What is opportunity? What is a "land of opportunity"?

A reader emailed me recently and wanted to discuss the issue of whether America is a "land of opportunity." Like many people, he was of the opinion that America's low intergenerational income mobility means that we're not the land of opportunity that many Americans think we are. He went on to speculate as to why Americans labor under this delusion.

But is it a delusion? As I see it, the question has as much to do with philosophy and semantics as it does with actual economics. It all hinges on what "opportunity" means, and what it means for a country to be a "land of opportunity."


Thought Experiment 1:

As a thought exercise, consider a world in which ability is 100% heritable; if your parents have abilities of 57 and 73, you will have an ability of 65, with absolute certainty. And suppose that in this world, income is purely a linear function of ability (I=kA, where k is a positive constant).

In this world, your income will just be the average of your parents' incomes. Intergenerational mobility, as measured by the likelihood of being in a different income class than your parents, will be zero at the individual level, and at the household level will be determined entirely by who you marry.

Is this world a "land of opportunity"? It's a pure meritocracy, after all. But no one's income differs from that of their parents.


Thought Experiment 2:

As another thought experiment, imagine a world in which income is determined entirely by luck. When you are born, a die is rolled that determines your lifetime income. In this world, therefore, no one's income will be correlated with their parents' income at all. There will be a very large degree of observed intergenerational mobility.

Is this a land of opportunity? You have the chance to be in a different income class than your parents, and your chance is just as good as anyone else's chance. But that's all it is - chance. You are completely at the mercy of the dice.


You may feel that one of these hypothetical worlds is a "land of opportunity," but I think you'll be in the minority. What about a combination of the two? If income were a weighted sum of inherited ability and pure luck, would that make us a "land of opportunity"? Would it depend on the weights?

I doubt many people would say "Yes." The reason is that inherited ability is just another kind of luck. If income is the sum of luck and more luck, it still probably doesn't feel like a land of opportunity. Luck just doesn't feel like opportunity to most people; that's almost certainly why low intergenerational mobility bothers people in the first place (because it implies your income is determined by the luck of your birth).

So what do we feel does constitute "opportunity"? I'm not sure, but after thinking about it, I think it has to do with a third variable: effort. I conjecture that we think of a "land of opportunity" as being "a place where hard work allows you to succeed."

If I'm right, this means that we value opportunity because it fits with a certain moral model that we have regarding rewards, punishments, and free will. We view humans as being able to freely decide how much effort to put forth; hard work is a choice. And we think society should be setup so as to reward hard work and punish laziness - to change the incentive structure of people's effort decisions so as to maximize the effort that they choose to put out.

Furthermore, I don't think we want this kind of society because of a concern for economic efficiency. Leisure is fun! Rewarding hard work does not necessarily increase utility, even if it increases production. Instead, I think that our desire to reward hard work and punish slot comes from a moral value judgment that work is good in and of itself.

This, I am guessing, is why the idea of a low-mobility society bothers people. If your parents' income determines your income, it means that working hard does not bring the rewards that it ought to bring. The people who are most concerned about low mobility are not, then, socialist types who want to redistribute outcomes; they are old-fashioned moralizers who want people to reward people for working hard. They are angry that Horatio Alger stories to rarely come true.

What does this mean for the debate about opportunity? Well, much of the pushback against the "low mobility" complaints has come from libertarian and conservative circles. But this fight may not be about differences in values - libertarianism vs. socialism - as much as it is a debate about facts on the ground. Libertarians and conservatives who claim that America is still a "land of opportunity" are saying that it's still the case that hard work still gets rewarded here, as it ought to be; and those who complain about intergenerational immobility are claiming that hard work isn't as rewarded these days as it ought to be. So I think both sides should realize that this is what they're arguing about.

As a final note, what about my own values? Well, I was raised to think that "equality of opportunity" was a good and desirable thing. But until today, I didn't really realize what that meant. And now I'm starting to question my own values! Do I really care about how much society rewards hard work for hard work's sake? I'm not sure if I do. Maybe there are other kinds of equality that I care about more...but that is a subject for another post...

Economists, release your inner nerd!

Time for a lighter post, on the culture of economics. (Warning: this post is tongue-in-cheek.)

Every field of study has its own peculiar conventions of how "very smart people" are supposed to act. If you're in physics, you should have unkempt hair, juggle or do some other unusual hobby, be sexually promiscuous, and try to make your intellectual achievements look effortless (i.e. you should do a Feynman or Einstein impression). If you're in computer science you should talk like a character out of a Neal Stephenson novel, use hacker jargon, and know every XKCD joke by heart. If you're in math, you should either act genuinely crazy (like Grothendieck or Perelman) or very soft-spoken and mild (like Fefferman or Tao) - i.e., you should convey the impression that you have a lot of very powerful software running in the background of your brain. I'm not sure what biologists act like, but it seems to include wearing a goofy grin all the time.

But all of these disciplines share some common markers of nerdiness. One of these is enthusiasm for new technologies. Another is a love of - appropriately enough - science fiction. the "gee whiz" attitude is an integral part of being a science nerd.

Economics is different. Very few economists read a lot of sci-fi (or, at least, are reluctant to admit it openly). At social gatherings, economists tend to discuss sports, politics, and money rather than augmented reality or driverless cars. They tend to be better-dressed and better-coiffed than natural scientists. In other words, they are a little bit like MBAs. In this way, economists show that they are about Business; that they are worthy of consulting gigs and Congressional testimony.

But economists can't be just like MBAs; they have to also show that they are Smart as well as Business. But if you can't show you're smart by quoting Vernor Vinge and gushing about Augmented Reality glasses,  what are you supposed to do?

Answer: Act like you have mild Asperger's. Don't pump people's hands when you encounter them at the AEA Meeting; stand there awkwardly as if you're not sure whether to shake their hand or not (then finally shake it). When discussing economics, pepper your explanations with excess formalism: instead of saying "figure out how the business cycle works," say "examine the joint time series properties of macroeconomic variables." Instead of "mean and variance," say "moments of interest." Talk...very...slowly...with...random...long... ... ... ...pauses. Drop the occasional politically incorrect comment, and then pretend you didn't realize you did it and apologize sincerely. If all else fails, start wearing Hawaiian shirts and make your hairstyle a combination of fauxhawk and mullet (OK, just kidding, don't do that).

But for Milton Friedman's sake, don't be a science nerd! If someone references Star Trek or Mass Effect, give them the hairy eyeball. Remember, "technology" has nothing to do with semiconductors or machine learning or General Relativity; "technology" is the Solow Residual! Economists evaluate technology from on high; we do not descend into the muck of knowing how it actually works. And remember: you do math well, but you don't like math, not for it's own sake. Do not gush about all the cool difficult math you just did, whine about it.

To sum up, let your social awkwardness indicate that you are a Smart Person, but let your self-consciously normal personality and appearance indicate that you are also Business.

OK, OK, I joke. But man, I wish that the economics profession would let loose its inner geek once in a while! Face it economists: you do math, stats, and coding for a living. It's too late; you are a nerd. You are not a backslapping deal-making executive or a trash-talking caffeine-guzzling Goldman Sachs trader. You are a scientist of some sort, or at least you should be. Embrace it! Watch Fringe. Grow your hair out. Learn to juggle.

Actually, I see some encouraging signs of a move toward nerdiness in the econ profession. Bloggers like Tyler Cowen, Karl Smith, and Robin Hanson are beginning to gush about the Next Big Thing in technology (while Brad DeLong regularly quotes all my favorite sci-fi authors). When he taught my macro field class, Miles Kimball kicked it off by talking about how in 100 years we'd all be cyborgs (a more optimistic variation on Keynes' quote about the Long Run).

