Thursday, July 21, 2016

Trump happened because conservatism failed


Tyler Cowen (now a Bloomberg View colleague of mine) took a crack at this question back in February, and I've been thinking about it ever since. Here's my unified theory of why a guy like Trump managed to take over the Republican party this year, when nothing similar had ever happened before in living memory.

First of all, a note about causality. Most events are the result of a chain of causes - if one link in the chain falls apart, the event doesn't happen. This is not the way human intuition naturally thinks about causality - we instinctively imagine each event as the sum of causal factors, and attribute some percent of responsibility to each factor. But with a causal chain, each link is responsible for 100% of the causality. Just like the marginal value of a right shoe and the marginal value of a left shoe are both equal to 100% of the total value of a pair of shoes.

So I think that Trump is a special human being. He's a reality star, a possibly-faux-billionaire celebrity who's really good at overselling himself, and has essentially no scruples. There aren't many of those in the United States who want the job of president. In fact, there is probably only one. If Trump had been killed in a car accident in 2014, we might be looking at a much more typical Republican candidate, with the Republican establishment retaining a shaky but intact grasp on the party.

But that's just one link in the chain - one precondition for the Trump Takeover. I think there are two other main links here: 1. The dramatic weakness of the Republican establishment, and 2. The existence of a Trump-friendly voter bloc in the first place.

In the past, the Republican presidential candidate was usually a gray, bland figure, a stalwart conservative but not a fire-breathing one, a man who had worked his way up the ranks. Romney, McCain, Bush II, Dole, and Bush I all fit this description - Reagan was the only possible exception within my lifetime, and even he didn't deviate too far from this model. As a conservative, the Republican nominee would support tax cuts, a business-friendly attitude, a tough-guy attitude toward America's enemies and rivals, and traditional family values based on Christianity. That's what conservatism was.

But in the past fifteen years, the three pillars of conservatism - economic, foreign-policy, and social conservatism - have all had huge, dramatic failures.

Economic conservatism had two big failures. The first failure was when the Bush tax cuts failed to reverse income stagnation:


The second failure was when a lax regulatory climate appeared to give rise to a financial crisis that devastated the job market. That second shock was so huge that it has all kinds of people questioning neoliberalism itself - big, comprehensive alternative policy paradigms like protectionism, socialism, and industrialism are now being openly considered. Those alternatives may or may not gain traction. But certainly, the formula of "cut taxes and let businesses do as they see fit" is now pretty discredited. Some older intellectuals continue to fight doggedly for this economic program, but nowadays they are rightfully ignored.

Simple truth: Economic conservatism failed in the 2000s and 2010s.

Next, foreign policy conservatism. This failed during the George W. Bush administration, when Bush turned bellicose rhetoric into bellicose reality with the disastrous Iraq War. The Iraq War was a disaster because despite winning the war pretty handily and taking low casualties, we received no gains. We spent massive amounts of money and thousands of lives, and temporarily wrecked our international prestige, only to turn Iraq from an unthreatening petty dictatorship into a failed state and a breeding ground for ISIS. It was a failure of the modern conservative approach to war itself.

A more minor failure was the seeming emptiness of Bush's bellicose rhetoric when it came to actual threats. Under Bush's watch, Putin's power grew inexorably, and North Korea got nukes, while Bush barked impotently. This wasn't nearly the kind of disaster that Iraq was, but it probably unsettled some Americans, and it certainly unsettled the foreign-policy establishment.

So foreign-policy conservatism failed in the 2000s.

Finally, social conservatism. This was the biggest failure of all. Social conservatism promised to restore family values by promoting Christianity and resisting things like gay marriage. But as Charles Murray and many others have documented, working-class white America professes more traditional values, but doesn't practice them. On the whole, working-class whites are no longer going to church, are no longer getting married (or staying married), and are having kids out of wedlock - in other words, traditional family values are dying among the very people who were most receptive to social conservatives' message. Here's a graph from the Washington Post:


Social conservatism also failed to make its case to young Americans. Secularism is rising rapidly. Gay marriage enjoys wide support, especially among the young. Americans have resoundingly rejected the values pushed on them by Christian conservatives in the 80s, 90s, and 00s. Here's a graph from Pew:


So social conservatism also failed in the 2000s and 2010s.

Add all this up, and what do you get? A massive, total failure of all three pillars of modern conservatism within a 15-year period. It's little wonder, therefore, that Trump voters were unwilling to vote for Republicans who offered them only more of the same - the same economic policies that seemed to cost them their jobs and businesses and wages, the same foreign policies that embarrassed their country, the same social policies that had done nothing to save their families. Even when the conservative ideology was offered with maximum fire and vitriol, in the person of Ted Cruz, they weren't willing to bite. So they looked around for something else, and Trump was there.

So that leaves us with the final link in the chain: the question of why Trumpism filled the void that conservatism created with its rapid collapse. Why are Trumpians Trumpians in the first place? That's a question I don't think I know how to answer. It's probably something having to do with race, religion, tribalism, xenophobia, etc. It very well might have something to do with globalization and import competition from China. Or it might just be a faction that was there all along, and supported conservatism for a while out of convenience. Or all three. Or something else. I don't know.

But whatever the reason for Trump's support, a necessary piece of the Trump takeover equation was the collapse of the conservative ideology. That epochal event should be a lesson to us all - it's what inevitably happens to an ideology when it succumbs to overreach, dogmatism, and an echo chamber.

I hope I don't ever have to watch the same thing happen to the American left.

Tuesday, July 19, 2016

Criticisms of NGDP futures targeting


Zak David, a quant trader, recently wrote a post criticizing Scott Sumner's idea of NGDP futures market targeting. Sumner fired back with a defense of the idea, and Zak responded with an update to his post.

I want to see if I can explain Zak's ideas in a little greater detail. Basically, he's right.

To recap, the original NGDP futures targeting idea goes something like this:

1. The Fed sets an NGDP target (say, 5%).

2. The Fed then offers to enter into any number of NGDP futures contract with anyone who wants, at a price equal to the target. So if I take a $1000 long position in these futures, and NGDP comes in at 10% (double the target), I get $2000 back. If I take a $1000 short position, and NGDP comes in at 2.5% (half the target), I get $2000 back. And so on. The Fed is always on the other side of the deal, and I can make as many of these deals as I want (assuming I can post sufficient margin).

3. The Fed then makes monetary policy automatically in response to people entering into these contracts with it. If a person takes a long position in NGDP futures, the Fed tightens a bit to make sure NGDP doesn't actually come in above target.

Zak had three main criticisms of this idea:
A) Informed traders will not trade in this market,
B) Manipulators will trade in the market, and
C) Data revisions will introduce noise into monetary policy.

I'll ignore (C) and try to explain (A) and (B). Keep in mind that I'm not saying anything new in this post; just restating Zak's argument in my own words.

First, let's talk about why informed traders - the people we want to trade these contracts - won't even show up. Suppose I have some knowledge that the Fed doesn't, about macroeconomic forces. For example, suppose I see a big inflationary shock coming that, if the Fed doesn't counteract it, will raise NGDP to 10%. Will I take a long position in an NGDP futures contract in the market described above, thus revealing my private information to the Fed and helping it make better policy?

