Sunday, January 24, 2016

Book Review: "Economics Rules"


As y'all know, I love a good book about econ philosophy-of-science. Economic Rules: The Rights and Wrongs of the Dismal Science, by Dani Rodrik, is my favorite book in this vein to come out in quite some time.

I gave Rodrik's book a glowing blurb in Bloomberg View, and it was well-deserved. But actually I do have one big problem: the first two chapters. These chapters consist entirely of Rodrik's very general thoughts on economic models, and what they should and shouldn't be used for. 

The problem with these early chapters is the audience. Economists will already have heard most or all of these philosophical ideas. Non-economists, in contrast, will probably not understand what they're reading, because the chapters are written in sweeping, general terms, and move very quickly between a number of difficult topics that each require a good deal of background knowledge. So these early chapters suffer the same issue as Karthik Athreya's Big Ideas in Macroeconomics - they fall into an uncanny valley, too old-hat for economists but too inside-baseball for non-economists. 

So I fear that many readers may get turned off early and not finish the book. Which is a shame, because the latter two thirds of it are really excellent, and should be read carefully by economists and non-economists alike.

Rodrik really shines when he talks about his own field, development econ. He gives a vivid recounting of the Washington Consensus - why it was adopted, why it went wrong, and how the mistakes could have been avoided. The story of the Washington Consensus provides the perfect backdrop for Rodrik's ideas about what economists and models should do. The episode demonstrates why it's important for policy advisors to look at a bunch of alternative models, and use personal judgment to choose which ones to use as analogies for reality. It is the perfect example of the "models as fables, economists as doctors" worldview that Rodrik is trying to lay out.

In fact, I wish more of the book had been about trade and development economics. Rodrik's blog posts and articles on these topics are always top-notch, and when you look at how Rodrik has struggled with these topics, you easily understand why he thinks about modeling and policy recommendation in the way that he does.

Anyway. Enough nitpicking. It's Rodrik's book, not my book. 

Chapters 3 through 6 of  Economics Rules alternate between Rodrik's criticisms of his colleagues and his responses to outsiders' criticisms of the econ profession. On all of these points, I find myself pretty much in agreement with him. It's very difficult to sum them all up (so go read the book), but here's a few that really stood out:

* Rodrik notes that economists tend to present a much more simplistic, pro-market stance to the public than they show in their research and behind closed doors. He attributes this to economists' widespread belief that the public is biased against markets. Rodrik suggests that economists give the public a little more credit, and change their public stance to reflect the true diversity of their views. That sounds right to me.

* Rodrik strongly criticizes the New Classical and RBC macro theorists of the 1980s. He essentially accuses them of trying to create a grand unified Theory of Everything, which in econ is just never going to work. That sounds about right. 

* Rodrik tries to counter the criticism that economists ignore things like norms. In doing so, he basically says "The evidence shows that norms often matter, and economists pay attention to the evidence." This demonstrates Rodrik's deep respect for data and evidence. He doesn't even mess with the question of "theory vs. data" - to Rodrik, the two always go together. I admire that a lot.

* Rodrik does say one thing that kind of bothers me. He says that economics, unlike science, doesn't replace bad models with better ones - it just makes new models, expanding the menu of models that policy advisors have to choose from. That seems very true in practice. You rarely hear economists talk about models being "disproven", "falsified", or "rejected". But to think that any model is appropriate in some situation seems wrong to me. There are always many more models than real-life situations. Most of those models are just never applicable or useful to any real-world phenomenon. I think economists could stand to recognize this more.

Anyway, this is a great book, and a quick read. Get it and read it if you haven't.

Thursday, January 21, 2016

101ism


Economics is a big, big tent. Within econ there are many schools of thought. One of these is what I call "101ism" (I didn't invent the name but I forget who did). 101ism is the set of ideas that most people take away from Econ 101.

We all know basically what 101ism says. Markets are efficient. Firms are competitive. Partial-equilibrium supply and demand describes most things. Demand curves slope down and supply curves slope up. Only one curve shifts at a time. No curve is particularly inelastic or elastic; all are somewhere in the middle (straight lines with slopes of 1 and -1 on a blackboard). Etc.

Note that 101 classes don't necessarily teach that these things are true! I would guess that most do not. Almost all 101 classes teach about elasticity, and give examples with perfectly elastic and perfectly inelastic supply and demand curves. Most teach about market failures and monopolies. Most at least mention general equilibrium.

But for some reason, people seem to come away from 101 classes thinking that the cases that are the easiest to draw on the board are - God only knows why - the benchmark cases.

You see examples of this all the time in the media and in discussions with people who have taken some econ, but I want a concrete example, so I will pick on a friend of mine: Josh Barro. Josh is a wonderful human being (and once had me on MSNBC to discuss men's fashion), and he is quite smart as well. But today I did notice him displaying a bit of 101ist thought in a Twitter discussion:


Josh, I apologize for picking on you! This is only one small example out of many, many I see all the time. It was just a convenient one. I promise to buy you a beer as recompense.

Anyway...

First of all, notice that "immigration has a big negative effect on native-born wages" - what Josh calls "econ 101 models" is actually a much stronger result than 101 teaches! In 101, demand curves may slope down, but they need not slope down very much. If demand curves are very elastic (i.e. flat), then a large positive supply shock will not decrease price very much. In other words, if labor demand is elastic, then we'd expect to see a very small negative impact of immigration on native-born wages - which is, in fact, exactly what we see in study after study (survey paper 1, survey paper 2).

So a very small negative effect on wages is perfectly consistent with 101. The Card and other immigration papers are not inconsistent with 101 in the slightest. But 101ism demands that elasticities be somewhere in the middle (because slope 1 and -1 lines are easy to draw on a board), so effects are never supposed to be very small. 101ism says that moderate elasticity should be the benchmark, and very high or low elasticity is a puzzle that needs special explanation.

Now suppose we go beyond 101 itself, to 401. Now we're thinking about general equilibrium. In general equilibrium, a positive labor supply shock can induce a positive labor demand shock, so that wages go right back to where they were before. That demand response might come pretty quickly. If we go beyond 401 and think about things like variable capital utilization, then the demand response might come very quickly, so even the instantaneous effect of immigration on wages would be smaller than partial equilibrium analysis would suggest.

Why should partial equilibrium, rather than general equilibrium, be the universal benchmark? Just because general equilibrium is a bit harder to learn, does that mean that general equilibrium effects should be treated as puzzles in need of explanation? What about search models, models with monopolistic competition, etc.?

Anyway, this is my problem with 101ism. It treats certain theories as benchmarks even though they have no right to be. Which means that it treats lots of empirical results as puzzles even though they don't deserve to be.

People, simplicity does not equal generality.

So what is the antidote for 101ism? If 101 classes already include things like perfectly elastic and perfectly inelastic curves, monopoly, general equilibrium, and market failures, then what can educators do to prevent students turning into 101ists? My recommendation is the same as before: Put empirics in 101. Seeing results like Card's that contradict simple 101ist stories - but can be easily explained with 101 concepts - will force students to think about the fact that elasticities are not always moderate, that partial equilibrium is not always the whole story, that market failures sometimes exist, etc. etc. In other words, empirical results will aid in giving people a fuller, richer understanding of basic econ theory in all its versatility.