Think about it. We are living in the Age of the Nerd. Economics is one of the last places where being a geek is not yet sexy. But the times, they are a-changin'. Live long and prosper.

Thursday Roundup (2/23/2012)

Almost forgot it was Thursday!

Hmm, some of my comments on these links are getting rather long. What do y'all think...should I start doing a bunch of mini-posts, or stick to long infrequent posts?

1. Barry Ritzholtz explains why trying to be an active investor without a supercomputer and a staff of trained finance professionals is a mug's game. Remember: Friends don't let friends day-trade.

2. Simon Wren-Lewis says what few are willing to say publicly: that macroeconomic arguments are really thinly veiled arguments about income redistribution. Is he right? I don't know. I'm a cynic, so I'll say "probably, a lot of the time."

3. Felix Salmon points out that tying company's fortunes to their short-term stock performance tends to destroy them. Very true. Remember that stock prices display excess volatility. Tying a company's fate (or the pay of an executive) directly to its stock price introduces a bunch of noise into the outcome of who lives and who dies (or who gets paid a lot and who gets paid a little).

4. Mark Thoma excerpts some recent NBER research on the importance of manufacturing. Interesting stuff. However, don't expect this to convince Ryan Avent.

5.  Steve Williamson flags and summarizes some very interesting research on chained transactions. I've been thinking about this in the context of counterparty risk for a long time, and I'm considering getting in on this research program.

6. Two Paul Krugman posts remind us why our intuition says fiscal stimulus works: A) GDP often seems to go up during wars, even though the things being produced are mostly destroyed, and B) cutting spending seems to deepen recessions. These are two big reasons that macroeconomists keep trying to make models in which stimulus works, even though the profession has not made it easy for them to make those models.

7. Brad DeLong flags a Larry Ball paper on hysteresis and unemployment. Very worrying stuff.

8.  Econ debate of the week: Arnold Kling says that if the output gap is negative, we should be seeing deflation. Ryan Avent says that no, low inflation by itself is enough to indicate a negative output gap. I tentatively score this debate Kling 1, Avent 1, which is just to say that I don't think anyone understands inflation dynamics well enough to know who's right here. If hysteresis is having a big effect, it helps Kling's argument.

9. Scott Sumner has a great post on why we should increase immigration from China.

10. Nick Rowe thinks we should stop thinking about money as a store of value, since all goods can be stores of value. But I think this is not right...since money can (under normal circumstances) be used to buy any good, we can expect the price of money to be less volatile than the price of any good. As a store of value, money gives you a real rate of return of -inflation (unless people ditch the currency for outside money), while any consumption good gives you a real return of -depreciation + change in relative price. Hence, I feel like money has special value as a passive investment vehicle...

11. And last but not least, Maria Popova discusses how to think like a scientist. Everyone should read this article, especially economists...

Scheduling Special Items

Back in July we posted an article about special limits on homeowner policies for things such as guns, jewelry, coins, cash, silver and furs.  In the wake of a string of burglaries in our area (burglaries that are only focused on taking cash, coins and jewelry), we felt it was important to remind people of the homeowner limitations on these items.  It differs per policy and per item but usually there is only about $1000 to $2500 of coverage given on the homeowners for things such as guns, jewelry, coins, cash, silver and furs.  If you own more than that limitation in any of the mentioned categories you should schedule the items on a special policy.  Feel free to contact Fey Insurance to make sure you have things appropriately covered.

On a side note, the current criminals who have been robbing homes in the area are first placing calls asking if you have a security alarm.  As soon as you answer no they hang up and then know your home is unprotected.  Be sure to never answer no to such questions over the phone to a random phone call.

Are macroeconomic methods politically biased?

In a recent post, Steve Williamson writes:

The tools of modern macroeconomics are no more the tools of right-wingers than of left-wingers. These are not Republican tools, Libertarian tools, Democratic tools, or whatever. These are the tools of Economic Science[.]

I've thought about this for a long time, and I'm not sure that Steve is right. I think there is a case to be made that the methodology of modern macroeconomics has the effect of biasing the field toward conservative policy recommendations.

Let me explain why.

Modern models of the business cycle generally rely on one of two techniques: 1) Dynamic stochastic general equilibrium models (DSGEs), or 2) Structural vector autoregressions (SVARs). The former is by far the more popular and well-accepted (although Chris Sims won the Nobel Prize for inventing the latter), so when I talk about "the methodology of modern macro," I'm going to talk about DSGEs.

One of the main features of DSGEs is that they are microfounded; that is, they try to explain macroeconomic phenomena in terms of individual decisions. Another feature is that they are based on optimization, which means that the individual decisions are modeled using the calculus of variations.

Explaining macro phenomena based on individual optimization is hard to do. Individuals may take many things into account when making their decisions; in math terms, this means you can easily have a large "state space." Also, the thing that people optimize (their "objective function") may be very complicated; in principle, it can include all manner of weird things like non-rational expectations, learning, dynamic inconsistency, habits, overconfidence, reference points and framing effects, etc. Finally, aggregating a whole bunch of individual decisions into one giant macroeconomic outcome is in principle a very hard thing to do; it's even harder if you include things like firms and governments.

So, unsurprisingly, making a DSGE model is a lot easier if you make some simplifying assumptions. Here are some simplifying assumptions that make a DSGE pretty easy to solve:

1. The assumption that the economy can be modeled with a representative agent; in other words, that the macroeconomy behaves as if there's only one person in it.

2. The assumption that government doesn't exist, or exists only to transfer income from one person to another.

3. The assumption that prices are fully flexible.

4. The assumption that firms are simple profit-maximizers and make zero profits in equilibrium.

5. The assumption that individuals have rational expectations.

6. The assumption that risk preferences can be entirely modeled using people's utility of consumption, and that this utility can be modeled using a small number of parameters that do not change over time.

7. The assumption that labor markets clear.

8. The assumption that "technology" is represented by the Solow residual, and that technology is exogenous and evolves according to a simple time-series process (for example, an AR(1)).

9. The assumption that the business cycles we observe represent small enough fluctuations that the model that describes them can be linearized around its steady state.

If you make all of these simplifying assumptions (and a few more), you end up with something like the first DSGE business-cycle model: the "Real Business Cycle" model of Edward Prescott and Finn Kydland, first published in 1982. This model, and the approach it pioneered, won a Nobel Prize for its authors.

Now, if the above assumptions seem unrealistic to you, that's because they are! And if you think that this makes the RBC model unlikely to fit the data, well, you're right. It doesn't.

(Side note: If Kydland and Prescott's model didn't fit the data, then you may ask, why was it awarded with a Nobel Prize? The answer is "nobody knows the mind of the Nobel Prize committee," but it is probably because this model was the first business-cycle model to try to answer the Lucas critique. The Lucas critique says that models should only contain "deep structural" parameters - i.e., parameters that won't change when government policy changes. Kydland and Prescott's model bases everything on "tastes" and "technology," which most economists at the time - and many even now - were willing to accept as "structural." Thus, it seemed to many people at the time that Kydland and Prescott had invented a modeling approach that had a good shot at one day explaining the business cycle in a way that wouldn't change when policy changed. Many macroeconomists still believe this, as evidenced by the dominance of the DSGE modeling approach in the macro literature.)

So, the DSGE model that is easiest to make (RBC) doesn't do a great job of describing the business cycle, much less predicting it. What would be better?