It depends. IF the Fed hits its NGDP target on average, then I will not. Because in that case, on average, I would lose money betting on the Fed not hitting its target. Why the heck would I bet good money on 10% - or 2%, or 6%, or 5.001% -- when the probability distribution of NGDP is distributed symmetrically around 5%? A negative expected return with positive risk? No thanks!

If the Fed DOESN'T hit its target on average, then I might be able to make some money entering into this futures contract. But if the NGDP futures targeting mechanism doesn't lead to the Fed hitting its target on average, why the heck would we want to use that mechanism to make monetary policy in the first place??

So IF the mechanism works, no informed traders would use it. Hence, whatever information they have about macroeconomic shocks will NOT reach the Fed.

That is criticism (A).

OK, so who definitely would trade in that futures market? Manipulators.

Suppose I'm just some deep-pocketed jerk with zero knowledge of the macroeconomy, and I want to make some free money at the expense of the country and the bond markets. Here's what I do. First, I sell TIPS and buy Treasuries - in other words, I bet against inflation. Then I take a huge amount of long positions in NGDP futures. The Fed tightens monetary policy. My TIPS go down relative to my Treasuries, and I pocket the spread. Then I take a bunch of short positions in NGDP futures -- at the exact same price as before -- to net out my previous long position.

I have manipulated the TIPS and Treasury bond markets. I have caused monetary policy to change. And I have made arbitrage profits.

This is bad, because it introduces noise into monetary policy, and it also causes the bond markets to be less efficient.

That is criticism (B).

Both of these criticisms are valid. In other words, an NGDP futures targeting policy as stated above would introduce zero information to the making of monetary policy, while introducing a nonzero amount of noise. You'd be better off setting monetary policy according to  a random number generator, because at least then you wouldn't be letting crooks rig the bond markets.

So Zak David is correct. The idea is not sound. If you want to use NGDP futures targeting to set monetary policy, you're going to have to think of a much better system than the one described above.

(Fun bonus point: Why doesn't criticism (A) apply to all financial markets? That's probably the biggest question in the field of market microstructure. Check out the Glosten-Milgrom model and the Kyle model for two classic answers to that question.)


Updates

1. Everybody is asking me to link to these old posts (post 1, post 2) by Mike Sankowski criticizing Sumner's idea. Check them out if you're interested in this debate (and if you're not, why have you read this far?).

2. As expected, Scott Sumner fires back. He accuses Zak and me of disbelieving the EMH. Well, does anyone think the EMH holds when the government pegs the price of assets? If the government offered to buy and sell infinite amounts of Tesla stock futures at the price of $200 a share, would that market be efficient? No, it would not. Would $200 be the best estimate of Tesla's future earnings? No, it would not. Scott, just because you call something a "market" doesn't mean it's efficient.

Sumner seems to have thought very little about how markets actually become efficient. Scott, you need price discovery. Which means you need informed traders to trade. Informed traders' trades are the mechanism by which information gets from the world into the price. If informed traders don't trade, the price is based on some combination of A) noise, and B) manipulation. Informed traders only show up if they can profit by trading on their information. For informed traders to profit, someone else must lose money. In most models of market microstructure, the money is lost by liquidity traders (sometimes called "noise traders", though that term is now usually used to mean fools who trade overconfidently on false information).

In Sumner's "market", the only liquidity trader is the Fed itself. If the Fed sets policy such that A) informed traders can make money trading against the Fed, and B) the Fed offers infinite liquidity, that means that informed traders can make infinite money at the Fed's expense. But the Fed controls policy. It can make very, very, very sure it does NOT lose infinite money to informed traders. If the Fed provides infinite liquidity, the only way for the Fed to make sure that it doesn't lose infinite money to informed traders is for the Fed to make sure it doesn't lose any money to informed traders. (Note that this would most likely involve setting monetary policy to overreact to any trade.)

Hence, an informed trader would have to be dumb to trade in Scott's market, because trading in Scott's market means fighting the Fed and losing. Hence, no informed traders will show up. So the only traders who do show up will be A) liquidity/noise traders, B) fools, and C) manipulators. Hence, if the Fed sets monetary policy in reaction to trades in Sumner's market, it will set monetary policy purely in reaction to noise and/or manipulation.

Wednesday, July 13, 2016

When will China make its move?


I'm now reading Paul Kennedy's The Rise and Fall of the Great Powers, so I thought I'd ask a disturbing, alarmist, but important question. If China makes a bid to overturn the U.S.-led global order by military force, when will that bid come?

(This sounds like a job for...amateur made-up political science!)

First, two preliminary questions: 1) Will such a bid really come? And 2) What would it look like?

My answer to (1) is "maybe, maybe not." So far, there have been several modern examples of great powers not trying to overturn the existing order by force. The UK dominated the seas and built a huge maritime empire, but never tried to leverage its global power to dominate the other great powers of Europe; instead, it tried to maintain a balance of power that allowed it to be rich and secure. The U.S. made a few aggressive moves in the early 1900s, but only reluctantly joined World War 1, and then tried to go isolationist in the interwar years - it eventually became a hegemon, but only reluctantly. And the Soviet Union made a lot of threatening moves and came close to fighting the U.S., but backed off repeatedly. So there's plenty of precedent for new powers refusing to try to overthrow the old ones by force - in fact, the only real violent attempts in the industrial age came from Germany (twice) and Japan. But there still seems to be a decent chance that China will launch an attack against the U.S.-led coalition, given the "Thucydides Trap." So let's consider what happens if it does attack.

As for question (2), my guess is that it would be a naval attack in the South China Sea (against the U.S.) or in the East China Sea (against Japan, which would then call for help from the U.S.). Tensions have been rising slowly but inexorably in both places. A decisive naval victory against the U.S. would A) push American power out of Asia and establish Chinese hegemony in its backyard, and B) cause the U.S.' allies all over the globe to realize that America could no longer protect them, thus effectively ending America's position as a global hegemon. Such a conflict probably wouldn't go nuclear - the U.S. signaled its willingness to die to protect Germany, France, and the rest of Europe from the USSR in the Cold War, but it seems unlikely that it would do the same just to protect freedom of the seas in Asia. So if an attack comes, I expect it to be China trying to sink our Asian fleet. If it does that, it wins.

OK, now on to the main question: When will such an attack come, assuming it comes? Let's imagine we live in a worst-case version of a Paul Kennedy world, where great powers only care about hegemony, rather than the welfare of their people, etc. In that case, this becomes like the old Econ 101 question of when to cut a forest. Basically, if China is going to attack, it will do so whenever the opportunity cost of attacking - i.e., the benefit of waiting - drops below a certain threshold.

What are the benefits of waiting to attack? Basically, continued economic growth and technological progress. If we're in a Paul Kennedy type world, a larger economy means more military power, which means A) a higher chance of beating the U.S., and B) a higher chance of dominating Asia and the world after beating the U.S. Better technology means the same.

So if we're in a Kennedy world, we can think of GDP, maybe with some extra exponent on productivity, as the percent chance of getting "flow hegemony" in the objective function after an attack. But before the attack, flow hegemony is zero (because in this cynical world, power doesn't matter if you don't use it to rule the world). And there's some time discount rate too. So basically, when China's economic growth and productivity growth slow down below some threshold rate (representing the discount rate in their hegemony objective function), that's the time to attack.