Sunday, January 10, 2016

So much for QE (guest post)


I thought it would be interesting to post a private-sector economist's views on macroeconomic policy. So here's a guest post by Gerard MacDonell, who was an economist at Point72 Asset Management, (previously SAC) from 2004 through 2015:


"So Much for the QE Stimulus"

Last month’s Press Release from the FOMC announcing the first rate hike in a decade contained a seemingly-innocuous and yet telling discussion of the interaction between interest rate and balance sheet policy.  It marked the end of false confidence in the efficacy of quantitative ease (QE), which can be traced to a technical error Ben Bernanke made while lecturing the Japanese on deflation in 1999.
The Committee expects that economic conditions will evolve in a manner that will warrant only gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run.  
…The Committee is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities and of rolling over maturing Treasury securities at auction, and it anticipates doing so until normalization of the level of the federal funds rate is well under way. 
The passages above were not a major departure or surprise to the markets, but they confirm that the Fed leadership has now abandoned its original story about how QE affects the economy and has conceded that the tool is weak.  If QE were strong, the balance sheet could not remain large even as the Fed promised to raise rates only gradually.

It has long been obvious that QE operated mainly through signaling and confidence channels, which wore off on their own without any adjustment in the size or composition of the Fed’s balance sheet. Accordingly, QE cannot be relied upon to provide much help in the next economic downturn, which means the Fed will have to tread carefully to avoid a return to the zero bound.

The story initially told by the Fed leadership starts with the claim that large scale asset purchases (LSAPs) reduce the term premium and expected returns in government securities, by removing default-free interest rate duration from the capital markets.  This is meant to encourage portfolio flows out of government securities and into corporate debt, equities and foreign currencies. And the resulting easing of financial conditions is supposed to stimulate spending to reduce unemployment, contain deflation risk and eventually push inflation back to target.

That story does not hold much water. The theoretical foundations supporting QE were invented – or really revived from the 1950s – in an effort to justify a program that had been resolved upon for other reasons.  LSAPs did not actually succeed in reducing the stock of government rates duration because they were fully offset by the fiscal deficit and the Treasury’s program of extending the maturity of the federal debt. And while the estimated term premium and bond yields did go down during the QE era of late 2008 through late 2014, they had a disconcerting tendency to rise while LSAPs were ongoing.  This latter point squares with contemporary finance theory but not with the 1950s-style portfolio balance channel asserted by the Fed, which presumes more durable segmentation than applies to US government securities.

There are still believers in the QE story, in both academia and the markets.  However, the Fed has abandoned the flock it once led.  If the leadership still believed the official story, it could not promise both to maintain the size of the balance sheet and raise rates at an historically slow pace.  That would deliver far too much stimulus, particularly with the economy now near full employment. The obvious way to square this circle to recognize that the Fed does not believe the story, which is an advance.

Peak QE gullibility seems to have been reached in the late summer of 2012, with Ben
Bernanke’s presentation to the Kansas City Fed’s monetary policy conference at Jackson Hole.  In that speech, the Chairman asserted that the first two rounds of LSAPs plus the maturity extension program (to that point) had reduced 10-year Treasury yields by 80 to 120 basis points.

Since these comments were made, further maturity extension and the third round of QE have raised the total stock of rates duration on the on the Fed’s balance sheet (measured in 10-year equivalents and as a share of GDP) by about 50%.

So assuming assuming a linear relationship between QE and yields, the estimated impact of the entire QE program would be a reduction in the 10-year Treasury yield of 120 to 180 basis points. That is a lot.   Moreover, according to the original story, little of this presumed stimulus would unwind without asset sales or a passive shortening of maturities, both of which have largely been excluded for now.

Roughly around the time of QE3, it became fashionable to measure quantitative ease in terms of a fed funds rate cut (below zero) that it effectively equated to. Thus was born – or again revived – the so called shadow fed funds rate.  In fairness to advocates of the concept, some of whom were Fed officials, the shadow rate was estimated with bond yields and was not just the result of an accounting exercise chopping presumed QE effects off the nominal funds rate.

Still, the fashion was to ascribe the negativity of the shadow rate largely to the LSAPs or what we call QE.  Estimates of the shadow funds rate at the conclusion of the LSAPs in late 2014 ranged from -2 to -5%, which meant -- if taken seriously – that the Fed would have a lot of wood to chop once the time to tighten policy had arrived.

Readers of this comment may recall those charts circulated by Wall Street showing the fed funds equivalent going deeply and shockingly negative after 2009. In retrospect, those charts are cringe-inducing and best forgotten.  It is a mercy that the Fed has participated in the forgetting. For those who do not want to forget, the estimated shadow rate has recently spiked to around the nominal funds rate, even without asset sales from the Fed’s balance sheet. Oops.

This raises the question of why the Fed initially promoted a story that so obviously would not stand the test of time.  We can imagine three possibilities, the third of which is the most speculative and, if true, the most interesting.

The first possibility relates to the first round of event studies, which measured the immediate effects on the term premium and bond yields of QE-related news.  The initial application of QE occurred in the context of financial crisis and unusually high market segmentation, even in Treasuries, so those event studies understandably found large effects.

Announcement effects are a poor measure of fundamental effects that will endure long enough to affect the economy, particularly when markets are functioning normally, as they roughly have since mid-2009.  The reason is that markets typically act more segmented in the short run than over time, and this is particularly the case in the market for government securities.  But smart and credentialed people argued otherwise and the FOMC may have been comforted by that.

The second possibility is that the Fed wanted to raise confidence in the markets and real economy and thus chose to communicate that it was wielding a new and fundamentally powerful tool, even if Fed officials had their own doubts.  Unlike in the case of the term premium and bond yields, there is compelling evidence that applications of QE led to durable changes in equity prices and inflation expectations that may have been somewhat stimulative.

It is best to lift confidence with tools that have a mechanical force and do not rely purely on confidence effects. But if such tools are not readily available, then it probably does not hurt to try magic tricks and pyrotechnics.

The problem looking forward is that people may not be so responsive to the symbolism of QE next time around.  After all, the Fed is now revealing its true or updated beliefs, which may be hard to cover back up come the next downturn.  Moreover, the Bank of Japan has got hold of QE, which raises the odds it will be properly discredited, if history guides.

The third possibility involves some “blue-sky thinking”, to steal a term Ben Bernanke used in his book, The Courage to Act.  It is possible, although unproven, that Bernanke and his colleagues in Fed circles were durably confused by Bernanke’s early and mistaken relation of the Quantity Theory to the efficacy of LSAPs.