Fast-forward to 2007, and have a look at the Smets-Wouters model of the business cycle. This "New Keynesian" model is currently considered the "best" DSGE model in terms of forecasting performance. Which is to say, it performs ever so slightly better than the judgment-based forecasts of well-informed individuals. Consequently, some variant of the Smets-Wouters model is used by most central banks as their DSGE model of choice (which they use as a complement to other types of models, such as SVARs, reduced-form models, and judgment-based forecasts). Of course, the fact that Smets-Wouters is the "best" DSGE model does not mean it is very "good." Its forecasts are basically useless more than one quarter into the future.

Of course, this slight improvement on the original Kydland-Prescott model comes at a high cost in terms of the complexity of the model. Instead of one or two "shocks" (exogenous factors that are postulated to drive the business cycle), Smets-Wouters has seven. And there is a lot of doubt that all of these shocks are "structural" in the sense of the Lucas critique - in other words, there seems to be a pretty big chance that the parameters of the Smets-Wouters model would change if policymakers changed their policies (thus begging the question of why Smets and Wouters bothered to use a microfounded DSGE modeling approach in the first place).

Now realize this: It took 25 years to go from Kydland-Prescott's RBC model to Smets-Wouters. That is comparable to the time it took physicists to develop quantum mechanics.

And yet, despite being so complex, and despite making heroic assumptions about the "structural-ness" of certain parameters, and despite being 25 years in the making, the Smets-Wouters model does not come even close to capturing all of the "frictions" that people believe are at work in the macroeconomy. It does not include the financial frictions that many people believe caused the 2008 financial crisis. It does not include behavioral effects like habit formation, hyperbolic discounting, etc. It does not include learning. It does not include limited enforcement of debt contracts. It does not include hysteresis in labor markets. It does not include income or wealth heterogeneity among households or firms. And this is not even close to an exhaustive list of the relevant things that it doesn't include. To include all those things in one model is prohibitively difficult with current technology; the state space of the model explodes, and you would need a supercomputer to solve it if it could be solved at all.

So what this illustrates is that it's really hard to make a DSGE model with even a few sort-of semi-realistic features. As a result, it's really hard to make a DSGE model in which government policy plays a useful role in stabilizing the business cycle. By contrast, it's pretty easy to make a DSGE model in which government plays no useful role, and can only mess things up. So what ends up happening? You guessed it: a macro literature where most papers have only a very limited role for government.

In other words, a macro literature whose policy advice is heavily tilted toward the political preferences of conservatives.

Is that bad? Not necessarily. If the facts had a well-known conservative bias - i.e., if the models that fit the data best were the models that implied no role for government - then that would just be too bad for liberals! Liberals would have to accept that their ideas were contradicted by the best scientific evidence available.

But I contend that in the case of DSGE models, conservative policy recommendations don't emerge because they come from the best models, but only because they come from the easiest models. Thus, the conservative slant of modern macro comes not from the weight of evidence, but from the combination of publication bias and the inherent unwieldiness of the DSGE framework.

Now here's something else that might be worth mentioning. The DSGE framework was invented in large part by Ed Prescott, a man with deeply conservative political beliefs. The insistence that microfounded models with individual optimization were the only believable "structural" models - i.e., the only models that could answer the Lucas critique - came mostly from people with deeply conservative political beliefs (including Robert Lucas himself). And the criticism of alternative modeling approaches - in particular, of SVARs - seems to be much louder from economists with deeply conservative political beliefs.

That by itself proves nothing. (Maybe they're conservative because they believe the results of their models! Maybe conservatives are more scientifically honest!) But it seems like circumstantial evidence against the alleged political neutrality of modern macro methods.

Was DSGE created as an intentional conspiracy by conservatives to force macroeconomists onto a playing field tilted toward laissez-faire policy conclusions? Almost certainly not. Have conservative-minded macroeconomists been privately pleased with the publication dominance of models that tend to vindicate their prior beliefs? Almost certainly yes. Do I have a better alternative modeling approach handy? No (I'm not brave or foolish enough to mount a spirited defense of SVARs).

The real question, though, is: Has the "conservative publication bias" of DSGE made macroeconomists more complacent than they should be about searching for alternative modeling approaches, even in light of the extremely limited usefulness of DSGE models three decades after their creation? I don't know the answer. But if the answer is "Yes," then the claim that DSGE is a politically neutral tool of economic science is not quite right...

Update: It's worth pointing out that Thomas Sargent, one of the pioneers of both DSGE and Rational Expectations, and one of the three Nobel Prize winners in the photo at the top of the post, is actually a Democrat (though it's also worth pointing out that he left the Rational Expectations paradigm and started working on learning-based models, which have proven to be a lot harder to work with!).

Thursday Roundup (2/16/2012)

Your weekly dose of under-discussed econ bloggery:

1. PUBLIC GOODS MINI-BONANZA!
1a. Mark Thoma says we should be taking advantage of low interest rates to spend big on infrastructure. I agree.
1b. John Cochrane laments the fact that our government spends a lot more on transfers (mostly health care) than on infrastructure. Can he be joining the new Thiel/Tabarrok conservatism? I hope so!
1c. Eric Rauchway notes that much of the productivity improvements during the Depression were due not to great exogenous leaps in technology, but simply due to massive infrastructure creation. That is cool, and I didn't know that.
1d. Tyler Cowen links to an Ed Glaeser column on how to improve U.S. infrastructure spending.

2. Brad DeLong discusses the forward march of human liberty. Upshot: the post-WW2 20th century was pretty much all good.

3. DeLong also cites some very interesting thoughts on the British industrial revolution. The idea is that technological progress was made necessary by high labor costs and made possible by cheap capital. Does this mean that the flood of cheap Chinese labor might be holding back innovation right now?

4. Steve Williamson reveals why his antipathy toward Paul Krugman is so strong. Basically, he sees Krugman as anti-intellectual and anti-math.

5. Robert Waldmann and Mark Thoma discuss the differences between New Keynesian and Old Keynesian models of the macroeconomy.

6. Simon Wren-Lewis has a great discussion of the splintering of the macro field into "schools of thought."

7. Mark Thoma presents some alternatives to Tyler Cowen's ideas for the big banks.

8. Matt Yglesias harps on one of my very favorite topics - the fact that building and land-use restrictions have retarded the growth of Silicon Valley.

9. There are many worse things you could read than the writings of Menzie Chinn on global imbalances.

10. Greg Mankiw points out that I am his grandstudent.

11. Last but not least, an oldie but goodie: Scott Sumner on why the lack of small-sized recessions casts doubt on the idea that real shocks cause business cycles.

Separating Self-Insurance Facts From Fiction

Note: The following commentary appears in the February 20, 2012 edition of Business Insurance Magazine as part of its special spotlight report on self-insurance for the middle market.

Small and midsize companies are looking at self-insurance as a cost-effective health care benefits solution as Patient Protection and Affordable Care Act deadlines approach. Michael W. Ferguson serves as chief operating officer for the Self-Insurance Institute of America Inc., looks at facts and myths surrounding the decision to self-insure.

As more smaller and midsize companies look to self-insurance solutions to control escalating group health care costs in the wake of passage of the Patient Protection and Affordable Care Act, this proactive risk management approach has attracted increased negative attention from traditional health insurance industry and state regulators who warn of various calamities.

Of course, this criticism is largely predictable, as health insurance carriers are worried about market-share erosion, and state regulators don’t like the fact they cannot directly regulate self-insured group health plans because of Employee Retirement Income Security Act (ERISA) pre-emption. Nonetheless, it’s worth pointing out some of the more frequently repeated canards in order to help clear up any confusion this may cause for employers considering self-insurance.

But first the disclaimer: Self-insurance is not the best option for every employer, regardless of size. In fact, it could be a very bad option based on a variety of considerations. In this regard, it is highly recommended that employers engage in the same type of thorough due diligence they would rely on for any other major financial decision.