Chinese GDP growth has already slowed substantially:


Current official figures are at around 6.6%, though the true figure may be closer to 5%. And many people think that only an unsustainable, unproductive debt-laden construction boom is keeping growth at that pace -- once it ends, many expect China to have to deal with the financial overhang from the boom, which could lead to a decade of slow growth. Productivity growth is much harder to measure, but what few data points we have point to a slowdown in recent years.

One big factor will definitely drag down Chinese growth in the years to come: population shrinkage. According to government estimates, the country's working-age population (15-60) has been declining since 2012, and has now shrunk by 26 million. The decline is projected to continue, accelerating sharply between 2020 and 2025:


Even an immediate baby boom wouldn't affect this number until 2030, so the repeal of the one-child policy will not change anything for a while - and given the low fertility of other Asian countries, and the lack of much interest in having more kids, it seems unlikely that the long-term effect of the repeal of the one-child policy will actually arrest China's population decline.

So after 2020, there will be a sharp decline in China's working-age population. If the "debt overhang" people (Chris Balding, Michael Pettis, etc.) are right, China will also have to deal with another sharp slowdown in growth sometime in the next few years. Meanwhile, productivity is slowing down as China reaches the technological frontier and is thus less able to acquire new tech through FDI joint ventures, forced tech transfers from multinationals, or industrial espionage.

All of this points to a Chinese attack sometime in the remaining years of this decade. IF, of course, they decide to attack at all, and if GDP enters the objective function in the way I just hypothesized.

In any case, after 2020, China's "window" for a successful overthrow of the U.S. might close. Rapid population aging and labor force decline, the slowdown of catch-up growth, and (possibly) the overhang from decades of debt buildup might do more than just reduce the benefit of continuing the "peaceful rise" strategy. They might actually cause severe domestic unrest in China, forcing the country to turn its energy toward domestic security matters. And even if that doesn't happen, China's inevitable economic slowdown may simply weaken the country's total military power, allowing the U.S. and its allies - perhaps including a fast-growing India - to retain hegemony into the indefinite future.

So I think that if China does decide to take the more violent, aggressive great power path, we can expect some action within the next few years.

Sunday, July 03, 2016

Economist gekokujo


"Gekokujo" (下克上) is a Japanese word meaning "low overcoming high". It refers to when the people lower down in a hierarchy rise up and overthrow those above them. Rebellions, mutinies, and populist uprisings are all gekokujo. The word was often used in conjunction with coup attempts by lower-level military officers in the years before WW2. Japan, it turns out, is a lot less hierarchical - or at least, obedient - of a place than people think.

One culture I know that is very hierarchical is the econ profession. It has a centralized job market. Academic hiring is heavily weighted toward candidates from top departments. And it's sort of an open secret that old, famous professors can essentially publish whatever they want in top journals, which gives these old famous people enormous clout.

As in most academic fields, publishing in one of a few top journals is key to career advancement. But in recent years, more and more top-journal publishing has been dominated by one single journal: the American Economic Review:


In econ, the standards for what constitutes good research and what constitutes bad research are less clear than in the natural sciences (though far clearer than in the humanities). That adds to the suspicion among the lower ranks of the profession - grad students, younger profs, profs and students from lower-ranked departments, etc. - that successful economists got where they are by sucking up to old famous people. "It's a sleazy profession," a young and talented assistant prof once confided to me, over a beer. "I'd advise you to get out of it." (I ended up taking his advice.)

Anyway, it makes sense that econ would be ripe for some gekokujo. And it also makes sense that the rebellion would erupt from the Econ Job Market Rumors forum.

Almost everyone except EJMR regulars despises EJMR. The site has a fair amount of the sexism and other aggression so common on anonymous internet forums (it's been called "4chan for economists", which in my opinion is a bit of an insult to 4chan's creativity and sense of humor), but that can't account for the near-universal visceral hatred that most economists feel toward the place. Most people who tell me how much they hate EJMR talk about what one PhD student called its "insecurities, careerism, and insane status and hierarchy obsession." Essentially, EJMR vacillates between slavish worship and bitter disdain for the top people and organizations in the profession. These people deeply believe that they need to suck up to the big dogs to get the brass ring, and even though they go along with it - econ jobs, with their high salary, lucrative consulting gigs, and intellectual prestige, tend to be a pretty nice brass ring - they don't like having to do it. So if econ is going to have an equivalent of the gung-ho young Japanese officers who launched repeated coup attempts in the 1930s, it stands to reason they'd come from EJMR.

It also stands to reason that the target of the uprising would be the AER, one of the profession's most important gatekeepers. So I was hardly surprised to see a publication scandal involving EJMR and the AER. Essentially, EJMR people started accusing an AER editor of 1) favoritism and bias, and 2) overlooked citations. These are typical academic sore points, and of course this dispute obey's Sayre's Law. But I also see it as a proxy for a wider dissatisfaction with the centralized, hierarchical, and somewhat arbitrary nature of a lucrative and prestigious profession.

There's a possible political angle here too, though I don't want to play it up too much. The AER editor being accused of favoritism, and the young authors accused of being the beneficiaries, are all women. The paper is a reduced-form empirical paper of the type that is taking over more and more of econ publishing. And the paper's policy conclusions are that unemployment is bad and that poverty could be transmitted from generation to generation by mechanisms other than genetic ability.

Like Japanese army officers in the 1930s, EJMR people tend to be right-leaning types in addition to careerists. The few times I could bring myself to read EJMR, I always saw a combination of A) disdain for political liberalism, B) disdain toward "reg monkeys" (a pejorative term for economists who do reduced form empirics), and C) bitterness toward women in general and toward allegations of sexism in the econ profession. It seems possible to me that many smart young conservative men were drawn to study economics, attracted by its traditional support for free markets and its traditional skew toward the male demographic - but that when they arrived, they found a profession increasingly tilted toward the left, increasingly populated by women, and increasingly accepting of the use of reduced-form regressions that can easily be interpreted as making a case for government intervention. George Borjas, who came out in support of the rebels, is certainly known to lean pretty strongly to the political right. This episode of EJMR gekokujo might be part of a more general backlash against these trends by angry young conservative men who feel that the econ elite, by favoring women and/or liberal politics, is depriving them of their just desserts.

Or not. That was just a thought I had, and it seemed kind of interesting, so I wrote it down. Don't take these musings of mine as any kind of evidence that left-right politics or gender politics is actually involved. But whatever the larger political context (or lack thereof), it clearly seems to me like a case of econ's "bottom feeders" (as one top economist called EJMR's denizens) rising up against the masters of their lucrative, prestigious little universe. I wouldn't be surprised to see more such "incidents", as Japanese history politely refers to them.


Update

Regarding the sexism thing, someone sent me the following screenshot from an EJMR thread discussing this post:


I don't think this kind of thinking totally dominates EJMR, and I don't know how much it's motivating this particular uproar. But I do think there's a fair amount of it there, which is why I mentioned it. It's also why I didn't try to comment on the merits of the case...I don't like pseudo-corruption and favoritism, and it certainly seems like a pervasive problem in econ, but I'm also pretty wary of joining what might turn out to be a sexist witch hunt...