He made this mistake most famously in his 2002 Helicopter Ben speech, but it is easier to identify in his 1999 essay lecturing the Japanese on how to escape deflation.  To motivate his recommendation of LSAPs and other stimulative measures the Japanese might take, Bernanke made the following points:
The general argument that the monetary authorities can increase aggregate demand and prices, even if the nominal interest rate is zero, is as follows: Money, unlike other forms of government debt, pays zero interest and has infinite maturity. The monetary authorities can issue as much money as they like. Hence, if the price level were truly independent of money issuance, then the monetary authorities could use the money they create to acquire indefinite quantities of goods and assets. This is manifestly impossible in equilibrium. Therefore, money issuance must ultimately raise the price level, even if nominal interest rates are bounded at zero. This is an elementary argument, but, as we will see, it is quite corrosive of claims of monetary impotence. 
There are a couple striking aspects of this passage.  For starters, Bernanke attempts to port the spirit of inevitability implicit in the Quantity Theory over to the idea of LSAPs. This is inappropriate because there is no quantitative aspect to the program, as Bernanke himself would later insist, while assuring us that QE would not be inflationary. But one must wonder if this misapplication of the Quantity Theory to LSAPs created in Bernanke and associates an excessive confidence in the efficacy of the program.  As late as 2002, he seemed to believe there was a sense in which simple logic implies LSAPs just had to work as a matter of “elementary” quantitative logic.

Separately and amazingly, Bernanke actually makes a technical error of economics when he claims that increments to the money stock, as he defines it, always have an infinite maturity.  A rise of the monetary base will indeed have infinite maturity if it driven by normal economic growth and the Fed successfully pursuing its inflation objective. In such a situation, gains of the monetary base will show up in higher currency in circulation and (to a lesser extent) a rise of required reserves.

However, that is not really relevant to the case for LSAPs. Increases of the narrow money stock driven by a surge in excess reserves to fund asset purchases designed to drive the economy out of liquidity trap do not have infinite maturity.  Again, Bernanke would later argue this point himself, and demonstrate it by paying interest on excess reserves, thereby by converting them from money to debt. Bernanke’s money injection actually had ZERO maturity.  Or more to the point, it did not even happen.

The only way LSAPs could be considered a quantitative operation would be if the scale of them communicated something about the tolerable inflation rate. But this was specifically excluded in 2012 when Bernanke and colleagues on the FOMC formalized 2% as the unchanged inflation objective.

The Fed leadership has come a long way from believing that QE had something to do with the power of the printing press to a recognition that the program is a combination of an indirect and transitory rates signal, a confidence game, and a duration take out that probably achieved much less than was advertised. But at least the journey has been made, which has reduced the risk of a contractionary policy error.


Updates

Tony Yates responds.

Friday, January 08, 2016

How the left talks about race


These days American public discourse tends to feel like a giant continuous race war. Well, I guess we had that "national conversation about race" that Bill Clinton always said we needed. Oops. But anyway, I guess I might as well wade in.

The right's way of talking - and thinking - about race is just totally poisonous. The conservative movement has been recruiting working-class whites and Southern whites for decades by using anti-black dog-whistles, and by promoting the idea that government spending equals white-to-black racial redistribution. More recently, the Trump campaign has ridden - and possibly spurred - a wave of anti-immigrant xenophobia. In the online social science discussion, racial theorists like Steve Sailer have gained an inordinately huge amount of currency among right-leaning intellectuals. Then there are the Twitter Nazis and the Reddit Nazis (and let us speak no more of them). So it is basically now impossible to talk to people on the right about race in a rational way.

So people on the left are the only ones I can talk to. And the left isn't perfect in the way it talks about race (who is?), so I have some criticisms to make. And of course any criticisms I make will inevitably be viewed as "tone policing". To a lot of people, it makes no sense to complain about lefty foibles when the far more scary right is beating down the doors. But that's really all I can do, because there's just no talking to the right about this. Instead of convincing rightists to switch sides, a more realistic goal is to improve leftist racial discourse in order to make the left more appealing to the mass of mushy centrist Americans.

This is the thinking behind a recent Kevin Drum article on "political correctness". Drum is worried that thought-policing by lefties is driving people into the Trump camp. 
And let's be honest: We liberals do tend to yell racism a little more often than we should. And we do tend to suggest that anyone who likes guns or Jesus is a rube. And the whole "privilege" thing sure does get tiresome sometimes. And we do get a little pedantic in our insistence that no conversation about anything is complete unless it specifically acknowledges the special problems of marginalized groups. It can be pretty suffocating at times. 
For the most part, I don't mind this stuff...[but] Donald Trump is basically telling ordinary people that ordinary language is okay, and since that's the only language they know, it means they feel like they can finally talk again.
Liberals are excessively reluctant to "yell racism" and excessively deferential to deeply embedded structures of white supremacy...obviously it's a big country and there are some people out there who are calling something racist when it isn't. But the notion that on the whole this is a big social problem strikes me as a figment of white people's imagination.
I think neither writer captures the breadth, complexity, and subtlety of race relations in America today - how could they? But to the extent that I kinda-sorta agree with one of these people, I agree with Drum. Which is to say, Yglesias is focused on what is fair in his own value system and assessment of reality, while Drum is focused on the political effects of certain styles of discourse. Yglesias is like the kid who goes up to a woman in the mall and says "You're fat!", and when his mom gasps "Why did you say that?!", responds "Because it's TRUE!!" 

(Confession: That kid was me.)

Here's a brief, encapsulated version of how I see lefty racial discourse in recent years. In the past, anti-racism efforts focused either on concrete policies (segregation, redlining) or on individual attitudes (bigotry). But the concrete racist policies are mostly gone, and people have become very adept at hiding their bigotry when they want to. So lefties who want to eliminate racial inequalities have fewer obvious targets.

The response has been to focus on what Yglesias, employing the jargon of the day, calls "the deeply embedded structures of white supremacy". The idea is - I think - that patterns of racial inequality are supported by a diffuse and varied combination of hidden bigotry, stereotypes, subtly discriminatory attitudes, government policy, and the physical legacy of past injustices (de facto segregation, wealth inequality, etc.). That idea is correct enough. What's not as clear is how we should refer to those patterns, and - most importantly - how we should go about changing them.

Some lefties use the word "structure" to mean the pattern of inequality, while others use the word to refer to the diffuse combination of causes. Still others use the word to refer vaguely to social forces that they don't understand and have not thought about rigorously, but which they imagine must be complex, powerful, and probably directed by certain nefarious individuals. This last usage, which reminds me of how rebellious teenagers talk about "The System" or "The Man", is inevitably the most common...but hey, what do you expect?

The problem, I think, starts when left-leaning people take their idea of racist "structures" and start to apply it in the real world. How do you challenge or change a "structure"? You could try to remove policies that support continued inequality, or craft policies that try to redress the legacy of past injustices. Or you could take the lowest-cost option, which is simply to yell about "structural racism" a lot, to anyone who happens to be listening.

Naturally, I come in contact with a lot of folks who have chosen the latter option.

Declaiming against "structural racism" feels good. Racism is generally recognized as being a bad thing, and declaiming against bad things makes one feel righteous (I certainly feel that way). It also allows one to link up with like-minded people, making you feel like you have an army on your side and are not just shouting into a wilderness. 

