Lake Wobegon Effect Goes Viral

We seem to have a problem in higher education.

What are we going to do about grade inflation?  Maybe this is a problem that will eventually cure itself.  Graduate programs and firms will soon need to start adjusting grade point averages for the institutions and departments from which they are applying.  Some probably do this already, but the transactions costs involved must be tremendous.  I'm quite sure many do not make these adjustments, which is why we're seeing such rampant grade inflation.  This just isn't sustainable.

I think I smell a business opportunity here: We need a ratings agencies for institutions of higher education that will allow for quick comparisons of GPA across departments and institutions.  I can imagine a number of ways of doing this.  But it would require willful participation of the various institutions to supply data on grades of all students and classes (with names stripped, of course).

Is anyone doing this?  I seem to recall reading or hearing about medical schools making such adjustments.  I wonder how they do it.  I wonder how well they do it.

The Renminbi

So China says they are (finally) going to revalue their currency and "gradually" move toward a floating exchange rate. NY Times article here.

I think that is good news.  I really hope it happens soon.

I'm a bit outside my element here, but I don't see how they can do this gradually.  Well, maybe if the keep the timing and size of the adjustment close to their vest they can keep some control.  But then what's the point of revaluing?

Update: I should probably refrain from oblique posts.  To the commenter who explains why China has pegged the Yuan to the dollar and why, in principle, they are revaluing: Yes I understand.  My question had to do with the "gradually" part.  The point is that once the market knows China is going to revalue or stop pegging, the market won't let China do it gradually.  Thus, when China says they are going to do this gradually it's almost as if they are announcing nothing at all. This is something we need to see to believe.

Republicans dump market-based solutions to environmental problems and embrace command and control

While the so-called "socialists" push for market-based solutions.

We live in a very strange world.

Here's David Leonhardt:

There once was a time when the government relied on a very blunt way of regulating the economy. It told companies and individuals what they could do and what they could not do. These were the days of command-and-control regulation.

But then came the market revolution of the last three decades. With the Soviet empire collapsing, the United States economy growing more rapidly than Europe’s, and newly market-friendly China and India booming, people saw the drawbacks of command and control. Governments were usually better off avoiding outright bans and instead giving people incentives to behave in productive [less costly and less polluting] ways....

...Unfortunately, the great economic strength of market systems like cap and trade also happens to be their political weakness. They set prices and allow people to react. In the process, market systems acknowledge that reducing pollution may actually cost a little bit of money.

Politicians don’t like to admit this, because voters don’t like it. Accepting higher costs is especially hard when the economy is weak. So Congressional Democrats have been repackaging their energy bills to make them look less and less market-oriented. Senator John McCain, who supported a permit system for carbon as the Republican presidential nominee, no longer does. Senator Lindsey Graham, the South Carolina Republican, has reversed his position as well.

What does Mr. Graham now favor? A series of command-and-control regulations. He has introduced a bill with Senator Richard Lugar, an Indiana Republican, that would mandate specific standards for cars, trucks, homes and offices. It would also give the energy secretary the power to award loans to companies he thought could do a good job of setting up programs to retrofit buildings. State officials would do the same for factories. The bill, in short, puts more faith in government than the market 

...... 

Are stock prices showing mean reversion?

I know stocks are supposed to follow a random walk.  And they pretty much have.  At least over short run (days, weeks, months, and years), if not over the long run (10-20+ years).

But recently--say the last six months or so--doesn't there seem to be a lot more regression to the mean in short-run price movements?  Are hedge funds making a killing by buying low and selling high?

This is just armchair speculation.  I haven't done any unit root tests.  So maybe I'm all wrong about this.

The Spill

I haven't had much to say on the Big Spill in the Gulf.  Despite the media frenzy, I think it's still hard to tell how all this will shake out economically speaking.

Although I hear environmental economists are being lined up to value damages...  There's a clear hit to tourism in the Gulf already.  But then there will be gains in other places--people will go to the mountains instead of the beach.  If this stuff hits Miami watch the numbers explode.  If it screws up most the southern beaches then scarce and less perfect substitution possibilities will make welfare impacts much larger.

How deep are BPs pockets?  How limited is their liability, legally speaking?  Pretty deep and I don't know.