Also, check out some interesting comments from someone claiming to be a recent job candidate. He or she raises a great point, which is that in the age of empirical economics, data access is really important, and that many young and/or struggling economists are mad about top institutions getting preferential early access to data. Early access allows simple, easy analyses - which many non-top economists are perfectly capable of doing - to get published in top journals, because the data is novel. That, argues the commenter, is causing a lot of anger in the lower ranks of the profession, some of which might be getting displaced as anger against perceived nepotism (which is actually a different issue). That rings true to me, and I will definitely follow up on the data access issue...

Thursday, June 30, 2016

Some stuff economists tend to leave out


Chris Arnade got a PhD in theoretical physics, became a bond trader, and then became a photographer who documents drug addiction. He frequently writes on Twitter and elsewhere about social problems. Recently, he wrote a tweetstorm (series of threaded tweets) about his interpretation of Trumpism. I think Chris leaves out a lot of the reasons for Trump support - xenophobia, fear of racial conflict, misplaced nostalgia. I also doubt that the drug addicts that Chris spends his life documenting tend to be Trump supporters. But I think Chris makes some really good points when he writes:
Many people have no chance & they know it & reminded of it daily. On TV, on the web. They see what they are missing. And who is winning...The response to this is, we all have Iphones now. Everyone has all this stuff they never had before...Response 1: Maybe when we measure someone by how much stuff they have, those at bottom will never be happy. Because others have far more...Response 2: Maybe trying to get all that stuff is painful. Maybe the monthly payments needed to keep up isn't fun...Response 3: Maybe, crazy as it might sound, having an Iphone, and other things, just isn’t the key to happiness after all...Response 4: Maybe people need meaning beyond economic. Maybe they need to feel included, to have strong bonds to institutions & groups...Maybe the predatory, hyper rational society we have built has stripped institutions of their meaning...Maybe it has all left people, who used to get meaning from them, with very little, other than anger.
I think there's a lot to this. Putting it in econ language: 1) Social preferences are probably very important in reality. 2) Utility functions often contain inputs like inclusion, human connection, and a sense of meaning, for which no markets exist.

Econ rarely deals with these things. When is the last time you heard an economist talk about how minimum wage policy affects people's desire to feel like society cares about them? When is the last time you heard an economist talk about the need to include strong interpersonal relationships in GDP? When is the last time you saw a welfare analysis of tax policy that took inequality preferences into account?

The formal machinery of economics is totally equipped to deal with these things. You can put love in a utility function right alongside consumption, just call utility u(c,L). You can incorporate community stability into an urban model or a model of migration. You can put social trust as an input into a production function. You can give people a utility boost from having a job, and call it the "dignity of work". You can model the alienation of arm's-length market transactions as a transaction cost, and remove this cost for long-term informal contracts. Almost anything, except for some fairly exotic behavioral biases, can be dealt with using the standard tools of utility maximization and cost minimization that every econ student learns in school.

So why do economics classes, papers, and policy recommendations so rarely include any of these things?

Part of it might just be an accident - or maybe two accidents. Non-market goods like love, trust, connectedness, patriotism, social obligation, fairness, dignity, etc. is usually really easy to put into models - too easy, in fact. Assuming the existence of something really important but really simple is not intellectually or mathematically impressive. It might be the most important thing in the world, but it won't help you look smart for a hiring or tenure committee.

And these non-market goods are also very hard to measure empirically. How do you measure them? What economic data is a proxy for social connectedness, inclusion, or dignity? They'll usually wind up as unobservable parameters, meaning that the data used to evaluate the models will not be super-informative. (Sociologists probably know more about how to do this, but they don't even post their working papers or blog very much, so who knows what they're up to?)

Social preferences, on the other hand, can be devilishly hard to model. Some people do do it, in highly specific, stylized settings (see here and here), and some people do study social preferences empirically (see here and here; thanks to the excellent Ivan Werning for these examples). But they're pretty tough to put into policy evaluation models, and probably too tough for most undergrad classes.

So there are some technical and institutional barriers to putting these things in economic models and in econ classes and textbooks. But I suspect there might be cultural barriers as well. Econ began in an age when severe material deprivation was the main problem afflicting humankind (as it still is in many countries). Economists of the 19th and early 20th centuries correctly grasped that rising material prosperity would override almost any other concern for the destitute masses of the world, if that prosperity became available.

But as soon as countries get past the stage of abject deprivation, non-market goods and social preferences probably become a lot more important. By sweeping these things under the rug, economists are probably A) nudging policymakers to ignore crucially important stuff, B) developing a reputation for being out of touch, and C) opening the discipline to allegations of irrelevance from people who want to see econ replaced with other ways of analyzing the world.

Interestingly, I think a lot of the progress in the public discussion of these things has come from conservative-leaning economists, whose free-market bona fides probably give them the political cover to openly discuss things non-market goods like social trust. That's a positive development, but economists on the other side of the ideological spectrum should probably get in on that game. To their credit, left-leaning economists often do discuss inequality aversion, but this is rarely translated into formal models or official policy advice.

Anyway, I think Arnade has a point, and economists should listen - even though I'm not sure what exactly needs to be done.

Tuesday, June 14, 2016

The pool player analogy is silly


In a lot of debates about economic methodology, someone will bring up Milton Friedman's "pool player" analogy. The pool player analogy was part of Milton Friedman's rationale for modeling the behavior of economic agents (consumers, firms, etc.) as the optimization of some objective function. Unfortunately, the analogy is A) not that good in the first place, and B) frequently misapplied to make excuses for models that don't match data.

Here's the original analogy:
Consider the problem of predicting the shots made by an expert billiard player. It seems not at all unreasonable that excellent predictions would be yielded by the hypothesis that the billiard player made his shots as if he knew the complicated mathematical formulas that would give the optimum directions of travel, could estimate accurately by eye the angles, etc., describing the location of the balls, could make lightning calculations from the formulas, and could then make the balls travel in the direction indicated by the formulas. Our confidence in this hypothesis is not based on the belief that billiard players, even expert ones, can or do go through the process described; it derives rather from the belief that, unless in some way or other they were capable of reaching essentially the same result, they would not in fact be expert billiard players.  
It is only a short step from these examples to the economic hypothesis that under a wide range of circumstances individual firm behave as if they were seeking rationally to maximize their expected returns (generally if misleadingly called “profits”) 16 and had full knowledge of the data needed to succeed in this attempt; as if, that is, they knew the relevant cost and demand functions, calculated marginal cost and marginal revenue from all actions open to them, and pushed each line of action to the point at which the relevant marginal cost and marginal revenue were equal. Now, of course, businessmen do not actually and literally solve the system of simultaneous equations in terms of which the mathematical economist finds it convenient to express this hypothesis, any more than leaves or billiard players explicitly go through complicated mathematical calculations or falling bodies decide to create a vacuum. The billiard player, if asked how he decides where to hit the ball, may say that he “just figures it out” but then also rubs a rabbit’s foot just to make sure; and the businessman may well say that he prices at average cost, with of course some minor deviations when the market makes it necessary. The one statement is about as helpful as the other, and neither is a relevant test of the associated hypothesis.
Actually, I've always thought that this is kind of a bad analogy, even if it's used the way Friedman intended. Using physics equations to explain pool is either too much work, or not enough.

Suppose the pool player is so perfect that he makes all his shots. In that case, using physics equations to predict what he does is a pointless waste of time and effort. All you need is a map of the pockets. Now you know where the balls go. No equations required! Actually, even that's too much...since in most pool games it doesn't matter which balls go in which pockets, you don't even need a map, you just need to know one fact: he gets them all in. It's a trivial optimization problem.