That said, let’s jump in and separate some important myths from realities.

Perhaps the most unfortunate allegation is that a primary motive for many employers to self-insure is that they can escape regulation, raising consumer protection concerns. While it is true that self-insured plans are not subject to state benefit mandates, there is no evidence to suggest that self-insured employers scrimp on covered benefits. In fact, it is widely acknowledged that self-insured plans incorporate more robust coverage terms for key health services because they have the ability to customize their plans to meet the specific needs of their employees.

And for employers switching to self-insurance since the passage of PPACA, they don’t evade any new substantive federal regulations—except those specifically geared for commercial health insurance carriers—because, by definition, they would establish “non-grandfathered” plans.

The reality is that self-insured employers actually subject themselves to more regulatory requirements because they are governed by ERISA, which prescribes strict federal rules for plan fiduciaries, among other requirements designed to protect the interests of plan participants.

Some critics also claim that self-insured health plans are more cost-effective because they deny claims at a higher rate than fully insured plans. But in a report issued by the U.S. Department of Health & Human Services last year, HHS-contracted researchers from RAND Corp. concluded that there is no evidence of such disparity.

Then there’s the belief that self-insured plan participants pay higher premiums than their fully insured counterparts. The available data does not support this conclusion, either.

As part of a U.S. Department of Labor report on self-insured health plans released last year, Deloitte Financial Advisory Services L.L.P. and Advanced Analytical Consulting Group, Inc. found that from 2009 to 2010 for employers with more than 200 covered lives, the average per employee premium contribution to be covered by fully-insured plans increased by $808 compared to average increase of $248 for self-insured premiums.


Most recently, influential academics and public policymakers predicted that such self-insured plans would contribute to adverse selection when insurance market reforms are fully implemented, suggesting that employers would switch back and forth between self-insured and exchange-offered plans based on their claims experience on a yearly basis.

That’s a nice conspiracy theory for sure, but it does not match up with marketplace realities. The fact is that due to ongoing administrative and compliance requirements, employers cannot simply switch their self-insured plans on and off.

Moreover, once an employer transitions to a fully insured health plan, it loses possession of claims data, which makes it more difficult to re-establish a self-insured plan in the future regardless of other considerations.

Claims data is arguably the most important health plan asset, as it can help employers control future health plan costs and can be used to customized plan design details. Giving up this asset over one bad claim year is not a decision to be taken lightly by plan sponsors.

The health care marketplace is certainly evolving, creating shifting roles for self-insurers, commercial health insurance companies and public sector payers. All three industry segments contribute in different ways to ensure that coverage is as available and affordable for the widest population possible.

Those who disseminate misleading information about any of these segments do a disservice to the ongoing public dialogue on how to improve the country’s health care system.

How I survived the Econ Job Market

Come fall, I will collect my PhD from the University of Michigan and go to work as an assistant professor of finance at the Stony Brook University College of Business. It's a really excellent department, full of smart, good people doing interesting research, and it's in a really nice location, and, well, I'm very happy to be going there.

For me, this concludes the rite of passage known as the "economics job market" (or, to economists, simply "the Job Market"). It is difficult to overstate how important a component of the economics grad school experience the Job Market is. I'd always intended to do a lengthy post about the process, just to give outsiders a little taste of what it's like (kind of like I did with my first-year macro course). The problem is, when it came time to go on the Job Market, I went about it all wrong, ignoring or simply failing to follow almost every piece of advice that grad students receive. This is not to say that that advice is wrong; it's good advice! I'm just saying that I am a very unusual case, and therefore not the best person to be writing this post.

But heck, I'm going to write it anyway. Just keep in mind, my own approach is more of a "don't try this at home" kind of thing.

(Note: Economists can obviously skip most of this, since you know it already. For PhD students, I recommend reading John Cawley's guide to the job market instead of listening to anything I have to say. The following account is primarily for non-economists who want a window into our secret world.)


What is the Job Market?

The Job Market is the main process by which PhD economists get jobs, though not the only process. There are plenty of jobs outside the Job Market, which you get by applying in the normal way (cold calling, resume mailing, connections, etc.). But the Job Market has three advantages, namely:

1. The job advertisement, application, and interview processes are all centralized,

2. You get the resources of your academic department to help you send out your applications, and

3. You are almost completely assured of getting some sort of job at the end of the process.

Jobs that are included in the Job Market are almost all posted on one website: Job Openings for Economists, which is run by the American Economic Association. You find the jobs you want to apply for, you send a list of these to your department, and you find three or four people to write you letters of recommendation.

The department then does two things. The administrative people forward your letters to the employers, and the Placement Coordinator tries to help identify good targets to call and recommend you directly. (Here's a good place for me to give special thanks to Chris House, this year's Placement Coordinator at Michigan, who did a bang-up job, and put up with my unorthodox behavior with consummate patience.)

After applications go out, employers contact grad students for interviews. These interviews take place at the AEA's Annual Meeting in early January, which is a gigantic confab where most of the economists in the country go to eat free food and hobnob. As an interviewee, you generally don't have time to go to any of the presentations or speeches; you're running back and forth from hotel to hotel, going to interview after interview. This year's AEA Meeting was in Chicago.

You then wait a week or two, and the employers who are interested in you call you back and schedule a flyout. Flyouts, which happen in February and March, involve going to the place, meeting the people, getting taken to dinner, and presenting your research. After that, offers go out.

There is also something called the "Secondary Market" or "scramble," in which people who don't get jobs through the aforementioned process get matched with employers who couldn't find anyone to fill their slots. I don't know exactly how this works, but I think the Placement Coordinator has to do a lot of work, making phone calls and such. The sense I get is that essentially everyone at a top 50 school eventually winds up with some kind of job.

Which, if you think about it, is pretty awesome. Especially as things currently stand in our economy. Being an econ grad student has its drawbacks, but joblessness afterward is definitely not one of them.


What do you need in order to go on the Job Market?

You need a Job Market Paper, or "JMP." This is a piece of original research, usually the first chapter of your dissertation.

That's it! Really! That's all you need! In the words of the great professor Yusufcan Masatlioglu, "All you need is that one damn paper."

At your AEA Meeting interviews, you will mainly discuss your JMP. At your flyout, you will present this paper. You don't need to have published this paper; in fact, you don't need a single academic publication (most people save publishable papers for when they are already working as assistant profs, where the papers will count towards tenure). "All you need is that one damn paper."

The JMP is to economists what a demo reel is to animators. Although the research should be original and at least mildly interesting, the main purpose is to show off your skills - be they DSGE modeling, time series econometrics, game theory proofs, the ability to find novel instruments, or whatever. Whether or not you obtain a world-changing result is less important.

Actually, this is one area in which I didn't do the normal thing. My JMP (which you can read here) is more about an interesting result and a novel methodology than it is about showcasing my skills. Although I showed that I could run experiments and work with panel data, I didn't show the time-series econometrics or DSGE modeling skills I learned in my classes and in other research projects, and I definitely didn't show off any of the math skills that I have from my physics background. So my JMP, while (in my opinion) an interesting paper, wasn't really a complete "demo reel." That was risky.

For other examples of JMPs, check out the excellent papers of my fellow Michigan job candidates David Agrawal (tax), Jesse Gregory (labor/urban), Collin Raymond (micro theory), David Ratner (macro/labor), Caroline Weber (tax), Roy Chen (experimental), Gabriel Ehrlich (macro), Nora Dillon (labor), Bill Lincoln (trade), Noam Gruber (macro), and Brad Hershbein (education).


What kind of jobs do economists want from the Job Market?