In comparison to Exxon Valdez, it looks like the bigger numbers will come from relatively more tangible and measurable things--like tourism and recreation--as opposed to more controversial measures, like non-market values of birds and turtles.

It seems to me BP was in fact irrational when it came to prevention efforts.  The risks and potential damages to their bottom line profits were, objectively I suspect, way larger than BP's CEOs thought, despite warnings from their engineers.  Especially if the executives were to have considered both the legal response and the policy response and to a potential disaster.  Prospects for deep sea drilling now look dim, even if it can be done safely.   If drilling continues, regulations will be stiff and quite costly.

I smell hubris and arrogance.

Which makes me wonder: even if liability weren't limited would these companies always behave? Full liability would certainly help a lot.  But when these companies get big enough to assume so much liability, then they are big enough to do an extraordinary amount of damage.  One stupid mistake, a single act of hubris, reeks havoc.

What do commodity prices reflect about broader economic expectations and risks?

Gold prices are pushing repeatedly record highs.  But there is no inflation on the horizon; indeed, deflation is a far greater risk right now.  This can be gleaned by the fact that prices of other commodities, ranging from oil to minerals to agricultural commodities, are trending down, by record-low long-term treasury rates and low rates on inflation-indexed bonds, and by high unemployment and stagnant wages. The trend in CPI data is down too.

What gives?  Jim Hamilton nails it:

There's a common thread to all the above figures, and it's not fears about inflation. Instead it's worries about the level of real economic activity, showing up in a flight to safety. U.S. Treasuries remain the instrument of choice for investors who think nothing looks safe.

But with the long-run fiscal challenges facing the United States, are 10-year Treasuries really the safest place to put your money? The yellow metal seems to be one way some people are hedging that bet.

The broader economy has a lot to fear from fear itself, especially given the Fed seems either unwilling or unable to do anything to compensate for flight to safety while still stuck at the zero lower bound.  Plus, further fiscal stimulus is all but off the table given current fears feeding broad governmental flight to austerity, which only seems to make matters worse. (Also see: here--this is a long, tired debate)

Anyway, aside from the macro wars, I find it interesting that commodity price fluctuations appear to generally reflect a lot about the broader macro economy and perceived risks across a wide class of assets.

Consider:

1) During the 70s and 80s when fear of limited oils supplies ruled the day, commodity prices were high, and energy commodities in particular fluctuated negatively with stock market returns and positively with inflation.  This was a rare example of real-business cycle phenomenon stemming from uncertainty about supply of key natural resource commodities.

2) During the naughts, we saw a reversal of the earlier patterns, with commodity prices fluctuating positively with growth and stock market returns.  It appears this was because the larger uncertainties were about broader economic growth and demand, particularly from Asia; and after the recession hit, uncertainties about the size and timing of world economic recovery.

3) Now that gold is breaking away from the other commodities, I see signs of the same ominous fears that Jim Hamilton sees. Thus, today commodity prices reflect expectations of meager to declining growth mixed with sublime fears that governments will be unable to fullfil debt obligations, or perhaps fears of broader institutional decline.

Given commodity prices reflect so much about expectations about broader economy, it seems there should be a nice way to systematically evaluate expectations from commodity price patterns. But there really isn't much in the literature that I'm aware of.  I'm thinking in the back of my mind we need to somehow merge analysis like that of Kilian (ungated version here), which disentangles supply and demand factors in oil price determination, with asset pricing theory.

I should note that fears reflected in gold prices, while real, are still pretty subdued.  One way to try to put the size of the hedge in perspective is to approximate the total value of gold worldwide and compare that to, say, the capitalized value of the stock market, oil reserves, and bond issues.  Currently the world produces about 75 million ounces of gold per year.  With gold trading at $1220 an ounce, that's a world production value of about $91.5 billion.  That's pretty tiny in comparison to, well, just about anything.  It's hard to say what the worldwide stock of gold is, but it's hard for me to imagine how it could be more than 20 times the flow, which would put the value of the worldwide stock at something less than $2 trillion.  That's a lot of money, but it's still pretty trivial share of the world's assets.  "Proven" oil reserves equal about 1.2 trillion barrels (a value of some $90 trillion).  The global capitalized value of stocks was about $50 billion trillion in 2007. I expect real estate value exceeds both these figures by a large margin.  Our U.S. national debt is some $13-14 trillion, which also sounds scary but really isn't in comparison to our potential annual output and value of all our assets.  