But if really good pool players made 100% of their shots, there wouldn't be pool tournaments. It would be no fun, because whoever went first would always win. But in fact, there are pool tournaments. So expert pool players do, in fact, miss. They don't quite optimize. So if you want to predict which pool player wins a tournament, or why they miss a shot, you need more than just a simple balls-in-pockets optimization model. And you probably need more than physics - you could use psychology to predict strategic mistakes, biology to predict how arms and hands slightly wobble, and complex physics to predict how small random non-homogeneities in the table and air will cause random deviations from an intended path. 

The point is, if you use an optimization model to represent the behavior of someone who doesn't actually optimize, you're going to get incorrect results.

Of course, the pool player analogy wasn't Friedman's whole argument - the next paragraph is critical:
Confidence in the maximization-of-returns hypothesis is justified by evidence of a very different character. This evidence is in part similar to that adduced on behalf of the billiard-player hypothesis - unless the behavior of businessmen in some way or other approximated behavior consistent with the maximization of returns, it seems unlikely that they would remain in business for long. Let the apparent immediate determinant of business behavior be anything at all - habitual reaction, random chance, or whatnot. Whenever this determinant happens to lead to behavior consistent with rational and informed maximization of returns, the business will prosper and acquire resources with which to expand; whenever it does not, the business will tend to lose resources and can be kept in existence only by the addition of resources from outside. The process of “natural selection” thus helps to validate the hypothesis - or, rather, given natural selection, acceptance of the hypothesis can be based largely on the judgment that it summarizes appropriately the conditions for survival. 
That turns out to just be wrong. There are plenty of theoretical ways that non-profit-maximizing agents can stay around forever. Also, there are always new people and new companies being born and entering the system - there's a sucker born every minute, so as long as they drop out at some finite rate, there's some homeostatic equilibrium with a nonzero amount of suckers present. And finally, this argument obviously doesn't work for consumers, who don't die if they make bad decisions.

So Friedman's analogy was not a great one even on its own terms. Sometimes consumers, firms, and other agents don't perfectly optimize. Sometimes that's important. So you might want to model the ways in which they don't perfectly optimize.

But actually, everything in this post up to now has been a relatively minor point. There's a much bigger reason why the pool player analogy is bad, especially when it comes to macro - it gets chronically misused.

In pool, we know the game, so we know what's being optimized - it's "balls in pockets". But in the economy, we don't know the objective function - even if people optimize, we don't automatically know what they optimize. Studying the economy is more like studying a pool player when you have no idea how pool works.

In economic modeling, people often just assume an objective function for one agent or another, throw that into a larger model, and then look only at some subset of the model's overall implications. But that's throwing away data. For example, many models have consumer preferences that lead to a consumption Euler equation, but the model-makers don't bother to test if the Euler equation correctly describes the real relationship between interest rates and consumption. They don't even care.

If you point this out, they'll often bring up the pool player analogy. "Who cares if the Euler equation matches the data?", they'll say. "All we care about is whether the overall model matches those features of the data that we designed it to match."

This is obviously throwing away a ton of data. And in doing so, it dramatically lowers the empirical bar that a model has to clear. You're essentially tossing a ton of broken, wrong structural assumptions into a model and then calibrating (or estimating) the parameters to match a fairly small set of things, then declaring victory. But because you've got the structure wrong, the model will fail and fail and fail as soon as you take it out of sample, or as soon as you apply it to any data other than the few things it was calibrated to match.

Use broken pieces, and you get a broken machine.

This kind of model-making isn't really like assuming an expert player makes all his shots. It's more like watching an amateur pool player until you he makes three shots in a row, and then concluding he's an expert.

Dani Rodrik, when he talks about these issues, says that unrealistic assumptions are only bad if they're "critical" assumptions - that is, if changing them would change the model substantially. It's OK to have non-critical assumptions that are unrealistic, just like a car will still run fine even if the cup-holder is cracked. That sounds good. In principle I agree. But in practice, how the heck do you know in advance which assumptions are critical? You'd have to go check them all, by introducing alternatives for each and every one (actually every combination of assumptions, since model features tend to interact). No one is actually going to do that. It's a non-starter. 

The real solution, as I see it, is not to put any confidence in models with broken pieces. The dream of having a structural model of the macroeconomy - one that we can trust to be invariant to policy regime changes, one that we can confidently apply to new situations - is a good dream, it's just a long way off. We don't understand most of the structure yet. If you ask me, I think macroeconomists should probably focus their efforts on getting solid, reliable models of each piece of that structure - figure out how consumer behavior really works, figure out how investment costs really work, etc. That's what "macro-focused micro" is really about, I think.

So let's put Friedman's pool player analogy to rest.


Updates

Chris House (who was the first person to ever introduce me to the pool player analogy) has a response to this post. But as far as I can tell, he merely restates Friedman's (flawed) logic without addressing the main points of my post. 

Saturday, June 11, 2016

Econ theory as signaling?


I don't expend much effort dissing macroeconomics these days, but every once in a while it's good to give people a reminder. I wrote a Bloomberg post about how academic macro (or more accurately, mainstream macro theory) has not really helped out the finance industry, the Fed, or coffee house discussions. The reason, as Justin Wolfers recently pointed out, is basically that DSGE models don't work. Brad DeLong then wrote a post riffing on mine, which is excellent and which you should read. A super-fun Twitter discussion then followed, part of which Brad storified for posterity.

But that leaves the question: Assuming Wolfers and DeLong and I aren't just blowing smoke out of our rear ends, and DSGE models really don't work, why do so many macroeconomists spend so much time on them? One obvious hypothesis is that a huge percent of their human capital is already invested in knowing how to do this technique, so they just keep doing what they know how to do, and teaching it to their grad students.

Another hypothesis could be that it's just an equilibrium of a repeated coordination game. Universities pay macroeconomists to do research, but they have absolutely no idea what good macroeconomic research is, so in practice they pay macroeconomists to do whatever other macroeconomists decide is good. Maybe since macro data is very uninformative, no one actually knows what good research looks like, so they all settle on some random thing - DSGE models. This is a kind of Kuhnian explanation.

Another hypothesis is politics - a small conservative old guard thinks that since DSGE is at some level based on RBC, forcing everyone to do DSGE will nudge macro toward anti-interventionist stances on fiscal and monetary policy. And they use their positions of influence at departments, journals, and professional organizations to enforce conformity among the younger, less politicized economists. I don't really buy this hypothesis, but someone usually brings it up.

Yet another hypothesis is that it's just fun for some people to do, or at least to watch other people do, this kind of theory. Paul Romer recently complained that "in the new equilibrium...empirical work is science; theory is entertainment." I'm sure there are people out there for whom this really is the case - I once saw V.V. Chari get very excited that he couldn't use a fixed-point theorem to prove the existence of a solution in one of his models, and had to resort to more exotic methods. Heh. 

But here's another hypothesis: What if it's signaling?

I've been very skeptical of the fad in which everyone invokes signaling to explain social phenomena. I'm also pretty critical of the signaling model of college - yeah, it's probably part of what's going on, but the signal is just too expensive (4+ years of the prime working years of millions of our most talented young people, wasted on signaling?). So I bet it's a smallish piece of the college puzzle.