Most economics grad students really, really want an academic job. It's part of the grad school culture to believe that academic jobs (or jobs at the Federal Reserve) strictly dominate all other kinds, regardless of money, location, or quality of the institution. (Keep in mind, I have no hard data to back this up, but this is just kind of the sense I get.) Consulting, for example, even though it pays more, is definitely viewed by most grad students as a fallback option. Maybe this is just because as a student in an academic department, you're surrounded by professors who chose the academic way of life, and so tend to think it's the greatest. And I guess if PhD students just wanted big bucks, they'd have gone for Masters in Financial Engineering instead.

Like most applicants, I applied to a mix of academic, private-sector, and government jobs; although I wasn't as dead set on academia as some of my peers, it ended up clearly being the best choice for me, given the quality of the department at Stony Brook.

Job Market applicants are strongly encouraged not to have location preferences - i.e., not to rule out any region of the country. I cant tell you how many times I heard this! "No location preferences!" But I had strong location preferences, and so in this way I totally flew in the face of everything I was told (sorry, Chris!). I wanted to live on one of the coasts, in or near a large city, preferably a place where I already knew a lot of people. So I ended up applying to far fewer places than most of my peers: whereas a normal Job Market candidate usually applies to about 120 places, I applied to only about 80. This meant that I got correspondingly fewer interviews at the AEA Meeting (14, which is slightly below the Michigan average). In the end I lucked out, finding a job in the NYC area where I have a number of friends. But stubbornly sticking to my location preferences was clearly a risky move ex ante.


What kind of Job Market candidates do the best?

In general, academic employers want someone who can publish a bunch of papers in top-ranked journals. Non-academic employers are rumored to want whoever the academic employers want, and some say that they content themselves with taking the people who didn't get the academic jobs (again, this seems weird to me, but whatever).

Academic departments often have "slots" to fill. Economics, as a profession, is divided into fields, and so a department will often look for a "macro person" who will be assumed to do things like DSGE macro models and VARs, or a "tax person," who will do, um, tax stuff. Etc. You signal what "slot" you will fill by what kind of things you put in your JMP, by what field classes you took, and to a lesser extent by what you say in your cover letter.

Yet another way in which I didn't take the usual path was in terms of what "slot" I went for. I took macro as my main field class, but my JMP, while relevant for macro issues, was not the kind of thing that macro people usually do. My JMP was an experiment. However, I also didn't apply to any of the traditional "experimental econ" schools (e.g. Texas A&M). So I was a bit of an unusual applicant, difficult to fit into a pre-existing slot. This probably hurt me somewhat; while in good hiring years, schools are much more likely to gamble on an idiosyncratic or unusual type of researcher, in bad years they are much more averse to that sort of risk...and this was not a good hiring year. It was definitely a big ex ante risk not to go on the Market in one of the standard categories.


What are the advantages and disadvantages of the way the Job Market is set up?

This part is purely subjective, of course.

The way the economics profession runs its Job Market has obvious advantages. With a centralized, standardized application system, you can send out a lot of applications in a relatively small time. The single location of the first-round interviews is incredibly convenient. And the fact that all the interviews and flyouts happen within a short space of time allows employers and candidates alike to weigh all their options and select the best fit (it also allows competitive bidding and negotiation). So as a market, I have to say that the Job Market works very well - exactly what we'd expect from the economics profession.

But I must say, the centralized system does seem to have some drawbacks. For one, the structure of the market forces departments to pick and choose where they push their own candidates. Typically, there will be a small number of "stars" that the department pushes very hard, in the hopes of getting them into top schools. The knowledge that there can only be a few of these "stars" is not lost on first- and second-year grad students. That can be stressful.

In general, the Job Market is very stressful for most of the people who participate in it, and not only because one's future hangs in the balance. The fact that everyone is doing the same thing at the same time, and judging their success by essentially the same criteria, invites people to spend their time comparing themselves to their peers instead of thinking about their own individual preferences and what they really want to do with their lives. This comparison is so frenzied and intense that the Job Market has its own anonymous forum, Economics Job Market Rumors, where the gossip flies fast and thick (here's a thread about yours truly; here's a second, and a third).

In fact, I must say that the whole process has a slightly unpleasant whiff of a hierarchical culture (the profession) telling people what to want in life, defining a game and then convincing people that winning that game is all that matters. I can't help being reminded just a tiny bit of the Japanese college entrance exam system.

I suppose that the latter is a big part of why I personally took such an unorthodox approach toward the Job Market. Instead of focusing on winning the game, I focused (perhaps excessively?) on doing only what I wanted to do. I wanted to do research that I thought was interesting, so I did it. I also wanted to apply only to places where I would really want to work, and so I did that too. I took the advice of the great urban economist Masahisa Fujita, who once told me just to do what I wanted to do and not to worry too much about where I ended up. That approach succeeded in lowering my stress level dramatically during the Job Market process (though it probably slightly raised the stress level of my dissertation committee and Michigan's Placement Coordinator, for which I apologize).

In the end, I found a great job; statistically speaking, I got lucky. The vast majority of economics job-seekers will benefit from being significantly more orthodox than I was, even if it comes at the cost of more temporary stress.

Anyway, the ever-exuberant anarchist in me looks at the Job Market and says: "Pah, look at this rigid apparatus of social control! Blow it all up. Decentralize it and leave everyone to their own devices. Let job seekers think about what kind of job and what kind of life they want instead of where they rank." But the pragmatist in me says: "No, this system works well. It's relatively quick and low-effort, and it ends up nearly guaranteeing a job to people who participate in it. That far outweighs the downsides." The pragmatist wins. And hey, the Job Market ended up working for me, so what do I have to complain about anyway?

(Final Note: In addition, I'd like to give special thanks to my thesis committee members, Miles Kimball, Bob Barsky, Uday Rajan, and Yusufcan Masatlioglu, for the nearly absurd amounts of help they've given me; Dave Agrawal and Jeff Smith, for all the valuable job-market advice; and, of course, Vinnie Vinjimoor of the UMich econ department front office, for being the most competent human being on the face of the planet.)

Chucking the Solow growth model, cont.

A few posts back, I wrestled with Jim Bullard's hypothesis that a fall in asset prices caused a permanent negative shock to GDP. Since then, a whole bunch of people have weighed in with interesting comments.

Scott Sumner and Paul Krugman raise the first of the two issues I had raised: It is tough to interpret housing price changes as destruction of the capital stock. I can actually think of a few ways that housing price changes might affect productivity, and so can Brad DeLong, but I think we both agree that the change would be second-order.

David Andolfatto conjectures that regime-switching models of productivity growth - a sort of modified RBC model - could produce the kind of effects Bullard is talking about. But I don't think that's quite right, at least not the models that Andolfatto is talking about. In those models, asset prices fall because productivity falls; asset price changes are not the cause of changes in output, as Bullard hypothesizes.

What I find more interesting is this older Andolfatto post, which David kindly linked me to in the comments. It points to a model by Robert Shimer in which real wages are sticky. In that model, destruction of part of the capital stock does, in fact, lead to a permanent fall in GDP. (It does represent a chucking of the Solow growth model, because in the Solow model, real wages are not sticky. Shimer's model will not exhibit the conditional convergence that is the Solow model's main result.). This is very interesting. I'll have to take a closer look at the model, to see exactly how it works. If this model matches reality, then my second problem with Bullard's hypothesis is no longer a problem.

Right off the bat, I have some doubts about Shimer's model. Rapid growth after wars and natural disasters is a common phenomenon. And the evidence for conditional convergence is pretty strong. But the later part of Shimer's paper replaces the "real wages can never change" model with a model of search frictions in which real wages eventually move, slowly enough to cause jobless recoveries but presumably quickly enough to allow conditional convergence in per capita GDP across countries. That seems a lot more believable, though it still doesn't explain the "bounce back" from wars and disasters. Anyway, like I said, I'll have to take a closer look at the paper to see if the model makes sense.

