Big TFP data mystery! (Probably solved!)

NOTE: Mystery probably resolved! See update below. Here was the original post, for posterity:

While recently complaining about the overselling of static-efficiency policies, I asserted that rich countries have all grown at about the same long-term rate, despite decade-long divergences. I was talking, of course, about Total Factor Productivity, which at long horizons should be determined by technology.

I had been under the impression that over the last three decades or so, the rich countries had all experienced similar rates of TFP growth. My source for that was the OECD's time-series on multifactor productivity (another name for TFP). Here is a chart of those OECD productivity numbers since 1985:

As you can see, most rich countries grew their TFP at the same average rate, consistent with the idea that TFP mostly measures technology in the long term, and that technology spreads rather easily between rich countries. A few countries, like Korea, Ireland, and Finland, did much better over this period, and a few countries, like Italy, Spain, and Portugal, lagged behind. But most rich countries were clustered along the same basic line. The U.S., UK, France, and Germany (highlighted on the graph) all stayed very close to each other.

But I now see that FRED has its own TFP numbers for various countries, taken from the Penn World Tables. And here's what happens when I plot the TFP numbers for the U.S., UK, France, and Germany over the same time period (1985-2011):


The U.S. and UK lines match up as before, but the Germany and France lines are wildly, totally different! In fact, according to the Penn World Tables, Germany's TFP actually steadily declined from the mid-80s to 2011! 

What on Earth is going on here?? Obviously the two measurement methodologies are very different. So I tried to track down the source of the discrepancy, and I found some interesting stuff. 

First of all, it turns out that the Penn World Tables, currently assembled by a team of economists from UC Davis and the University of Groningen, have undergone substantial revisions to their methodology in recent years. They switched to a new growth accounting method developed by Francesco Caselli in the early 2000s (which I plan to study in detail when I get the chance). As Antonio, and Marek Jarociński pointed out in 2010, these revisions were enough to substantially change the results of all cross-country growth regressions. Simon Johnson, William Larson, Chris Papageorgiou, Arvind Subramanian criticized the new Penn methodology, and suggested possible changes. 

Meanwhile, the OECD methodology for calculating TFP has some questions surrounding it as well. To get TFP you need measures of labor and capital inputs. The OECD uses a pretty textbook method for doing this - simply stick in the raw estimates for the dollar values of labor and capital. But when they tried using another database called EU-KLEMS that tries to adjust for "quality" of inputs, they found totally different numbers.

I am not experienced enough in growth accounting to wade into these disputes in a substantive manner; it would take me at least a month of serious study to be able to say with any confidence which of these methodologies I believe most. The real takeaway here, though, is that TFP measurements are HIGHLY suspect, and will continue to be so for the foreseeable future.

That is bad news for most of modern macroeconomics, both on the growth theory and on the business cycle theory side of things. If differing methodologies for measuring labor and capital inputs diverge by this much, it means that any series you use probably has tons of stuff in it that it shouldn't have. That means that changes in the series at business-cycle frequencies - the good old TFP shocks of RBC models, which are also part of "kitchen sink" DSGE models like Smets-Wouters - are also unreliable. Basically, all those "shocks" are as likely as not to just be noise. That's probably true whether you compare across countries or look only at one country.

So this is a very pessimistic finding, and a huge challenge for the growth accounting field. Hopefully, a meeting of the brightest minds will get to the bottom of the problem and arrive at a consensus solution. If not, it means that any model that relies on measures of aggregate TFP, or factor inputs in general, is unreliable until the accounting problems are worked out.


Robert Inklaar of the University of Groningen contacted me and explained what was wrong! The most recent version of the Penn World Tables, version 8, did not take into account changes in averaged hours worked in some countries. Also, it used a Barro-Lee data source that apparently had some questionable data on trends in education. Inklaar says that the next version of the PWT, version 9, will fix the problems, and until it comes out, to use OECD data.

Well, I am mostly relieved. It's not really a methodology disagreement (except for the Barro-Lee education data). All of macro does not have to be scrapped, just yet. :-)

Thanks to Robert Inklaar for helping me out!

...But the growth economists I talked to about this mystery all expressed deep skepticism about these TFP data sets in general...

Monday, November 02, 2015

Growth vs. static efficiency

I have a new Bloomberg piece where I criticize John Cochrane, and conservatives in general by extension, for selling static efficiency policies as "growth" policies. The title is not the best (and the picture they use of John is also not the best; sorry about that). But the point is one I've really wanted to make for a long time:
Most of the so-called growth policies Cochrane and other conservatives propose don't really target growth at all, just short-term efficiency...Cochrane sells us on the need for growth policies by citing the undeniable benefits of long-term economic growth...But most of the policies Cochrane recommends are most certainly not things that would increase the growth rate for decades on end!...[S]uppose we cut taxes...the deadweight loss goes away...It provides a one-time bump, but nothing more...The same is true of most regulation.
You can read the whole thing here.