BUT, when it comes to DSGE, I kind of suspect that signaling could be a bigger piece of what's going on.

That suspicion was probably planted in 2005, before I even went to grad school, by a Japanese economist I knew who had done his PhD at Stanford. He gave me his advice on how to have an econ career: "First, do some hard math thing, like functional analysis. Then everyone will know you're smart, and you can do easy stuff." That's paraphrased only a little (I can't recall his exact wording).

I then watched a number of my grad school classmates go into macroeconomics. Their job market papers all were mainly theory papers, though - in keeping with typical macro practice - they had an empirical section that was usually closely related to the theory. The models all struck me as hopelessly unrealistic and silly, of course, and in private my classmates - the ones I talked to -  agreed that this was the case, and said lots of mean things about DSGE modeling in general, basically saying "This is the game we have to play." Then all of those classmates went on to do much less silly-seeming stuff, usually more focused on empirics, usually for government agencies. Essentially, they followed the advice of that Japanese economist.

Finally, I noticed an interesting data fact. Theory papers are getting much less common in top econ journals, but are still prominent among job market papers. The pattern again looks the same - prove yourself with theory, then do more empirical stuff later on. Of course, this data is for all econ, not just macro, and some percentage is going to just be people in the micro theory field itself. Plus, the thing for job market papers is just one year. So it's far from a slam-dunk case, but it's another piece of evidence that seems to fit the pattern.

But OK, suppose signaling is going on. What's being signaled, why is it valuable, and why is it hard to observe directly? The obvious possibility is that it's signaling intelligence - that the ability to make DSGE models is just an upper-tail IQ test. That's valuable because A) in the long run, people with very high intelligence are going to do good research, and B) intelligence gets much harder to observe in the upper tail. If DSGE is an IQ test, though, the invention of tools like Dynare that make it easier to make DSGE models might push the profession toward a pooling equilibrium, lowering the prestige and/or the salary of macroeconomists.

But it might also be what Bryan Caplan calls "conformity signaling". If macroeconomics research is a coordination game (see above), and if the prevailing research paradigm is not really better than alternatives, then you probably want macroeconomists who are willing to "play the game", as it were. So DSGE might be an expensive way of proving that you're willing to spend a lot of time and effort doing silly stuff that the profession tells you to do.

So there it is: The Signaling Model of Macro Theory Research.


Updates

Of course, all this is predicated on the notion that DSGE models haven't really increased our understanding of the economy. Chris Sims, one of the smartest folks in the business, and a very empirically minded macroeconomist, is a defender of DSGE. And here's another DSGE defense. So again, my premise here could always just be wrong.

Also, there are a lot of DSGE papers I personally like, but they tend to be ones that ingeniously poke holes in other DSGE models. See this discussion in the comments for some of those. Also, a few other examples are here, here, and here.

If you want to know what I think is the actual problem with DSGE models, see my next post

Tuesday, June 07, 2016

Republic of Science or Empire of Ideology?


The Washington Post has a long story by Jim Tankersley about Charles' Koch's attempt to influence the economics profession with massive donations of money to large numbers of universities. Here are some excerpts:
Koch’s donations have fueled the expansion of a branch of economic research that aligns closely with his personal beliefs of how markets work best: with strong personal freedom and limited government intervention. 
They have seeded research centers, professors and graduate students devoted to the study of free enterprise, who often provide the intellectual foundation for legislation seeking to reduce regulations and taxes... 
From 2012 through 2014 alone, his charitable arm, the Charles Koch Foundation, donated $64 million to university programs. A tax filing from 2013 lists more than 250 schools, departments or programs that received grants from the foundation, in amounts that ranged from a few thousand dollars to more than $10 million at George Mason University in Fairfax, Va. Recipients include obscure liberal arts colleges, flagship state universities and members of the Ivy League.

Some donations flow to research hubs within an institution, such as Mercatus at George Mason and the Ed Snider Center for Enterprise and Markets at the University of Maryland, which ground their research in the belief that economic freedom — and less government intervention — is the key to increased prosperity. Some support faculty positions at schools such as Clemson University and Florida State University, which have long specialized in that same sort of research...
Koch no longer personally reviews those applications — his foundation staff does...Koch, though, has articulated a set of principles to determine who gets his money. He has prized researchers whose values, as he calls them, are rooted in an economic philosophy that aligns with his— the belief that economic and personal freedoms produce the fastest advancements in human well-being.
The Post's article is titled "Inside Charles Koch’s $200 million quest for a 'Republic of Science'". This is a reference to a 1962 article by Michael Polanyi called "The Republic of Science: Its Political and Economic Theory". In that article - which Koch cites as a big influence on his efforts - Polanyi says that research dollars should flow to the scientists whose work is supported by the scientific consensus. Tankersley drily notes:
[Koch's donation effort] raises the question of whether Koch has become, for university researchers, the sort of distorting force that Polanyi warns against.
Why yes. 

Koch is making a sustained, multi-hundred-million dollar effort to push the academic economics profession toward a libertarian ideology. This is a "Republic of Science" to the same degree that North Korea is a "Democratic People's Republic of Korea".

One way to see this is as a defensive reaction against the interventionist turn in economic thinking. On many issues, academic economists are now less pro-free-market than the general public. And the most famous public-facing economists now tend to be left-leaning rather than right-leaning - Hayek and Friedman have given way to Piketty and Krugman. So the Koch donation campaign might be an attempt by libertarians to stem the tide.

Another way is to see it as a defensive reaction against the overall leftward turn of academia. Many social science disciplines - anthropology, urban studies, social psychology, and probably sociology - seem to have been captured by leftist ideology to a greater degree than econ was ever captured by libertarianism, even in the 70s and 80s. Koch might be using his hundreds of millions to try to preserve econ as a bulwark against this leftist capture of social science.

A final interpretation is that Koch is just doing what Koch always does - steadily pushing libertarian thought on the world by whatever means seem most expeditious.

Whatever it is, though, I don't like it. Unlike Koch, and unlike many of the lefty social science types I've been having debates with recently, I don't believe that social science is an inherently ideological enterprise. And I think it sets back our understanding of the world when people try to flood any portion of academia with researchers whom they think will promote a certain set of conclusions.

I don't have much more to say than that, so here's one of my favorite Feynman quotes:
Our responsibility is to do what we can, learn what we can, improve the solutions, and pass them on. It is our responsibility to leave the people of the future a free hand. In the impetuous youth of humanity, we can make grave errors that can stunt our growth for a long time. This we will do if we say we have the answers now, so young and ignorant as we are. If we suppress all discussion, all criticism, proclaiming “This is the answer, my friends; man is saved!” we will doom humanity for a long time to the chains of authority, confined to the limits of our present imagination. It has been done so many times before.
A real "Republic of Science" would focus on an open-minded search for truth, not the enshrinement of one pre-decided dogma.