Note that a hedge on gold is just that--an iddy bit of insurance in case things get much worse than expected.  It's a really bad basket for all your eggs.  The overarching expectation is that bets on gold will lose, especially if investing at today's high prices.

Advice for students taking an economics PhD prelim exam

It's a little late for advice as I'm in the midst of grading Ph.D. preliminary exams.  It's the first time I've done this and it is an eye-opening experience.  The experience inspires me to take a break and write down some advice for future students on how to study and take the prelim exam:

Guidelines for studying for a PhD preliminary exam in microeconomics:

1. Read a lot of economics at different levels and try to connect the dots.  You’ve just finished your first-year Ph.D training studying more advanced books.  Now go back and re-explore undergraduate textbooks.  You may see them in a different light.  When reading principles-level material, stop at times to think about how you might approach the same material at a more advanced, mathematical level.  When reading more advanced material, stop at times to think of practical real-world applications and how you might communicate concepts in non-technical ways to non-economists.

(a) Read at least two good principles of economics textbooks, carefully, cover to cover.  I recommend the following: Frank and Bernanke, Case and Fair, Mankiw, Krugman and Wells.  Others are good too.

(b) Read at least one good intermediate economics textbook, cover to cover, carefully.  I would recommend:  Pindyck and Rubinfeld, Perloff, Varian, Mclosky (fee at:  http://deirdremccloskey.org/docs/price.pdf ), Silberberg.

(c) Read two or three light armchair economist books, like Freakonomics, Frank’s The Economic Naturalist, and books by Steven Landsburg.

Seem like too much reading?  Maybe a PhD isn’t for you.  This much reading, and more, should be FUN.  As a practicing economist you will read at least this much every month or two.

2. Do lots and lots of problems.  Review all your problems from intermediate and graduate level microeconomics.  Try to think if there are any broader implications to the questions, especially ones that are more advanced or technical.  What do you think the writer of the question is trying to lead you toward? Often there is more to it than math tricks—the economist who wrote the question may have a broader conceptual point to make.  Problems from Varian’s Microeconomic Analysis can be good, and solutions are available online.  Hirshleifer and Riley has some wonderful problems.  Then there are the contemporary standard PhD microeconomics textbooks: Mas-Colell, Whinston and Green and Jehl and Reny.  Dive in.

3. Do as many problems as possible from old preliminary exams.

4. Discuss problems and interesting economic ideas with your classmates.  This is fun, and you’re likely to learn a lot from each other.


Guidelines for taking a PhD preliminary exam in microeconomics:

1. Think before you write.

2. If your gut instinct is to give an answer that doesn’t have to do with how incentives affect behavior, stop and think again.  If you really, really want to give an answer that is not economics based, then only do so after giving an answer that is based in economics, and explain with subtlety and insight the strengths and weaknesses of the alternative viewpoints.

3. It’s better not to answer a question than to answer it stupidly.  A stab in the dark is wrong with probability greater than 0.99.  A stupid answer makes the grader think you really don’t belong in graduate school and that they would be doing you a favor by failing you.

4. An okay answer explains the intuition OR provides mathematical formalism.  A better answer does both.  An excellent answer turns over the problem and considers different possibilities, both intuitively and formally. Excellent answers are quite rare.  A few excellent answers will wow the grader even if you don’t complete all questions on the exam.

Is corn becoming more or less tolerant to drought and extreme heat?

At Bioenergy Camp in Perry Iowa, I presented a paper with Wolfram Schlenker on the evolution of heat tolerance in corn.  I blogged about this paper awhile back.  The paper will be a chapter in a forthcoming NBER volume, Climate Change: Past and Present.

My seminars sometimes provoke a lot questions.  I'd like to think this a good sign that my talk is interesting.  Maybe I just need to work on being clearer  This talk, however, provoked a particularly sharp response from Ted Crosbie, Vice President of Global Plant Breading for Monsanto.  He didn't say why, but Dr. Crosbie claimed our results were wrong.