But I think left-leaning people should think a little more carefully about the consequences of this approach. I think that it could end up pushing lots of non-committed Americans, whose hearts are in the right place, to the rightist camp.

Imagine a middle-aged, middle-class white man living in the suburbs. Let's call him Bob. Bob is not a racial bigot - he'd just as soon hire a black person as a white person, and he'd just as soon have a black neighbor as a white neighbor. He does not subscribe to Sailer-type racial theories, and is heavily skeptical of any racial stereotypes he encounters. He votes for the Democrats.

But Bob takes part in "racist structures". He pays lots of money to live in his mostly-white suburban neighborhood, not because he wants to live next to white people, but because he believes that the schools are high-quality and that the neighborhood is safe. He works in a company that disproportionately employs white people, because that company pays him a salary, and because he has not encountered bigotry there sufficient to make him think twice about working there.

So here is my worry. In his discussions with his Millennial kids, or on Facebook, Bob may be assailed as as enabler of "structural racism" or "white supremacy". More thoughtful, intelligent lefties may assail him because he participates in (and even benefits from) segregated housing and schooling. Less thoughtful, less intelligent lefties may simply view him as a target because he is white and middle-class (even though they themselves are also likely to be white and middle-class). Unable to identify or directly target the "racist structures" they know must exist, humans inevitably focus on doing what they know how to do - give other individual humans a hard time.

Bob's natural reaction, of course, will be something along the lines of: "What can I do? Can I be less racist than I already am? Am I expected to move my family to a poor black neighborhood? Am I expected to quit my job and join a communist revolution, dedicated to overthrowing and remaking society? What do these people want???"

In the end, Bob may simply conclude that he is a target - and will always be a target - because he is white. and because humans are inevitably drawn to the opponents of the people who are attacking them, Bob will drift slowly toward the right. He will nod approvingly when conservatives decry "political correctness". He will be just a little more irritated when the Oregon anti-government militia crazies are identified as "white people." He may even start to pick up just a little more on those Republican anti-black dog-whistles. Of course, this will only increase the degree to which he comes into conflict with lefties that he encounters, which will reinforce the cycle that pushes him inexorably to the right.

I view this as a bad outcome. No, people like Bob do not constitute a silent majority in the United States - middle-class white people are actually a minority. But they are a substantial minority, who are vulnerable to being taken in by the Donald Trumps and Ted Cruzes and Rush Limbaughs of this world. And if you think middle-class whites are the only people who might be pushed rightward by well-meaning lefty attacks on "structural racism", think again. Poor whites and rich whites are just as susceptible. And remember that more Hispanics are identifying as "white" as time goes on. Asians are probably safe from day-to-day harassment by angry white anti-racists...for now.

Anyway, this whole scenario of "Bob" was a conjecture - a fantasy. This is what I worry about happening. I see small and subtle signs of this everywhere, but that means little - I could simply be primed to believe that the world fits my fantasy. So please don't read this as a declaration that "this is what is happening in American racial discourse and American politics." Instead, read it as a caution about a negative scenario that I envision happening.

I think it is incumbent upon prominent left-leaning anti-racist writers - Jeet Heer, the folks at Gawker, etc. - to think about this possibility, and how this bad outcome can be insured against.

Thursday, January 07, 2016

The Data Revolution goes mainstream


My Bloomberg View colleague Justin Fox has written an excellent post publicizing the econ profession's shift from theory to empirics. Fox puts the Hamermesh data on publication percentages into a lovely Bloombergy chart:


By now this is an old story to people within the profession. But I think it's an important story to keep telling to the public, in order to increase people's trust of economists. 

People instinctively know that empirical sciences - fields where theories have to be tested by data in order to gain currency - are more reliable than ones based on pure theory. Seeing that economists are now checking their ideas carefully will make the public more confident that prevailing ideas were not simply accepted because of ideology or intellectual whimsy. This is also why I think colleges should start teaching empirics in Econ 101.

Of course, there's bound to be resistance to the popular narrative of the Data Revolution. In an earlier post I tossed out some possible reasons for resistance within the econ profession. Some of those are good reasons, and some are less good, but the people in the public discussion will probably have a much simpler objective function. Ideological free-market types believe that simple Econ 101 type theory supports their ideas. Empirical results, because they deal with an inevitably non-101 reality, threaten that nice clean little intellectual world that the ideological free-marketers have built.

So I predict that we'll see most of the public disapproval and skepticism of the Data Revolution - on Twitter, in the media, etc. - coming from folks with a strong free-market ideological bent. Though a bit will come from lefty types annoyed that it was data rather than Marxist hand-waving that ended up transforming economics.

What form will the public criticism take? At first, I expect to see a lot of people saying stuff like "without theory, data is useless," or "data doesn't speak for itself." This, of course, is trivially true. But the Data Revolution isn't actually about replacing theory with data, it's about checking theory with data. Empiricists aren't out there running batch-file regressions - they're doing local tests of theories. (In fact, they're probably doing too much structural modeling, even when it's only related to their study by the most tenuous of threads!)

The battle of ideas is really between A) those who think that theories should have to have empirical support before we believe them, and B) those who want to believe theories until proven otherwise. It's about the strength of priors, in some sense - science vs. theoryderp. The Data Revolution really is just as important as Justin Fox writes. It represents a true paradigm shift in econ.

Eventually, the simplistic rhetorical criticism will run out of steam, and people will start gunning for some famous empirical results. The idea will be to discredit one or two top studies, and imply that empirical econ in general is unreliable, like nutrition science or social psychology. Naturally, there will be some targets available for this sort of attack, since A) scientists make mistakes, and B) conditions in the economy change, so old results sometimes no longer hold. 

The most sophisticated attack, I predict, will be based on replication and publication bias. That criticism will be the most effective, since it's almost certainly true. Econ has terrible data management practices, and is just as subject to publication bias, p-hacking, and data mining as any field. 

But I think that in the end, empirical econ will benefit from these public attacks. Data management practices will improve, and meta-analyses will sort the reliable results from the ephemeral. Randomization and control procedures will get better, and statistical analysis will become more sophisticated. Credibility will increase and increase.

In the end, I predict that the Data Revolution will not be a fad or a flash in the pan. Humans like believing in wanky theory when data isn't available, but when data is available, they want to have some confirmation that theories actually work. Most people are scientists at heart. And now that econ has tools that are more like the tools of science, I predict that the changes in the field are irrevocable.


Update

Here is a list of my previous prolix posts pompously pontificating on this particular point...





Sunday, December 27, 2015

Why I hate the "skills shortage" debate


Few econ policy debates are as fraught, or as confused, as the debate over "skills shortages" in the labor market. This debate occasionally crops up in discussions of the labor market as a whole, i.e. interpreting shifts in the Beveridge Curve. But it mostly comes up in the context of high-skilled or STEM labor.

The main problem with this discussion, as I see it, is that no one really knows what a "shortage" of skilled or STEM labor is supposed to mean. Here are some possible alternative meanings:


1. The labor market for skilled/STEM workers is not clearing, due to government policy; demand is outstripping supply. (This is the classic "econ 101" definition of "shortage").