Updates

I also thought this passage from Tankersley's article was interesting:
None of the largest recipients of Koch dollars appear on a list of the most influential academic economic departments in the United States, as calculated by the research arm of the Federal ­Reserve Bank of St. Louis. Only one professor who works at one of Koch’s most-supported centers cracks a similar list that calculates the top 5 percent of influential economists in the research community 
Koch-funded researchers make a larger impact in the public arena. They frequently testify before Republican-led committees in Congress. Their work often guides lawmakers, particularly conservatives, at the state level in drafting legislation, and they have provided the foundations for judicial opinions that affect the economy on issues such as whether the government should intervene to stop large companies from merging.
It's possible that the Koch doesn't want to influence economic science itself, as much as he wants to sculpt its public-facing component. The end result could be two econ professions - a dispassionate, truth-seeking one occupying the upper levels of the ivory tower, at MIT and Princeton and Stanford, doing hard math things and careful honest data work that slowly trickles out through traditional media channels...and a second econ profession in the lower-ranked schools, doing a slightly fancier version of the kind of political advocacy now done by conservative think tanks. The former would have the best brains and the best understanding of the real world, but the latter would have much more policy influence and impact on the wider intellectual world. This is different from the wholesale yoking of science to ideology that I was envisioning, but it also doesn't seem like a pleasant vision of the future.

Many Koch money recipients have pushed back on Twitter, saying that unions and left-leaning think tanks also fund university research too. Of course, that does worry me too - maybe it's time for a general code of ethics for econ funding. But it worries me a lot more if A) the funding becomes the main source of funding for whole departments, B) it's hundreds of millions of dollars from one single source, C) it's explicitly ideological, and D) it seeks to make hiring decisions along ideological lines instead of simply funding research by existing profs.

There's lots of dirty stuff out there in econ, but the Koch effort just seems so huge and so unapologetically ideological that it's worth singling out. Quantity, as one of Koch's favorite authors once said, has a quality all its own.

A commenter talks about the situation at Western Carolina University. I've mainly been thinking about the science and policy-advocacy aspects of this issue, but education seems important as well.

Saturday, June 04, 2016

Do feathers fall as fast as iron balls?


Josh Hendrickson's Twitter account is @RebelEconProf, and his blog is The Everyday Economist. So if both these names are accurate, I can only assume that Josh adheres to Mao's theory of Perpetual Revolution!

That has nothing to do with this post, I just always wanted to say that.

What this post is really about is that Josh wrote a post about my Bloomberg post about Econ 101! So I decided to write a counter-rebuttal post. Hmm.

OK, let's back up. I have two basic criticisms related to Econ 101:

1. I think 101 classes don't include enough empirics.

2. I think 101 models often get misapplied in public discussions, a phenomenon I call "101ism".

Josh is arguing about (1). I think. Mostly. But I think he doesn't always quite get what I'm saying. Therefore, I will do - you guessed it! - a point-by-point response. You know you love em.

Josh:
Noah Smith’s dislike of Econ 101 seems to come from the discussion of the minimum wage. 
Not really, no. That's just one example. It's probably one of the more egregious examples when it comes to the quality of the public discussion, but in terms of 101 models not fitting the data, there are better examples. For example, immigration is a positive labor supply shock, and positive labor supply shocks push down wages, right? Well, no, not in reality. That debate is probably a lot more settled than the minimum wage debate.

Josh:
[Noah's] basic argument is that Econ 101 says that the minimum wage increases unemployment. However, he argues that: 
That’s theory. Reality, it turns out, is very different. In the last two decades, empirical economists have looked at a large number of minimum wage hikes, and concluded that in most cases, the immediate effect on employment is very small. 
This is a bizarre argument in a number of respects. First, Noah seems to move the goal posts. The theory is wrong because the magnitude of these effects are small? The prediction is about direction, not magnitude.
If a theory represents only one tiny piece of reality, should we teach that theory front-and-center, in intro classes, as the main lens through which we are to understand the world?

I say no.

Here's an analogy. Suppose I drop a feather and an iron ball off of the Leaning Tower of Pisa, at the same height. Which one hits the ground first? Correct answer: The iron ball. It's denser than the feather, so it is less slowed down by air resistance. In fact, it's not even close.

Now, Newton's laws (including the classical Law of Gravitation) are a lot more general than air resistance. You need to learn Newton's Laws, just like you need to learn supply-and-demand.

But if you teach Physics 101 kids that Newton's Laws imply that feathers and iron balls fall at the same rate here on Earth, you're going to be embarrassed when some smartypants kid points out that no, they don't actually. And then the kids are going to start thinking physics is quackery.

This is why Physics 101 teachers are careful to emphasize that Newton's Laws only describe motion well when you can neglect air resistance. And then they send the physics kids to a lab, where they can see how and when air resistance matters, by looking at the evidence.

Econ 101 teachers are not always so humble in their presentation of theories, nor do they always defer to the evidence as the ultimate arbiter. And because of this, Econ 101 students are going to grow up, and they're going to read a Nick Hanauer column saying econ is total bullshit, because we keep raising the minimum wage and it hasn't and they're going to think "Everything I learned in Econ 101 was wrong!" Then they're going to turn to alternate sources - ideological movements, wordy literary tomes, etc. - to help them understand the economy.

In fact, this has already happened to a substantial degree.

Anyway.

Josh:
Second, David Neumark and William Wascher’s survey of the literature suggests that there are indeed disemployment effects associated with the minimum wage and that these results are strongest when researchers have examined low-skilled workers.
OK, yeah, the debate surely isn't settled. Not as much as, say, the immigration debate. But meta-analyses show that the estimates of the studies with the largest sample sizes cluster at exactly zero effect. It seems to me that the people saying the short-term effect is quantitatively small haven't yet won, but they're winning.

Josh:
Forgetting the evidence, let’s suppose that Noah’s assertion that the discussion of the minimum wage in Econ 101 is empirically invalid is correct. Even in this case, the idea that Econ 101 is fundamentally flawed is without basis. When I teach students about price controls, I am careful to note the difference between positive and normative statements. For example, many students tend to see price controls as a “bad” thing. When I teach students about price controls, however, I am quick to point out that saying something is “bad” is a normative statement. In other words, “bad” implies that things should be different. What “should be” is normative. The only positive (“what is”) statement that we can make about price controls is that they reduce efficiency. Whether or not this is a good or a bad thing depends on factors that are beyond an Econ 101 course — and I provide some examples of these factors.
Josh seems a bit confused here about what I'm saying. I'm not arguing for the inclusion of normative economics in Econ 101. I'm saying that if you don't teach Econ 101 kids some evidence, you're getting the positive economics wrong.

Josh:
The value of Econ 101 is the very process of thinking through [the] possible effects [of a policy change like the minimum wage]. What effect we actually observe is an empirical question, but it is of secondary importance to teaching students how to logically think through these sorts of examples.
Here's a real difference in philosophy between me and Josh. Josh thinks that teaching kids how to think deeply about the implications of models is Job #1, and everything else is of secondary importance. I think that if people use the wrong model to think about real-life situations, then this kind of deep logical thinking becomes worse than useless. Thinking deeply about bad models just leads to yet more mistaken conclusions about reality. I think Job #1 is to figure out how to use evidence to tell good models from bad.

You can learn how to think deeply through model implications in your second-year classes, after you have a realistic understanding of how to know whether you should do so in real life. Theories are powerful tools, and I think the first lesson for any powerful tool should be how to use it responsibly.

Josh:
If you are a student who only learned the perfectly competitive model in Econ 101, then you should politely ask for a refund. Econ 101 routinely includes the discussion of externalities, public goods, monopoly, oligopoly, etc. All of these topics address issues that the competitive market model is ill-equipped to explain. 
On this point, Josh and I are in total and complete agreement. This is what I mean when I bash "101ism".