Our main finding is that extreme heat tolerance in Indiana increased from 1940 to 1960 and then declined between 1960 and the present.  The turning points--1940 and 1960--coincide nicely with adoption of double-cross and single-cross hybrid corn.  Our estimates show relative tolerance to extreme heat at the end of our sample (2005) to be close to than in 1940.  That's the part Dr. Crosbie didn't like.

I don't think our results are wrong, even though there is a lot of uncertainty.  But allow me to speculate a little about the challenges here.

There is a lot of chatter in the business about plants being more drought tolerant than they had been in the past.  But it's hard to find persuasive evidence to back that claim.  One problem is that there are two closely related but different factors: drought resistance and extreme heat resistance.  When it's really hot, corn doesn't tassel, and this can kill seed formation and yield.  Also, when it's really hot, evapotranspiration increases, and there tends to be less precipitation to replenish soil moisture.  So, statistically, it's hard to separate stress coming from lack of moisture from stress stemming from extreme heat, including associated issues with flowering and seed formation (which tends to happen in the hot month of July).  All of this is complicated further by the fact that data on precipitation is poorer than data on temperature, which means temperature is likely to pick up effects from lack of moisture.  (We find it's hard to predict precipitation between weather stations but can predict temperatures well.)

So, what we find is that drought tolerance has in fact increased steadily over time.  That is, the detrimental effects of too little precipitation has attenuated.  But the effects of extreme heat (measured by degree days above 30C), conditional on precipitation, became steadily less damaging between 1940 and 1960, and then became steadily worse between 1960 and 2005.  Now it is possible that drought effects are somewhat confounded by extreme heat effects and vice versa.  After all, these are almost two sides of the same coin.  But temperature measures have the stronger association, probably because temperature is measured more accurately than is precipitation.

Things are complicated further by the fact that, despite global warming, weather has been good--a little cooler--during Midwestern summers in recent years.  If you're a farmer in Iowa you may think your high yields are due to the fact that your corn stalks can better take the heat.  But it may actually be (and to some extent almost surely is) because it's been little less hot than it used to be. We haven't reported these statistics, but when we run regressions without weather variables, the trend comes in about 10 percent steeper between 1950 and 2005.  Technically, we need to be clear about difference between the size of the dose and the size of the dose response.  The "dose" in the case being extreme heat. 

The good recent weather also raises some interesting questions about why it's been so cool, and whether we should expect that to continue with climate change.  All the climate models we've looked at predict serious warming in the Midwestern summers.  John Mirankowski says the climate modelers at Iowa State predict it will be warmer in Winter but not in summer.  With the amount of warming generally anticipated for the latitudes of the corn belt, it's hard for me to believe there won't be a fair amount of warming in summertime.  But it's certainly something to quiz the climate scientists about...

A focus on recent changes in heat tolerance is a little askew from this paper's focus on the long sweep of history.  Our sample stops too early and uncertainty too is large to discern with any degree of accuracy what's been going on in the last 10 years or so.  And we focused on the the relatively temperate state of Indiana because it has the best weather records in the first half of the last century.  We needed a number of years of good data before and after first adoption of hybrid corn.  Our main goal was to get good weather data from the terrible dust bowl years. 

Perhaps a better perspective of the more recent years can be found in our earlier PNAS article (check out the supplement, that's where the meat is) that examines the whole country from 1950-2005.  What that paper shows is that, looking broadly over time and geography, the basic relationship with yields is remarkably robust and stable. Looking over time, however, we simply split the sample in two.  While this would also obscure recent changes, the stability of the results suggests that if there were big improvements in heat tolerance that happened steadily over time we would have seen at least some indication that. I think this means that if heat tolerance has grown, it has probably been very recent and has probably been fairly modest.

The thing to do is update our fine-scale weather data and look more closely at evolution of heat tolerance in recent history over all states combined.  It should be easy enough to do once we download all the weather station data since 2005.