2. There has been an increase in demand for STEM workers in the U.S. not matched by an increase in supply, causing wages in those occupations to rise.

3. A policy-engineered increase in the supply of STEM workers would raise overall U.S. GDP per capita.

4. A policy-engineered increase in the supply of STEM workers would reduce income inequality in the U.S.

5. A policy-engineered increase in the supply of STEM workers would raise the relative power of the U.S. nation-state relative to rivals like China.

6. An increase in the amount or quality of STEM education in the U.S. would raise overall U.S. GDP per capita.

7. An increase in the amount or quality of STEM education in the U.S. would reduce income inequality in the U.S.

8. An increase in the amount or quality of STEM education in the U.S. would raise the relative power of the U.S. nation-state relative to rivals like China.


I'm sure I could think of more. But in addition to these multiple definitions, there is the question of time horizon. Are we talking about what has happened since 1980? Since 2000? Or since 2010?

There is also the question of the size of the posited effects in each case. Do we think that a bit more computer science education, on the margin, would be a good thing for American schools, or do we think that we should be training our workforce en masse to be knowledge workers?

Finally, there is the question of domain size. Who is a STEM worker? Are we just talking about software engineers in Silicon Valley? Are we talking about anyone who majored in a STEM field? Are we talking about anyone who works with a computer on a daily basis?

This huge proliferation of hypotheses pretty predictably leads to a massively muddled debate. Some pieces focus on one definition of the "shortage" hypothesis to the exclusion of others. Others lump many versions together and treat them as if they're the same thing.

But despite the hopeless confusion, people get very passionate about this debate. To many on the left, emphasis on STEM education must seem like an attempt at a "third way" substitute for redistributionary policy, or an attempt by employers to make employees shoulder more of the financial burden of training. It also might seem like an attempt by anti-interventionists to substitute "structural" explanations for the Great Recession for explanations based on aggregate demand. To those on the neoliberal right, denial of the importance of STEM must seem like a minimization of the importance of productivity in national wealth, or even a refusal to focus on total national wealth at all. Supporters of high-skilled immigration (including Yours Truly!) see the denial of "STEM shortages" as the beginning of an attempt to restrict high-skilled immigration in order to boost the incomes of the upper middle class.

So there are definitely some Robertsian effects at work here. That's going to make the debate even more difficult to conduct in a reasonable, rational manner.

So is there a STEM skills shortage in the U.S.? The answer is that I don't know. I've looked into a few of these sub-hypotheses, but there are just too many. In my opinion, we should be focusing on the marginal policy effects of A) an increase in high-skilled immigration, and B) a tilting of school curricula toward math and engineering. I will search the literature for quasi-experimental evidence on these policy effects, and report back what I find. But whatever I find is unlikely to satisfy most of the people involved in this argument.

Saturday, December 19, 2015

Cultural appropriation is great!


"You'll wear a Japanese kimono, babe/There'll be Italian shoes for me" - Randy Newman, Political Science


A lot of people are talking about this story from Oberlin. Apparently some kids are complaining because certain kinds of Asian-themed food served in dining halls is crappy and non-authentic, and therefore constitutes "cultural appropriation."

Now, on one hand, this is just a story about rich kids complaining about bad food. Nothing much to see here. But it gives me an opportunity to say something that has been rattling around in my head for a while: Cultural appropriation is actually a great thing!

Wikipedia defines cultural appropriation as "the adoption or use of elements of one culture by members of a different culture." This is a good thing, for several reasons.


Reason 1: Product diversity.

This is the simple, "Econ 101" reason, if you will. Suppose Japanese people open a bunch of Italian restaurants in Tokyo. The "Italian food" is not quite what you'd get in Italy, and it's made by Japanese people rather than Italians. There's mentaiko in some of the pasta dishes. This is cultural appropriation, pure and simple. But the existence of these "Italian" restaurants increases the number of dining options available in Tokyo. More dining choices = more fun city = better life for people.

In fact, pasta itself is probably the most famous example of this sort of cultural appropriation. It was originally a failed Italian attempt to copy Chinese noodles (as is Japanese ramen, actually). Aren't you glad we have pasta? Aren't you glad we have ramen? You can thank cultural appropriation.


Reason 2: Beneficial mutation.

Pasta isn't just a crappy dining-hall imitation of Chinese noodles. It's a new, wonderful dish in its own right. The same is true of ramen. If Italy and Japan had insisted on only eating real, authentic Chinese noodles, pasta and ramen wouldn't even exist! In other words, cultural appropriation creates mutations by trying and failing to copy other cultures. The good mutations survive - we still have pasta and ramen - while the bad ones mostly die out. Cultural appropriation thus leads to innovation.

This happens a LOT in music. Almost every modern genre of popular music is influenced by either blues, jazz, or hip-hop - three genres invented by black Americans. Sometimes that influence just leads to something lame (Iggy Azalea). But often, appropriators have gone in interesting new directions with the elements they take from black American music - think of the Beatles, Led Zeppelin, Sublime, or Daft Punk. And often, that mutation and experimentation travels back and affects black American music in return. A larger ecosystem of people bouncing ideas off of each other is a recipe for creativity, even if it sometimes creates boring crap.

If you don't like cultural appropriation, you shouldn't watch Star Wars. Not only does the first movie appropriate much of its plot from Kurosawa Akira's movie "Hidden Fortress" (which itself appropriated elements of Shakespeare), but many of the elements of the Star Wars universe are appropriated from Japanese culture. Lightsaber fighting is based on kendo, Yoda is a sennin, and Darth Vader wears Muromachi period armor.


Reason 3: Technological diffusion.

In the long run, diffusion of technology between cultures is one of the main forces that helps poor countries get richer. Cultural appropriation seems like it can help this process, since many technologies are invented to fill culture-specific needs.

For example, take electric kettles. You use these to make tea. They are wonderfully efficient and labor-saving. But they would not exist if the British had not appropriated tea-drinking from Asia. Another example is rice-cookers. These are just great. But you don't need a rice cooker unless you eat dishes with rice. And often the first dishes that introduce American white people to rice are sugary, fatty, crappy imitation Chinese dishes. But so be it. Now those white folks have rice cookers! And now they can make much better rice dishes.

Now, I don't know how big a factor this can be, and those are some pretty small examples. But in general, it seems like product diffusion can boost technological diffusion, and technological diffusion is usually a good thing.


OK, you say, but these are all benefits to the appropriators. What about the appropriated? Is this one of those cases where the majority benefits from free exchange at the expense of a dispossessed minority? Actually, I think it's quite the opposite. Here are some reasons cultural appropriation helps its supposed "victims":


Reason 4: Consumer Demand Spillover

Suppose that imitation Italian restaurants flood Japanese cities (as they have actually done). Many Japanese people will be content to eat only at these, but some Japanese people will go looking for more authentic fare. They will go looking for food cooked by actual Italians, which will offer job opportunities for Italian chefs. The supposed victims of appropriation - Italians - reap economic benefit.