So, assuming Bullard has in mind a model like Shimer's, we still have the question of why a fall in housing prices represents destruction of the capital stock.


Update: Jim Bullard responds. It appears what he had in mind is something like this:

1. The "trend" rate of growth had slowed in the 2000s, for whatever reason (technology slowdown, etc.).

2. However, self-fulfilling (but unrealistic) expectations about asset prices temporarily pushed GDP growth above its new, lower trend.

3. The end of that expectations-fueled boom sent the economy back to its new, lower trend growth path.

Not sure if I've got it entirely correct, but that seems to be the gist. It does not rely on destruction of the capital stock to explain the recession, rendering the rest of this post largely irrelevant (though interesting nonetheless).

Readers of this blog will know that I am very sympathetic to the idea of self-fulfilling expectations, sunspot equilibria, etc. I do still have one problem with this story, though. For this kind of story to produce a one-time permanent drop in GDP followed by resumed growth at the old trend rate, it would have to be that the 2000s housing boom masked a productivity slowdown that is now over. That could happen, sure, but I'd like to see some evidence before I believe it. Also, it would leave a puzzle as to why inflation was low during the bubble...

Is Identity Theft Coverage For You?

Consulting firm Javelin Strategies and Research reports more than 11 million people are affected by identity theft each year, at a cost of $54 billion to the victims. In trying to deal with this threat, the insurance industry has developed products to help a policyholder recover from this kind of loss. The monetary loss is not the only issue with identity theft. A victim can spend thousands of dollars and hundreds of hours trying to clean up credit records due to the thief using personal information to obtain credit with no intention of repayment, thus destroying the victim’s financial reputation. Identity theft insurance protection is designed to help you with this problem by covering expenses and sometimes professional services, that will help the victim recover from this type of loss.

Even with coverage provided, following simple steps can help protect you from this threat:

Shredding documents. Anything that contains sensitive information absolutely must be destroyed. There are specific documents that must always find their way to the shredder.
Old Tax Returns. Unless the IRS suspects you of fraud in your tax filings, you are usually only exposed to the threat of an audit for three years at a time. The National Endowment for Financial Education advises you to keep three to four years of tax returns, and shred anything older. Your tax return contains sensitive information, primarily social security numbers.
Bank Statements. Anything with bank account numbers should be shredded, including paper bank statements.
Credit Card Offers. These offers should go from the mailbox directly to the shredder, unless you are actually going to take the bank up on its offer. A lot of identity theft happens within families, so don’t leave these offers lying around.
Old Photo IDs. These IDs contain information, which by itself is probably not enough to be damaging, but used with other information could help perpetrate a fraud.

Pay Stubs. Absolutely shred your pay stubs. Some financial institutions will ask you the amount of your last deposit to use as a validation. A past pay stub can give that information.
Credit Card Convenience Checks. The most dangerous thing you can receive in your mailbox are convenience checks often sent with your credit card bill. These represent a live loan to whoever holds this check. Shred these immediately.
Canceled Checks. Canceled checks contain not only your account and routing numbers, but also your address and possibly your phone number. People often include their full account or credit card number in the memo section when paying with a check. Do your duplicate checks display your account and routing numbers? Don’t overlook these carbon copies.

Don't expect "expected" returns

Reading this article on PIMCO, I was struck by the following line:

Industry analysts also wonder whether PIMCO's $250 billion Total Return Fund, the world's largest bond fund, is such a behemoth that Gross sometimes has to swing for the fences to generate the kind of returns investors have come to expect.

Think about this for a minute. It may seem very natural to you that people who pay large fees to a company to manage their wealth should expect that company to earn them a higher return than they would earn if they just stuck their money in a low-fee index fund.

But does this expectation make sense in the long run? Suppose you gave $1M of your money to a hedge fund with an awesome brilliant manager who was incredibly talented at picking bonds that were going to go up in price. Soon your money doubles to $2M, then to $4M, even as the average bond price goes up only a little bit. You keep your money invested with the same manager (paying the same high fee), assuming that he will continue to double your money in the same amount of time, again and again. But as the manager accumulates a bigger and bigger share of the total bond market, it becomes harder for him to beat the market average.

To see this, just imagine if your hedge fund manager did so well that pretty soon he was managing the wealth of every bond investor. In that case, it will be impossible for him to beat the market, because he is the market, literally. So it makes no sense to expect the same excess return (i.e. the same percentage points of market-beating performance) year after year.

In your intro finance textbook, you will learn that various investments have various different expected rates of return. These expected rates of return may vary randomly, but they are not believed to decrease over time. Does that contradict what I just told you?

No, it doesn't. It's theoretically possible for stocks to go up by, say, 3% a year more than bonds forever and ever (or at least for a very very long time). Comparing one asset class to another is different than comparing one asset to the average performance of its asset class. To see this, note that it's possible for Apple stock to earn a 5% higher return than RIM stock forever, but it's not possible for Apple stock to earn a 5% higher return than the average of Apple and RIM stock forever, since eventually Apple will dominate the average.

Note that this is not Efficient Markets theory. This is just arithmetic. But the more "efficient" markets are, the quicker it will become impossible to beat the average as you grow in size, because the available mispricings that you can exploit to get excess returns will be more limited.

So here's the lesson: if investors "expect" an asset management company to beat a comparable index fund by the same number of percentage points year in and year out, they will be disappointed, because the company will soon get so big that it is almost indistinguishable from an index fund (except that it will have higher fees). Such fixed expectations of excess returns are not rational. But if investors do have such expectations, asset managers will have an incentive to accept greater and greater risk in order to have a chance of holding onto their clients. This is exactly what that article says is happening with PIMCO.

We REALLY need a Peter Thiel conservatism!

Peter Thiel is a little bit of a nutcase. He's a brilliant nutcase, though. And brilliant nutcases are exactly the kind of people who change the political discourse. Reading this Peter Thiel interview, I am more and more convinced that Thiel is the brilliant nutcase we need to move the American conservative movement out of its current rut and turn it into something that has relevance for the future.

Here are some things I learned from the interview.

1. Peter Thiel believes that inequality can reduce economic efficiency by causing sudden, devastating collapses in institutions:

We’re now at an extreme comparable to 1913 or 1928; on a worldwide basis we’ve probably surpassed the 1913 highs and are closer to 1789 levels [of inequality].  

In the history of the modern world, inequality has only been ended through communist revolution, war or deflationary economic collapse.

If you endogenize the possibility of social collapse, equality of income and wealth becomes a public good (up to a point).

2. Peter Thiel seems to think that we should think about how to make government more efficient, instead of drowning it in a bathtub:

There are ways that the government is working far less well than it used to. Just outside my office is the Golden Gate Bridge. It was built under FDR’s Administration in the 1930s in about three and a half years. They’re currently building an access highway on one of the tunnels that feeds into the bridge, and it will take at least six years to complete... 

There’s an overall sense that in many different domains the government is working incredibly inefficiently and poorly. 

3. Peter Thiel thinks that the package of conservative ideas that emerged in the Reagan years, and which dominates conservative thinking even to this day, has outlived its usefulness and must be replaced:

[T]hough I identify with the libertarian Right, I do think it is incumbent on us to rethink the history of the past forty years. In particular, the Reagan history of the 1980s needs to be rethought thoroughly. One perspective is that the libertarian, small-government view is not a timeless truth but was a contingent response to the increasing failure of government, which was manifesting itself in the late 1960s and early 1970s. The response was that resources should be kept in the private sector. Then economic theories, like Laffer’s supply-side economics, provided political support for that response, even if they weren’t entirely accurate. We can say that the economic theories didn’t work as advertised... (emphasis mine)

I have been saying this for a long time. The idea that "government is the problem" may have had considerable truth and usefulness and relevance in 1980; today, it is more of a calming mantra than a feasible policy prescription. Conservatism needs something else.