Nice places for ag/energy/environment economics workshops

Nick Flores puts out a call:

Dear Colleague,

I write to announce that this year's CU Environmental and Resource Economics Workshop will be held on September 17-18 at the Lionsquare Lodge in Vail, Colorado.  Deadline for abstracts is August 1.  A link to the workshop website which has more information is provided below.  Please pass this announcement on to colleagues and graduate students.

http://www.colorado.edu/economics/news/environmental-workshop/index.html

We have our own Camp Resources that is held in nice places too.  This year we're on the beach near Wilmington.  In the odd years we're in the mountains (Asheville).  The quality of the presentations last year (mostly grad. students) was excellent.  This year's program can be found here: 

http://www.ncsu.edu/cenrep/workshops/campresources2010.php

And finally, you may not think of Perry, Iowa as a nice place for a workshop.  But the hotel used for Bioenergy Camp was amazing, and it was a perfect environment for interacting with colleagues in the areas of agriculture and energy.  I loved the tour of the ethanol plant and hearing some perspectives from industry representatives.  Many kudos to Jim Bushnell for organizing this.

A critique Robert Pindyck's model to estimate maximum plausible willingness to pay to prevent global warming

So I've been completely buried with finals and grading and PhD prelim exams and putting my tenure packet together and working with a visiting out-of-town colleague on a old paper we really need to finish up, going to a wonderful Bioenergy Camp in Perry Iowa (muchos gracias to Jim Bushnell), and a little surfing break in Costa Rica....etc..etc...

Despite all this, I've long been meaning to write a critique of Robert Pindyck's seminar at Duke a few  weeks ago.  The talk was about the model he uses to grapple with uncertainty about climate change and its impacts, and what this uncertainty implies about the most we, as a planet, should be willing to pay to curb greenhouse gas emissions.

For the record:  I really like Pindyck's articles and books.  There are few economists who write theory as clearly and elegantly as he does--you can learn both the math and the economics from him.  With Pindyck, there is no "lets use math to obfuscate how shallow my ideas really are."  He's truly one of the best.

So maybe I'm hanging myself by writing this, but despite my general admiration of his work, I think Robert Pindyck is naive when it comes to thinking about uncertainty and climate change. (You can find one version of his paper here).  There is a bit of math in his model so, for the less wonkish, I'll try to keep things relatively intuitive in my critique.  And I will try to present his key ideas fairly.

Also for the record: I don't disagree with Pindyck's broad policy conclusions.  I too would feel extremely wary about spending more than 2% of GDP curbing greenhouse gas emissions.  However, I also think we could bring CO2 emissions close to zero pretty quickly if we spent 2% of GDP in an efficient manner.  But his model doesn't address costs, only maximum willingness to pay to prevent severe global warming.  Fair enough; it's challenging enough to just think seriously about the demand side of curbing CO2 emissions.

Pindyck's model is, I think, mainly a response to Weitzman, who shows how easy it is to justify spending almost all our current income combating global climate change.  Note that Weitzman is not advocating such a policy (nor would I!); he's just trying to sketch out the possibilities, and in doing so, pouring a very cold glass of water on how we economists might like to answer this question.  He basically concludes that cost-benefit analysis, as applied to this problem, is hopeless for determining the optimal amount to spend to curb greenhouse gas emissions.  I don't know that I accept Weitzman's conclusion. Yet.  But I'm feeling cold and wet.

So, in a nutshell, Pindyck takes a pretty neoclassic model of a representative global individual and plugs into that model two kinds of uncertainty:

(1) Uncertainty about the amount temperatures will actually change due to human activity (CO2 emissions);

(2) Uncertainty about the effect of warmer temperatures will have on global economic growth

I like the way he models uncertainty, with simple parametric distribution functions that are easy to manage analytically but also allow for fat tails.

Components of the model that are crucial to the outcome but that are not so transparent are:

(A) The amount of (assumed certain) economic growth that would occur in the absence of climate change;

(B) The nature of the utility function he uses

Factors (A) and (B) are central to the how we balance future potential losses from climate change with current costs of curbing climate change.  This gets at the heart of the so-called 'discount rate' we should use in trading present costs of curbing emissions against future benefits of less warming.