Hip hop is another example. How many white kids in the late 90s and early 00s got into rap and hip-hop because of Eminem? I am willing to bet that many of those kids went on to listen to black rappers and hip-hop artists (especially because Eminem did his best to promote these artists). I also bet that Elvis' popularity caused some money to flow to black artists like Chuck Berry. Sure, these artists probably deserved to get popular before their white appropriators did. That would be the ideal. But since most consumers need some kind of "gateway" music, appropriators can help funnel money to more authentic artists who would otherwise be completely ignored.

In fact, cultural appropriation can be the first step toward real cultural diversity. First, American stores start serving crappy sushi. Eventually, people eat good sushi somewhere and realize that most of the stuff in their stores is crappy. They complain. Stores then make an effort to get real, good, authentic sushi. And thus true cultural diversity is achieved.


Reason 5: Immigrant Opportunity

Americans were introduced to Chinese food via crappy faux-Chinese restaurants like Panda Express. But by helping develop a general taste for "Chinese food", those culturally appropriated restaurants helped create business for Chinese restaurants owned and staffed by Chinese immigrants. Chinese restaurants are now a huge source of employment for immigrants in the U.S. If you move from China to the U.S. with poor English skills and little formal education, you can work in a Chinese restaurant. That increased opportunity for immigrants is a huge boon to the supposed "victims" of cultural appropriation.


Reason 6: Cultural Empathy

Many of the American white kids who listen to black music - or faux-black music - will never interface with, or have any sympathy for, black culture. Some will drive around in SUVs their parents bought for them, blasting rap music even as they spout racist crap and condone policies that keep black Americans disadvantaged. Seeing this kind of thing is frustrating, and the fact that these kids listen to rap can seem like adding insult to injury.

But a few of those kids will go beyond a superficial adoption of memes from black culture. They will like the hip-hop they hear, and they will go to hip-hop shows (or at least watch them on TV). They will see black people in a context other than the conservative media narrative of "welfare queens" and "black-on-black crime". Black people will start to seem like human beings to them, and they will begin to have sympathy for movements fighting for better lives for black Americans.

This seems to have happened to my own father and a number of other white kids at his school in the 1950s and 1960s. They got into rock music - cultural appropriation of black music by whites - and this led them to get into blues music. That led them to go to clubs and stores in the black part of town, and make friends with black people. That in turn led them to be sympathetic to - and even participate in - demonstrations and sit-ins staged by black students over civil rights issues. Without that cultural appropriation, they might have simply bought the conservative line that black protesters were thugs and criminals.

Another example is how anime, cosplay, and other elements of Japanese pop culture are leading Westerners to travel to Japan and discover what that country is really like - which will probably benefit cultural, economic, and even national ties between the two nations.


So there you go: Six reasons why cultural appropriation is great. Sure, this is not always true - nothing is great 100 percent of the time. Naming a football team the "Redskins" will not have any benefit for anyone, and simply mocks the victims of ethnic cleansing. There are some bad examples of cultural appropriation, and we should get rid of them. Other examples are neither harmful nor beneficial. But most cultural appropriation seems like a very good thing - a first step and gateway to a more diverse, more interesting, more empathetic world.

Friday, December 18, 2015

Macro theory vs. string theory


After reading this cool article about the debates surrounding string theory, someone on Twitter asked me to do a post comparing it to macro theory. Well, I did that a long time ago back when I was a snarky young lad, but as someone at Bloomberg once said to me, "If you know a good story, tell it from time to time," so here goes.

String theory and macro (business cycle and growth theory) have one big problem in common: They're not easily testable. They are not untestable. There's a big difference. With string theory, if you could build a really really really huge powerful particle collider, you could probe particles down to the Planck scale, and you could establish whether or not particles are shaped like tiny strings. With macro, if you could observe a whole bunch of planets with no mutual trade between them, or if you could establish a world government and get it to do random policy experiments, you could definitely test growth and business cycle theories.

The problem is, we can't do any of these things. String theory deals with ultra high-energy phenomena, and macro deals with aggregate time series, and those are just very difficult things to observe. In both cases, one big problem is the lack of experimental controls. High-energy phenomena can sometimes be indirectly observed by looking at black holes or the echoes of the Big Bang, and the effects of time-series macro phenomena can be observed every quarter. But you can't really put these things in a lab (well, not real versions of them, anyway), so you can't poke and prod them and explore counterfactuals and deduce the underlying structure, etc.

(Update: This was a little confusing. Yes, you can test theories by looking at non-controllable phenomena. If a macroeconomic theory says "There will be a huge recession next year" and there is no recession, the theory has major problems. But because you can't do controlled experiments, you often have to deal with multiple competing theories that fit the same data. Did they U.S. economy recover from the Great Recession because of easy monetary policy, or in spite of it? And so on. In physics, this is especially problematic when looking at data from the Big Bang, of which there is only one. As you might expect, there are tons of theories floating around about how the Universe began, some of which incorporate string theory.)

So that's one similarity. A second is that studying both has led to useful spinoffs. Studying macro has led to time-series techniques like GARCH models, and arguably to much of microeconomics itself. Studying string theory has led to some cool mathematics, and to some other useful modeling techniques that have been applied in other areas of physics.

Now for the big difference. String theory is not really relevant to the real world. Although string theory techniques have found real-world applications, the theory itself has not and probably never will. No one in our lifetimes or our posthuman grandchildren's lifetimes is likely to build a machine that runs on string theory. Even if the theory - in all its myriad offshoots - turns out to be total crap, it doesn't really matter whether anyone believes in it or not. You might complain that we're wasting our society's brightest minds by paying them to study an untestable theory, but you'd then have to make the same complaint about much of mathematics itself.

In that sense, string theory is "safe" for the world. Macro theory might not be. If we pick the wrong macro theories, we could enact policies that cause real human disasters for millions. In fact, this probably happens quite often.

When data don't give you a guide to policy, major policy failures are inevitable. But what if macro is not totally untestable, but just mostly untestable? What if the evidence gives us a very weak but nonzero signal about which theories are good and which are bad?

This is the danger. If macro policy is hugely important and the signal from data is very weak, then small sociological phenomena within the econ profession - conformity, political bias, etc. - might cause great harm to real people. And bad scientific techniques - ignoring data entirely while placing too much faith in plausibility - might also cause cause real-world harm.

To sum up: If string theory happens to be complete B.S., there is essentially no loss to society. If prevailing macro theory (New Keynesian models now, RBC in the 80s, etc.) is complete B.S., there might be no loss, but there might very well be a big loss. This is probably why the public gets a lot madder about macro debates than about high-energy physics debates.

Saturday, December 12, 2015

Academic B.S. as artificial barriers to entry


"Stratos has never sampled the full terror stalking the stars." - David Brin, Glory Season


Paul Romer complains of "mathiness" in macroeconomics. Paul Pfleiderer talks about "chameleon" models. Ricardo Caballero says macroeconomists encourage the "pretense of knowledge". Everywhere, people complain about economists' fetish for pointless model-making. And of course, some folks accuse the economics profession of being a front for laissez-faire ideology.