Now, Cochrane's piece is a very good one, as far as conservative policy manifestos go - it is non-polemical, thoughtful, and well-researched. It includes not just standard Republican planks like tax cuts, but also some things like increased spending on research. I think Cochrane would be a great chief economic advisor for the Rubio administration.

Nor is he trying to be dishonest here. Cochrane is a good guy. The focus on "growth", and the tendency to sell static-efficiency policies with paeans to the benefits of multi-decade compounding, is just a bad habit - a holdover from Reagan days. But nevertheless, I think it's sloppy. Policies to boost static efficiency should be able to stand on their own merits; they don't need to be oversold like this.

Sunday, November 01, 2015

Robert Lucas in biology class

Back in August, a bunch of people were talking about Paul Romer and Bob Lucas and history of macro and stuff like that. Somehow I missed this post, where Brad DeLong dug up a Bob Lucas memoir and made fun of Lucas' college biology class exploits. For reference, here's a longer version of Lucas' story:
The only science course I took in college was Natural Sciences II - a biology course. We read a modern anatomy text, and also selections from Darwin, Mendel, and others... 
[T]here was nothing spooky about Mendel’s genetic theories. They were clear, they made some kind of sense (though there was nothing molecular in our Nat Sci II readings), you could work out predictions that would surprise you, and these predictions matched interesting facts. We did a classroom experiment with fruit flies, focused on eyes, and pooled the results. Our assignment was to write up the results in a lab report and compare them to predictions from a Mendelian model. I had not enjoyed the actual lab work but I liked writing the report and spent the better part of my weekend on it. It was the first time I can recall ever working out the predictions of a scientific theory from its basic principles and testing these predictions against experimental evidence. 
On Sunday evening, my friend Mike Schilder asked to copy [my report on the fruit fly experiment]. I agreed...Mike came back in half an hour, and told me: “This is a good report, but you forgot about crossing-over.” “Crossing over” was a term introduced to us to describe a discrepancy between Mendelian theory and certain observations. No doubt there is some underlying biology behind it, but for us it was presented as just a fudge-factor, a label for our ignorance. I was entranced with Mendel’s clean logic, and did not want to see it cluttered up with seemingly arbitrary fudge-factors. “Crossing over is b---s---,” I told Mike. In fact, though, there was a big discrepancy between the Mendelian prediction without crossing over and the proportions we observed in our classroom data, too big to pass over without comment. My report included a long section on experimental error, describing the chaotic scene that generated the data and arguing that errors could have been large enough to reconcile theory and fact. I handed it in as written. Mike, on the other hand, took my report as it stood, except that he replaced my experimental error section with a discussion of crossing over. His report came back with an A. Mine got a C-, with the instructor’s comment: “This is a good report, but you forgot about crossing-over.” 
I don’t think there is anyone who knows me or my work as a mature scientist who would not recognize me in this story. The construction of theoretical models is our way to bring order to the way we think about the world, but the process necessarily involves ignoring some evidence or alternative theories - setting them aside. That can be hard to do - facts are facts - and sometimes my unconscious mind carries out the abstraction for me: I simply fail to see some of the data or some alternative theory. This failing can be costly and embarrassing to me, but I don’t think it has any effect on the advance of knowledge. Others will see the blind spot, as Mike did with crossing-over, keep what is good and correct what is not.
DeLong makes fun of Lucas for rejecting chromosomal crossover. which is indeed a real thing, and the discovery of which won a Nobel in 1933. It does seem kind of lazy, actually. Even before Wikipedia, it wouldn't have been hard to go grab an advanced textbook and look up how chromosomal crossover works. Lucas is unhappy that it's presented as a fudge-factor, but by the time you're an undergrad you should be too old to depend on the teacher for 100% of your knowledge. If something isn't adequately explained to you, go look up how it works! 

Lucas says that this episode demonstrates a professional weakness of his - the tendency to want to over-simplify theory in order to "bring order" to the world. But I think it demonstrates something slightly different and more worrying: selective empiricism.

In his bio class, Lucas did an experiment on fruit fly inheritance. After the results didn't completely agree with the predictions of basic Mendelian theory, he attributed the discrepancies to experimental error - basically, to measurement noise. Fine (if slightly lazy). But then he takes the experimental result as support for the Mendelian theory, despite the presence of all that experimental error!

If the experimental situation was such a "chaotic scene," then any seeming agreement between Mendelian theory and the lab results might well have been an experimental error. So if college-age Lucas had really been an empiricist, he would have said "This experiment was such a chaotic scene that it provides only very weak support for Mendelian theory." Instead, he concludes that the experimental setup was reliable enough to support the theory that makes "some kind of sense" to him, but too unreliable to indicate the presence of additional phenomena like chromosomal crossover.

In other words, Lucas' conclusion from the experiment relied strongly on his own priors. Or if you prefer a frequentist term, he protected the null hypothesis. That has little to do with oversimplification; it's just a manifestation of confirmation bias. You pick the theories that make sense to you, and believe in them until the data decisively refute them.