In most models another component of discount rate--a pure rate of time preference--is added to the mix.  But this is usually small and there are fairly persuasive ethical reasons to set it equal to zero.  Pindyck didn't seem to understand these arguments, even though his model embraces them; he seemed to think they have to do with one's individual preference for consuming something today rather than tomorrow, holding all else the same.  The issue is really about whether the utility of someone who is born today is intrinsically worth more than someone born in 50 or 100 years, holding all else the same.  Yes, it matters that people of the future may be much richer (or possibly poorer) and in many ways better off (or possibly worse) than we are today, but that is what (A) and (B) take into account.

For (A), Pindyck assumes a baseline of 2% per-capita growth in consumption worldwide. If one is used to thinking about U.S. growth over the last 100 years this seems pretty reasonable at first blush.  Over the long run, growth has been remarkably steady and just a tad beneath this rate.  For the world as a whole growth may even be a little more rapid.

But in many countries growth has been highly erratic.  Some countries have stagnated or declined for decades or more.  Indeed, even in the U.S., productivity growth was much more rapid 1950-1980 than has been sense.  And individual growth rates vary way, way more than national rates.  Looking more broadly than simple averages, a few lucky ducks experience much more than the average while most experience much less.  This heterogeneity happens to matter a whole lot. Pindyck ignores this heterogeneity and does not acknowledge how important it may be. 

It also matters a lot that he assumes the baseline growth rate is certain.   If he instead modeled the baseline growth rate as a random variable, and assumed that uncertainty interacted in a plausible way with uncertainty about the effect of climate changes on growth (number 2 above)--say, more baseline growth is negatively correlated with impacts from climate change, following from the idea that greater technological advance would make coping with climate change much easier--then I'm confident he would obtain very different and likely much higher willingness to pay to curb warming.

For (B), Pindyck assumes the classic CRRA (that's for Constant Relative Risk Aversion) utility function that many economists use.  This is a nice utility function that is reasonably intuitive and flexible.  But it does have some serious shortcomings. The main shortcoming is that it implies a powerful symmetry between the elasticity of intertemporal substitution and risk aversion that grossly violates real historical investment opportunities. (Sorry, this gets a pretty wonkish.)  To explain the risk premia historically observed on risky assets, we need a very large risk aversion coefficient, which would imply highly inelastic intertemporal substitution.  But highly inelastic intertemporal substitution would imply interest rates much higher and far more volatile that we have observed in history.  Thus, the reality that is our last 100-plus years of financial history strongly violates CRRA utility. 

All of this may seem technical, and it is, but it matters a lot to Pindyck's conclusions. It matters because if Pindyck were to instead use a utility function with high risk aversion and more elastic intertemporal substitution--which is what we observe in real financial data--then his willingness to pay numbers would become much, much larger.  They would become larger still if he were to combine a more realistic utility function with other kinds of uncertainty, like baseline growth, described above.

What utility function should Pindyck use?  One possibilty would be the recursive utility function by Epstein and Zin.  Pindyck made a snyde comment about this utility function in his seminar (he claimed not to have these preferences).  So what about the habit formation model of Cochrane and Cambell (JPE 1999)? Or similarly Ryder and Heal (1973)?  The essential idea is that utility of consumption is relative to expected or recent consumption.  These kinds of utility functionS can be show to roughly fit the facts, unlike CRRA.  But they imply, at times, huge risk aversion and relatively more elastic intertemporal substitution, without the bizarre non-expected-utility recursive structure of Epstein and Zin.

It is not clear to me that these alternative theories are necessarily correct while Pindyck's is wrong.  But the point is that Pindyck is purportedly sketching out the range of possible willingness to pay.  And while he is generous with some of his assumptions, his is clever to compensate generous assumptions in certain respects with much less generous assumptions in other respects.  And relaxing these other assumptions--like baseline growth, certainty of baseline growth, homogeneity in growth, and a utility function that when combined with modest growth pushes marginal values of the future toward zero at an unrealistically rapid rate--could cause his willingness-to-pay numbers to skyrocket.

So while my own subjective judgment would likely put the maximum willingness to pay to prevent global warming in the ballpark of Pindyck's, I think reasonable people could plug numbers into a model not all that different from Pindyck's, but equally if not more realistic, and obtain willingnesses to pay that are much, much larger.  If the point is to place limits on what is plausible, I don't think Pindyck has done so very convincingly.