But we should remember that compared to other disciplines, econ is in great shape. A friend just sent me a paper by Ananya Roy, a professor of urban planning at UCLA, entitled "What is urban about critical urban theory?" Here is an excerpt from the abstract:
This essay discusses how the “urban” is currently being conceptualized in various worlds of urban studies and what this might mean for the urban question of the current historical conjuncture. Launched from places on the map that are forms of urban government but that have distinctive agrarian histories and rural presents, the essay foregrounds the undecidability of the urban, be it geographies of urbanization or urban politics. What is at stake is a critical urban theory attentive to historical difference as a fundamental constituting process of global political economy and deconstruction as a methodology of generalization and theorization.
And here is the spectacular final paragraph:
I conclude then with the invitation to read the urban from the standpoint of absence, absence not as negation or even antonym but as the undecidable. I conclude too with the provocation that theory, including a theory of the urban, can be made from the tealcolored building at the edge of the world that is the Dankuni municipality, a panchayat office repurposed for urban government. But in a gesture befitting the task of provincializing the urban, I note that the dedication plaque for the panchayat building references a fin de siècle poet, Jibanananda Das and his writings on “rupasi bangla,” or beautiful Bengal, envisioned as rural and verdant. But Das is also the first urban poet of Bengal, with a set of starkly neo-urban poems that are now etched into the region’s self-imagination of urban modernity. The plaque can thus be read as a serendipitous anticipation and premonition of the urban yet to come but its rurality cannot be effaced or erased (Figure 4). The sign of a constitutionally demarcated urban local body, it is the undecidability of the urban.
To many readers not steeped in critical theory, this may sound like a broken fire hydrant of nonsense. One may be tempted to reach for a copy of Pennycook et al.'s paper, "On the reception and detection of pseudo-profound bullshit."

But I don't think critical theory is simply the academic equivalent of meaningless auto-generated guru wisdom. My guess is that it's actually something else: Obscurantism.

Here's what I kind of suspect is going on.

For a given level of demand, supply restrictions generally push up price. You don't want to have any old dork walk in off the street and get a full professorship in urban studies. That would send salaries crashing, and prestige as well.

But what if urban studies is just inherently a really easy field? (I'm not saying this is true, I'm just being hypothetical!) What if all the remaining big truths could be uncovered by running a few regressions in Stata? In that case, the supply of potential urban studies profs would be really big. Danger!

If existing urban studies profs can form a cartel, they can artificially raise the barriers to entry and bring supply back down again. Cartelization in academia doesn't seem that hard, since admissions, hiring, and tenure committees are already cartels, and since the barriers to creating new universities and new top journals are very high.

The barriers to entry will probably be some combination of A) a psychometric test, and B) an ideological loyalty test. These tests are relatively easy to administer. They also take advantage of natural supply restrictions - very high-ability people (along whatever dimension you want to measure) are relatively rare, and ideological buy-in is limited by the diversity of ideas in society. For example, there are just not that many people who are both A) really good at parsing dense paragraphs of text, and B) deeply committed to a quasi-Marxist lefty ideology.

Artificial entry barriers provide a tidy explanation for the rise of "critical theory" in humanities, urban planning, anthropology, and sociology departments. Critical theory is basically just the practice of taking lefty social criticism - of the type you might find in any college dorm - and dressing it up with a bunch of neologisms and excess verbiage. Stephen Katz of Trent University explains this in an essay entitled "How to Speak and Write Postmodern". He gives some hypothetical examples:
For example, let’s imagine you want to say something like, “We should listen to the views of people outside of Western society in order to learn about the cultural biases that affect us”. This is honest but dull...[Instead]  say, “We should listen to the intertextual, multivocalities of postcolonial others outside of Western culture in order to learn about the phallogocentric biases that mediate our identities”... 
You want to say or write something like, “Contemporary buildings are alienating”. This is a good thought, but, of course, a non-starter. You wouldn’t even get offered a second round of crackers and cheese at a conference reception with such a line. In fact, after saying this, you might get asked to stay and clean up the crackers and cheese after the reception...[Instead, say] “Pre/post/spacialities of counter-architectural hyper-contemporaneity (re)commits us to an ambivalent recurrentiality of antisociality/seductivity, one enunciated in a de/gendered-Baudrillardian discourse of granulated subjectivity”.
As multivocalities on the internet say: LOL.

The supply of super-lefty people who are able to parse artificially dense text is limited, but not so limited that it's hard to find people who are willing to do it for $70,000 a year. Meanwhile, student demand for humanities, anthropology, urban studies, and sociology majors is probably pretty inelastic, so university demand for professors in these areas is probably inelastic. Hence, for departments and journals in these fields to make "critical theory" a soft requirement for professors is probably an effective way of keeping their salaries (and job perks) as high as they are.

It seems pretty obvious that humanities departments have been almost entirely consumed by this sort of thing. Any semblance of objectivity (whatever that would even mean in the humanities!) is gone, replaced by pervasive quasi-Marxist doofiness. And humanities scholars' research work now appears to largely consist of parsing and writing artificially dense text. As for the social sciences, anthro seems to have taken some big steps in this direction, and sociology more modest steps.

How about economics?

The econ profession as a whole is shifting toward empirics, and possibly even toward reduced-form empirics. Since the flood of data is a recent thing, most of the new insights in the field over the next decade or two will probably be gained from doing this kind of work - as John Cochrane says, "The stars in their 30s are scraping data off the internet."

Scraping data off the internet is cognitively demanding work, but not that demanding. Without artificial entry barriers, the data flood would probably increase the supply of people qualified to be economics professors. To preserve their high salaries and high levels of intellectual prestige, it therefore behooves the economics profession to create some artificial barriers.

Econ isn't going for ideological tests - or at least, not very much. There's too much pressure from the world at large to stay objective. So the entry barriers rely mostly on psychometric tests. Mathematical theory, of the type economists do, is hard to do - much harder, for most people, than parsing dense paragraphs of woo-woo "critical theory".

This could explain the pressure on empirical economists to include a structural theory section that has little relation to the reduced-form empirical analysis that forms the core of a paper. It also might explain why even though the economics literature is more and more filled with reduced-form empirical studies, theory papers are still very common on the job market.


Updates

Brad DeLong is annoyed with me for picking on Ananya Roy, and links to an essay of hers that he implies is much better than the paper I cited (and which is written in more-or-less plain English). But I didn't quote one of Roy's papers because I think she's a bad urban studies researcher (how would I even know if that were true?). My conjecture was that many successful urban studies profs will have written at least one or two papers like this - much like almost any top macroeconomist will have at least one or two theory papers with unrealistic assumptions and complex math that can't really be tested against data. I'm not trying to single out any individual for criticism.