4. Peter Thiel believes in a version of Tyler Cowen's "Great Stagnation" idea, but is more subtle than Cowen, because he doesn't try to argue that the IT revolution was a mirage; he simply believes that it wasn't enough to compensate for the slowdown in other areas:

I believe that the late 1960s was...when scientific and technological progress began to advance much more slowly. Of course, the computer age, with the internet and web 2.0 developments of the past 15 years, is an exception...  

There has been a tremendous slowdown everywhere else, however. Look at transportation, for example: Literally, we haven’t been moving any faster. The energy shock has broadened to a commodity crisis...I think the advanced economies of the world fundamentally grow through technological progress, and as their rate of progress slows, they will have less growth. This creates incredible pressures on our political systems. I think the political system at its core works when it crafts compromises in which most people benefit most of the time. When there’s no growth, politics becomes a zero-sum game in which there’s a loser for every winner. Most of the losers will come to suspect that the winners are involved in some kind of racket. So I think there’s a close link between technological deceleration and increasing cynicism and pessimism about politics and economics. 

I couldn't agree more. Energy is where the slowdown is, and that affects everything else (though IT is affected less). And yes, a technological slowdown will make politics more of a zero-sum game, with all kinds of awful consequences (example: all of human history before the mid-1700s).

(Interestingly, the interview reveals that Cowen's book was heavily inspired by Thiel's ideas. See? Brilliant nutcases moving the political discourse!)

5. Peter Thiel believes that much of our inequality is due to factor price equalization, caused by the massive dump of Chinese labor onto global markets:

As for why inequality has gone up...I would say globalization has played a much greater role [than other factors] because it has been the much greater trend...The question is, what is there about globalization that creates a winner-take-all world? There certainly has been a labor arbitrage with China that has been bad for the middle class, as well as for white-collar workers, in the past decade or two. 

I agree with this, though I think that our wage stagnation itself may also be worsened by the labor arbitrage,   as we replace expensive automation with cheap Chinese workers. Thiel hints at this idea in his interview, but doesn't go there.

6. Peter Thiel thinks that the government should be more hands-on about industrial and technology policy, not less:

[T]he unplanned statistical view of the future is that we don’t know what energy technology will work, so we’ll experiment with different things and see what takes off. The planned view says that two are most likely to be dominant, and so the government has a role to play in coordinating resources and making sure they work. So if it’s nuclear power, it has to free up space at Yucca Mountain, deal with zoning rules and get plants built, and it’s a complicated project at the regulatory level. The same is true of solar or wind power. If government wants high-speed rail, it must overcome local zoning rules...

[N]o one at a senior level in the Administration even thinks about the question of technology. It’s assumed to be a statistical, probabilistic thing...This is a radically different position than, say, that of John F. Kennedy, who could talk about the nuts and bolts of the Apollo space program and all the details of what was needed to make it happen... 

If there is going to be a government role in getting innovation started, people have to believe philosophically that it’s possible to plan. That’s not the world we’re living in. A letter from Einstein to the White House would get lost in the mail room today. (emphasis mine)

It strikes me that there is a huge opening for conservatives here. Ever since the success of the Clinton years, many liberals have come out against industrial policy (possibly to burnish their "seriousness" credentials in a policy world dominated by neoclassical economics). This gives conservatives an opportunity to be the ones to champion a new era of technology policy: to say "Look, the government's role should not be to throw more money at health care, it should be to do the kind of planning and coordination of technological progress that companies are unable or unwilling to do." This will require conservatives to throw off a lot of the "libertarian" dogma that became canon after the Reagan years. But far-sighted libertarians like Alex Tabarrok are already making this argument, so I see a lot of reason for hope.

Anyway, I agree with and endorse all six of the Peter Thiel positions listed above. That's right - I am saying "ditto" to the man who created the Stanford Review. Well, not "ditto," since Thiel also has a number of opinions with which I strongly disagree (and others about which I'm highly skeptical). An example would be his idea that environmental regulation has played a large role in the technological slowdown. (And yes, we shouldn't forget that Thiel thinks women's sufferage was a disaster, and wants to live on a floating libertarian utopia out of trash...Like I said, he's a brilliant nutcase.)

But the basic thrust of Thiel's worldview is sound: We need a conservative movement that is focused on progress. Reagan and Clinton may have succeeded in burning some institutional deadwood, but by the time the Bush years rolled around, we were down to burning the furniture. Proceeding further down the path of deregulation, spending cuts, and intentional government shutdowns is unlikely to do anything except to convert us to a neo-feudal backwater. Additionally, telling people to shut up about inequality is not likely to be effective in the long term.

The United States cannot succeed if public policy goes off the rails every time Republicans win an election. I am a liberal, but I believe we desperately need a relevant, functioning conservative movement. We need a conservative movement that is focused on making the government more effective, not smaller. Arguing for cutting the heath-care welfare state are sound; crusades against trains are ridiculous. The conservatism of the future - if conservatism is to have a productive future - is one that acknowledges the existence of public goods, and tries to steer government away from redistribution and waste and toward provision of those public goods. Progress must be the name of the game. 

I hereby nominate Peter Thiel as the official thought leader of the new conservatism.

Jim Bullard chucks the Solow growth model!

Sometimes I skim stuff too fast. When I saw David Andolfatto and Tyler Cowen linking to a Jim Bullard speech about wealth effects and output, I assumed that it was some sort of observation about aggregate demand. After all, wealth affects aggregate demand, so when wealth evaporates in a financial crisis, AD should fall. No surprise there.

But then, via Scott Sumner, I found out that Bullard (the president of the Federal Reserve Bank of St. Louis) is saying that wealth shocks affect long run aggregate supply!

What?!?!?!

Intuitively, this makes absolutely zero sense. Permanent negative wealth shocks lower potential output? Well, if capital is destroyed, that's true; for example, take the effect of World War 2 on Japan and Europe. All those bombs certainly lowered productive capacity (while destroying wealth). But if the financial crisis was that sort of thing, then it should raise the trend rate of growth, as we engage in "catch-up growth" to replace the destroyed capital.

Are we seeing rapid catch-up growth now? No.

So how does Bullard think this works? Is he putting forth a subtle and powerful argument that I missed by skimming? Let's see what he say in his speech:

A better interpretation of the behavior of U.S. real GDP over the last five years may be that the economy was disrupted by a permanent, one-time shock to wealth. In particular, the perceived value of U.S. real estate fell substantially with the 30 percent decline in housing prices after 2006. This shaved trillions of dollars off of the wealth of the nation. Since housing prices are not expected to rebound to the previous peak anytime soon, that wealth is simply gone for now. This has lowered consumption and output, and lower levels of production have caused a significant disruption in U.S. labor markets. 

The negative wealth shock lowers consumption and output. But after the recession ends, the economy simply grows from that point at an ordinary rate, neither faster nor slower than in ordinary times. It is more like an earthquake which has left one part of the land higher than another part. There is no expectation of a “bounce back” to a higher level of output after the recession ends.

Huh. I just can't make heads or tails of this idea. It seems to fly in the face of all the most basic intuition macroeconomists possess regarding growth.

Issue #1: A decline in housing prices is not a decline in the stock of productive capital. Houses are mostly consumer durables. A fall in housing prices leaves us with the same number of actual houses as before the crash; yes, that will have supply effects via geographic clustering and relocation costs, but there's no reason to think that these effects are dominating what we see in the economy.