Anyway, thanks to Josh for responding, and I look forward to purging him and the other capitalist roaders from our glorious Cultural Revolution talking about this further!

And now, back to my regularly scheduled caffeine-overdosing.

Wednesday, June 01, 2016

Can social science yield objective knowledge?


I've been having a fairly epic email argument with a lefty* social scientist friend, about whether social science can give us objective knowledge about the world. Apparently, it has become accepted in lefty* social science and humanities circles that the study of human beings is an inherently subjective enterprise, and will never yield the kind of knowledge delivered by physics, chemistry, biology, etc.

There are essentially three arguments for this. Paraphrasing heavily:

1) Social science has policy implications, and so ideological bias will always leak in, affecting both researchers' methodological choices and their interpretations of conclusions.

2) Social phenomena are highly complex, and hence can never be understood in the way natural phenomena can be.

3) Social science = humans studying other humans, and "reflexivity" prevents us from understanding ourselves in the same way we could understand the behavior of ants or atoms.

I think all that each of these arguments highlights an important difficulty of doing social science, but gets the implications wrong.

In fact, in recent decades, a few very successful predictive social science theories have emerged that don't suffer much from any of these problems. My four favorite examples are auction theory, gravity models, matching theory, and random-utility discrete choice models. Each of these is not just very predictive, but very useful to humanity. They power Google auctions, allow people to forecast trade flows, improve organ transplants, let cities predict how many people will use the train, and allow humanity to do many other things.

Keeping these examples in mind, let's go through the (heavily paraphrased) arguments one by one.**


1) First, the presence of ideological bias. Yes, these days few people care about the policy implications of the orbit of Venus, while most people care about the policy implications of minimum wage studies. So these days, people are more likely to be objective about the former than the latter. But it was not always thus! There was a time when scientists were being put under house arrest (or worse) for saying politically incorrect things about the orbits of the planets.

Eventually, the facts won out. Natural scientists who ignored the prevailing ideology were able to predict the motion of the planets better than their rivals, and that basically settled it. There seems no reason, in principle, why a similar process wouldn't happen with social science.

Now, it might happen a lot slower, because really super-predictive social science theories are harder to get than super-predictive physics theories. But predictive success seems to drive out ideology, meaning that social science has a chance of being objective.

Some people think it's a good idea for social science researchers to lay their cards on the table - to admit their ideologies when they report their research results. That sounds like a nice idea, but I suspect it is not even slightly feasible in practice. Imagine an economist saying "From this natural experiment, I find the elasticity of labor supply with respect to minimum wage increases to be -0.1. Also, you should know I'm a lefty type who wants to use policy to help the working class."

Well, how much did the economist let said ideology affect said estimation? Did he underestimate the elasticity because he thinks that reporting a small number will make people more likely to enact minimum wages, which he thinks will help the working class? Did he overestimate the elasticity in a conscious or unconscious attempt to correct for his bias? Did he try to get an unbiased estimate, because he doesn't know whether minimum wage would help or hurt the working class, and he wants to find out?

Who knows??? Not him. Not the reader. So this sounds like a nice idea, but I don't think it would work in practice at all. In practice it would just lead to a lot of confusion, suspicion, and noise.


2) Second, complexity. Well, again, this is a big challenge in natural sciences too! Quantum mechanics and relativity have passed every empirical test, to arbitrary levels of precision. But will these things tell us how a tree grows? Maybe. But if so, that's certainly far in the future. Right now, there are plenty of phenomena too complex for particle physics to understand. That doesn't mean particle physics is incapable of yielding objective knowledge.

To me, the argument that social science phenomena are too complex seems quite a bit like the "irreducible complexity" that creationists use to argue for "intelligent design". Yes, you can always find some phenomenon so complex that existing theories can't (yet) explain it. And as theories get better and better, you can keep on jumping up to even more complex theories, saying  "Oh yeah? Explain that, scientists!". But that just means you keep losing and losing, as scientists get better and better at explaining the world.

I guess you can jump directly to the most complex, hard-to-study phenomena of all - macroeconomics, politics, and history - and camp out there for a good long while, constantly saying "See? Told you so! You haven't explained this stuff yet, and you never will!" And you're probably safe - you'll be in your grave before science explains these hellishly complex, probably-non-ergodic macro-phenomena.

Well, good for you! But in the meantime, the sphere of things that can be explained by science will expand...


3) "Reflexivity". The idea that humans can't study their own behavior. If you manage to make a theory that predicts human behavior, people's behavior will change so that the theory no longer works.

Well that's obviously wrong. Here's a very useful, robust law of human behavior that many humans have rediscovered over the years: if you walk up and threaten random humans with a deadly weapon, they'll probably hand over their money.

Obviously, reflexivity often matters. In economics there are plenty of examples. The Lucas Critique. The disappearance of asset market anomalies. I'm sure there are also tons of examples in other social sciences.

But there are obviously lots of situations in which it probably doesn't come into play very much. Epidemiologists figured out that when everyone washes their hands, disease has more difficulty spreading. So they made rules and public awareness campaigns trying to get people to wash their hands. The rules and campaigns worked, and now disease has a harder time spreading in rich countries. Reflexivity be damned! There are also plenty of examples in econ - the response to taxation, for instance, or the labor market effects of immigration - that have no obvious reflexivity problem.


So while ideology, complexity, and reflexivity are real challenges in social science, they don't seem insurmountable. They don't seem to represent a fundamental difference between social and natural science.

These arguments against objective social science really feel a lot like the "God of the gaps" reasoning that religious thinkers use to argue against the universality of natural science. Every gap in science's current ability to explain the world is presented as a reason to embrace religion - usually the specific religion of the person making the argument.

When it comes to social science, the "natural alternative" for the people making the above arguments isn't God, it's lefty* ideology. Into every gap in our current understanding of social phenomena should flow the conviction that the have-nots are oppressed by the power of the haves. Arguing with lefty* friends in the soft-sociology/anthropology/humanities complex feels a bit like arguing with a Catholic priest about science back in 1700. "You can predict balls rolling down ramps, but can you tell me when the next thunderstorm is going to happen? No you can't! See? Nature is inherently mysterious! Only the Bible will show you the truth!"

Social science is damn hard (and not just for the reasons described above). It'll be many years before predictive social theories get good enough to understand things like recessions, elections, or the rise and fall of great powers. Maybe it'll never happen. But that's not a reason to give in to ideological, desire-based worldviews. We should keep crawling forward toward a better and better objective understanding of the world.


*"Lefty" is not meant as a pejorative here. I just don't have a word for the Marxist-influenced, left-leaning idea/ideology package that has become dominant in the humanities and soft social sciences, along with the methodology of critical theory. It is a very broad, complex, multi-faceted idea/ideology package with no commonly accepted over-arching name, so "lefty" will have to do for now. If you know a better term, let me know.

**Obviously this is a one-sided exercise, since I'm responding to my own summaries/paraphrasing of the opposite side. But that doesn't mean it's a straw man. The concepts and ideas I put forth will be summarized and paraphrased in your own mind, and next time you encounter someone who says something kinda-sorta like the arguments I describe, you can use your internally summarized and paraphrased arguments to think about the filtered, summarized, paraphrased versions of that other person's arguments that appears in your own mind. The purpose here is to present ideas, not to definitively win an argument or settle a point.