Some commenters have been suggesting that critical theory is actually on the wane in the humanities. That is interesting; I don't know many humanities people, so I'm pretty uninformed about recent trends. I knew a bunch of Michigan humanities PhD students back in grad school, and they were all very into critical theory. I also met an incoming literature prof at Stony Brook who said she does "theory", and when I asked her "What kind of theory?", she blinked in surprise and asked "Are there multiple kinds?". So anecdotes suggest it ain't dead yet...

A commenter points out that, as usual, Feynman did this snark way before I did.

Thursday, December 10, 2015

Efficiency in growth's clothing? (reply to John Cochrane)




In response to a John Cochrane policy paper on growth policies, I wrote a post chiding Cochrane for selling efficiency policies as long-term growth policies. Cochrane now has a long and rather testy reply to Yours Truly. The basic message of the reply is: "If level effects are really, really big, they tend to look like long-term growth effects."

Yep. That's right.

Cochrane's original paper described the impact of growth policies by drawing an analogy with the period from 1950-2000:
If the US economy had grown at 2% rather than 3.5% since 1950, income per person by 2000 would have been $23,000 not $50,000. That’s a huge difference. Nowhere in economic policy are we even talking about events that will double, or halve, the average American’s living standards in the next generation. 
To get a policy change that had that effect, we'd need:

A) A doubling of the level of detrended steady-state GDP, and

B) Frictions in the economy and/or the policy-making process that smoothed that change over 50 years.

Cochrane, in his new post, asserts that (A) is possible (I'll get to that later). He doesn't mention (B). How much of the growth we enjoyed from 1950 to 2000 a result of policy improvement? Cochrane certainly believes strongly that Reagan's policies caused a lot of the growth in the 80s and 90s, but how about the equally impressive growth from 1950-1980?

When I look at U.S. history I see a pretty smooth growth trend (I'll use a David Andolfatto tweet instead of just grabbing FRED data, because it's funnier!):




See the big growth takeoffs from policy liberalization? Neither do I.

Of course, at any time we could have chosen to become North Korea, at which point the line would have crashed and burned, so in some sense the whole upward trend was due to policy. But I think that it's hard to look at this steady upward march and see anything other than the steady improvement of technology. If you look at other countries, you see that they did just about as well as us (or better) over this time period, and that our growth and theirs was highly correlated. To me, that says that it was technology (and trade), not policy changes, that drove most of the global growth trend.

But OK, OK, if we DID engineer policy changes that doubled our income, would it matter to us if it was abrupt or spread out over decades? No, it would not. So Cochrane is right - a "level effect" that huge really would be party time.

So maybe my Bloomberg piece didn't really manage to express what actually annoyed me about Cochrane's paper. I guess it wasn't just about "growth effects" vs. "level effects". It was about proof versus conjecture.

Cochrane, by citing the growth we enjoyed from 1950-2000, and then telling us that we can enjoy similar growth if we do his preferred policies, seems to imply that this is something we've done before and therefore something we can do again. To me, that doesn't seem to fit the facts, even if you give Reagan as much credit as Cochrane gives him. To me, it seems pretty obvious that liberalizing policy changes produced, in the past, at best small bumps in the trend of steady technological progress.

But OK, OK, John obviously really believes that his preferred policies would engineer a HUGE change - a doubling or tripling - of our potential GDP. I may disagree with that prediction, but I guess I shouldn't dismiss it out of hand. I definitely think that pointing to the growth from 1950-2000 as an example of what we could achieve with deregulation is misleading. But ultimately that springs from the fact that my priors about how the world works are just very different from John's.

Anyway, on to John's other points:


Cochrane Point 1: If China did it, why not us?

Because China started off very far away from the technological frontier. If you liberalize your economy in ways that allow you to start importing and applying foreign technology, you will be able to grow fast. Some of China's growth is simple Solow capital catch-up, but some of it is a sudden and dramatic influx of foreign technology.

The U.S. is at or near the technological frontier, so I assume it would be a lot harder for us to do what China did. I think this again illustrates a difference in the way John and I think about productivity - he seems to instinctively think of policy, I always instinctively think of technology.


Cochrane Point 2: We could triple or octuple our GDP by making it easier to do business!

I was pretty skeptical of this argument. Reverse causation is a much bigger problem than Cochrane seems to think; he dismisses it with some anecdotes, but I don't think it can be dismissed. Another problem is the poor fit of the regression line Cochrane shows - see Kevin Grier for more on this point.

A third problem is that the World Bank's "Ease of Doing Business" indicators are constructed from surveys, which have all kinds of huge methodological issues (which Cochrane himself has pointed out in other contexts). They are not objective measures of the ease of doing business.

What this means is that A) the hypothetical "frontier" that the World Bank and Cochrane construct may not exist, and B) attempts to reach that frontier might actually hurt rather than help growth/efficiency. Alternatively, engineering improvements in the rankings might help a lot for poor countries but not help much for rich countries.

If we look at real-world examples, only one single country - Singapore - has both A) substantially higher GDP than the U.S., and B) better performance on the World Bank rankings. Singapore's GDP is about 60% higher than ours in PPP terms, so if we could reach that level it would indeed be great. They are #1 in the World Bank's rankings. The U.S. is #7. Countries #2-#6 are actually all a bit poorer than the U.S.

But maybe we can emulate Singapore.


Cochrane Point 3: Permanent growth effects might not actually exist.

Yep, true. Cochrane points to a Chad Jones paper showing this, which I actually already knew. It's a good paper. In fact, if you just use a simple Solow-type exogenous growth model you get a similar conclusion - there's nothing you can do to boost growth in the very long run.

Whether or not this is true, it is orthogonal to my point. I was talking about the overselling of efficiency-based policies by appealing to the history of long-term growth. I did not intend to claim that there are other clearly identifiable policies we could take to boost the growth trend for 50 years.


Cochrane Point 4: I should not have used the word "conservative".

I think this word was appropriate. First of all, it's one that the public intuitively understands. Second of all, it accurately communicates Cochrane's apparent love for Republican politicians, especially Reagan. In an earlier post (also a rebuttal to Yours Truly), Cochrane wrote:
In 1980 Ronald Reagan announced some pretty radical growth-oriented policies, at least by the standards of the time. (Not much new since Adam Smith, of course.) The standard liberal commentators made the standard objections: voodoo economics, numbers don't add up, it will take generations of unemployment to lower inflation, the debt will explode, and so forth. (Plus, the Soviet Union will be there forever, we might as well get along.)  Reagan offered optimism; won, malaise ended, we won the cold war, and there was an economic boom.
I would note that:

A)  John uses the word "liberal" to describe people who disagree with his desired policies, and most people use "conservative" to mean the opposite of "liberal".

B) Reagan's policies included more tax cuts, while the big deregulations came under Carter. Deregulation is the centerpiece of Cochrane's current growth proposals, so it's interesting that he credits Reagan 100% and Carter 0%. If the World Bank's Ease of Doing Business rankings had been around at the time, I think Carter's reforms would have resulted in a lot more improvement than Reagan's, but Cochrane gives Reagan all the credit. That sort of feels like a politically "conservative" view of things.

So I don't think that any harm was done by the use of "conservative".

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.


Updates

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.