Why does a decline in housing prices leave our economy able to produce less than before? It doesn't seem like it should.

Issue #2: A permanent negative shock to the stock of productive capital, as I mentioned earlier, will lower potential output, but will raise the rate of growth due to the renewed possibility of "catch-up" as we build back up to our old capital/labor ratio. Think of Japan after World War 2. In other words, there should be a "bounce back," directly counter to what Bullard is saying.

So, basically, what we have here is Bullard saying that the neoclassical (Solow) growth model - and all models like it - are wrong. He's saying that a change in asset prices can cause a permanent change in the equilibrium capital/labor ratio. 

That is not "crazy talk," necessarily, because it is at least conceivable that the Solow model - and hence, most growth theorists working today - might be completely wrong. But Bullard is going to have a hard time convincing the profession of that. And note that Bullard's contention would also invalidate all business cycle models of the "RBC" type, since those models are based on the neoclassical growth model. Even more deeply, what Bullard is saying is directly counter to our most basic notions of what "capital" is.

For more Bullard critiques, see Scott Sumner and Matt Yglesias, who have already made some of these points.

Bottom line: "We're not as wealthy as we thought we were, and hence we are choosing to buy less stuff" is an argument about aggregate demand, and it is an argument that many people accept. However, "We're not as wealthy as we thought we were, and hence we are able to produce less stuff" makes no sense in the context of any economic theory I know of. Bullard has some serious explaining to do if he wants us to believe the latter.

Thursday Roundup (2/9/2012)

Seemed like there wasn't much going on in the econoblogosphere this week (I was traveling for most of it, for second-round job interviews). People spent a lot of time discussing Charles Murray's new book, which seems to me a bit like feeding the trolls. The new unemployment numbers came out, and there was some argument over what they mean, but not as much as one might expect. Anyway, here's the links you may have missed:

1. Tyler Cowen discusses the benefits of, and good news about, Latin American immigration to the U.S.

2. Nick Rowe wonders why we don't smooth our consumption of leisure. Interesting question.

3. John Taylor thinks that our economic recovery has been terrible, and continues to be terrible. He chalks this up to the failure of "Keynesian" policies. I think it would be interesting to see him argue with Tyler Cowen, who says that we are having a good, strong recovery, and that this is evidence of the failure of "Keynesian" macro.

4. Scott Sumner reminds us that the Macro Wars are a three-legged race between Keynesians, neoclassicals, and monetarists (instead of a two-sided battle as many seem to think).

5. Brad DeLong, using some simple math, explains his thinking about labor market hysteresis.

6. Rob Johnson of INET interviews Sylvia Nasar about the history of economic thought.

Why rational expectations models can be wrong

Washington University professor David Levine has a pair of articles (article 1, article 2) in the Huffington Post about why financial crises can't be predicted, and why rational expectations theories are the only good theories in economics. Although I disagree strongly on both counts, Levine's arguments are very thought-provoking.

(As an aside, just to get this out of the way, Levine uses the Heisenberg Uncertainty Principle as an analogy to explain why observer effects make non-rational economic theories fail. This is not a great analogy, since the Heisenberg principle can only be related to observer effects in certain specific situations; also, the Heisenberg principle deals with conjugate pairs of observables, which are different from the kind of observer effects Levine is talking about. This isn't super-relevant, just remember not to get your physics intuition from interdisciplinary analogies. But anyway, back to Levine's ideas...)

Levine's first argument is that financial crises, by their very nature, can't be predicted:

Take an example: how we might predict stock market crashes? Suppose that two behavioral psychologists, call them "Kahneman and Tversky," produce a model of "cognitive biases" that predicts when crashes will occur. The model tells us that the stock market will crash on October 28. Since the model is reliable and has a perfect track record, we naturally believe this prediction. So what would you do? You would sell all your stock on October 27. But of course if enough people do this the stock market will crash on October 27 and not October 28. So this apparently reliable model will be proven wrong.

This is similar to an argument made by Levine's colleague Stephen Williamson. I've addressed this type of argument in the past, but here is a brief recap:

Conditional predictions are different than unconditional predictions. If your modeling goal is to say with confidence that "A financial crisis will occur at 9:01 A.M. on February 17, 2012," then Levine is right; you are probably not going to succeed. However, if your modeling goal is to say: "Unless X policy is taken first, a financial crisis will occur at 9:01 A.M. on February 17, 2012," then you have a chance of succeeding. Why? Because unless investors can predict whether policy X will be taken, then knowing that the model is correct doesn't allow them to make riskless profits. And of course, conditional predictions are the kind policymakers usually care about. So Levine is wrong in cases where policy is decisive.

As a side note, even in cases where Levine is right, this does not make modeling crises a useless exercise. It may be that increasing our understanding of the causes of crises leads to a decrease in the amount of crises rather than an increase in our ability to predict the timing of the crises that do occur. But that's fine! It means that the benefit of better crisis modeling accrued to society instead of to the modelers. That just means that research into the causes of crises generates a positive externality, and should therefore be subsidized by the government and/or some other collective public-goods provision mechanism.

And it means that critics of the econ profession who say "You economists didn't pay enough attention to models of financial crises" can still be right, even if Levine is right!

Levine's next argument is that rational expectations models of the economy are the only models that can be right over the long term:

In simple language what rational expectations means is "if people believe this forecast it will be true." By contrast if a theory is not one of rational expectations it means "if people believe this forecast it will not be true." Obviously such a theory has limited usefulness. Or put differently: if there is a correct theory, eventually most people will believe it, so it must necessarily be rational expectations. Any other theory has the property that people must forever disbelieve the theory regardless of overwhelming evidence -- for as soon as the theory is believed it is wrong.

But notice the logic behind this idea. It assumes that economic theories penetrate the public consciousness and are used by economic actors. Levine postulates that over time, as non-rational-expectations theories are shown to be wrong, economic decision-makers (i.e. you, me, and other folks) will gravitate toward rational expectations theories. This will mean that in the long run, only rational expectations theories will describe the economy. But it also must mean that in the long run, only rational expectations theories will be believed by the public. So if Levine is right, we should see more and more regular people gravitating toward the belief that other people are rational.

Do we, in fact, see this? I am not sure we do. On one hand, index funds are becoming more popular, signifying greater public acceptance of the Efficient Markets Hypothesis. On the other hand, the recent recession probably decreased faith in rational-expectations models of the macroeconomy, both among economists and among the public at large.

So if we don't see people accepting rational expectations theories, then the theory/behavior convergence that Levine talks about is not happening. Meaning that rational expectations theories may well be wrong.

Note that one easy way for rational expectations theories to be wrong is for the average person to simply be dumber than the people making the theories. For example, it's easy to reliably predict the mistakes of rats running in mazes, simply because rats aren't smart enough to learn our theories. Now, obviously, humans are not that far apart in intelligence, but if the difference between different humans is big, it could mean that behavioral theories could consistently be right.

(Does this make behavioral economics elitist? Maybe. But not necessarily. It could be that theorists are smart when making their theories but are dumb at other times. I can personally attest to the fact that this really does happen!)

In his second article, Levine asks how long it takes rational expectations to prevail, and cites the actions of the passengers on Flight 93 on 9/11 as an example of a quick rational response to new information (in this case, the info that hijackers would use planes as weapons). But does this mean that crowds are always rational? There is ample evidence for inefficient herd behavior in the psychological literature.

Anyway, Levine's logic in arguing for the supremacy of rational expectations is subtle and powerful. But I think reality is even more subtle, and even more powerful.