But hey, who among us didn't have silly ideas in college?

Saturday, October 31, 2015

Rap is capitalist

The economics of rap lyrics would be an interesting subject for a pop econ book.

When I was a kid, I barely listened to rap, and most of what I knew was West Coast "gangsta rap." To me, gangsta rap was basically a form of chivalric fiction -  a glorification of the honorable, violent lifestyle of warriors in an anarchic society. It was all just "Mine enemies besmirched my honor, so I smote them down with the strength of my good right arm." Medieval knights were basically just gangsters, after all, so it makes sense that they'd have similar romantic myths.

I also was dimly aware of protest rap ("Fuck tha Police", Public Enemy, KRS-One, etc.) and 80s dance rap (a variant of goofy 80s dance music).

But as I got older and started to listen to more rap, I noticed one theme that was overwhelmingly common, and seemed to be getting more dominant: the rags-to-riches story. A huge amount of rap these days, and for at least the last ten years, has lyrics that are a variation on: "I was poor, then I made high-quality entertainment products, and now I am rich!"

For example, here's an excerpt from "Started From the Bottom," by Drake:
I done kept it real from the jump
Living at my mama's house we'd argue every mornin' nigga,
I was trying to get it on my own
Working all night, traffic on the way home
And my uncle calling me like "Where ya at?
I gave you the keys told ya bring it right back"
Nigga, I just think it's funny how it goes
Now I'm on the road, half a million for a show
This theme is absolutely ubiquitous. In the late 90s and early 2000s, around the time I started listening to more rap, it seemed to be totally replacing gangsta rap as the dominant lyrical message.

One interesting thing is how overwhelmingly capitalist this theme is. A number of (white) lefty humanities students I meet are quite enamored of rap, viewing it as a form of protest against the structural injustice of the capitalist system. But barely any of that has been popular for many years now. The overwhelming majority of the mainstream popular rap music from the last decade and a half has been about working hard, taking risks, reaping financial rewards, and enjoying a money-driven status-conscious consumerist lifestyle. In other words, a total and utter embrace of the capitalist dream. Of course, the successful business exploits of rappers themselves are now well-known; the capitalist dream goes way beyond music-making.

Modern rap also puts the lie to the idea, popular in right-wing media, that rap encourages a culture of poverty. That was true of gangsta rap - even if he amasses money and power, a gangster is expected to stay in his community and remain true to the lifestyle of the streets (much like the ideal of noble poverty in chivalric fiction). But modern capitalist rap is about hard work and risk-taking in the pursuit of prosperity - exactly the kind of values conservatives ostensibly want people to have. Ludacris, whose music O'Reilly has repeatedly failed to recognize for the satire that it is, even has a song advocating Randian selfishness.

So I think both lefties and conservatives get modern rap fundamentally wrong. It's just Horatio Alger, updated for a wealthier, more liberal, mass-media-driven age.

But rap is about the culture of Black America, and therefore it is about scarcity. You can't have rags-to-riches without the rags. Black America is much poorer than the rest of the country, and is therefore a world defined by the daily experience of scarcity; it's a world where every constraint always binds. That makes for some interesting economics.

For example, the drug trade figures prominently in rappers' stories of how they survived before getting rich. The standard rapper autobiographical tale has the rapper selling drugs until his music career takes off. Usually, this involves taking large risks, since it involves operating outside of the protection of the law. This, of course, demonstrates many of the unintended negative consequences of government prohibition of commodities.

Also, a world of scarcity is a world where transaction costs are too high for many kinds of market institutions to function. For example, equity markets. Here is an excerpt from Future's "Where Ya At":
Where your ass was at, dog, when I was in the Pyrex?
Where your ass was at, dog, when I was drinking Hi-Tech?
Where your ass was at, dog, came through the projects?
Where your ass at we keep that fully loaded contracts?
and also:
Where your ass was at when I was trapping in the stove?
Had to struggle to get where I'm at and sell dope
The song is addressed to someone who wants some kind of unspecified favors from Future now that he's a rich, successful musician, but who refused to help Future when he was a poor, struggling chemical manufacturer. Unfortunately, given the lack of formal equity markets, the dispute over just how much the person helped Future must be resolved by extra-legal means. Informal purchasing contracts, barter, and other economic workarounds also make frequent appearances in rap lyrics.

I don't think I'm reading too much into these songs, either; rappers themselves are obviously acutely aware of the importance of good formal economic institutions.

Rap lyrics paint a picture of how government has influenced the economy of African-American society, especially via the War on Drugs. An economic niche has been carved out and reserved for poor Americans. That niche offers the promise of a middle-class income, but at the price of horrible risk to life and limb. It has encouraged informal marketplaces with weak institutions, leading to high transaction costs and numerous market failures.

No wonder rappers are so proud at having escaped that situation and made it into the regular economy! I know I would be. Perhaps our politicians should listen to more rap music.

Monday, October 26, 2015

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:

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):

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.


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.