Month: November 2006

The case for economic turbulence?

Here is my Wall Street Journal review of Clair Brown, John Haltiwanger, and Julia Lane, Economic Turbulence: Is a Volatile Economy Good for America?  Excerpt:

In short, America is not becoming
a nation of part-time Wal-Mart cashiers or burger flippers.  In four of
the five sectors studied by the authors–semiconductors, software,
financial services, retail food and trucking–the growth rate for
full-time jobs exceeds the growth rate for jobs in general.  (Retail
food is the exception.)  Separate research, conducted by Ann Huff
Stevens at the University of California, Davis, shows that the average
tenure for employed U.S. male laborers has been broadly stable over the
past 35 years.

Insofar as individuals move to
lower-paying jobs, the turnover of firms is not the driving cause.  The
most original proposition in "Economic Turbulence" is the claim that a
big part of measured wage declines derives from job downgrades within
firms–sticking with the same employer but moving from, say, mid-level
manager to gopher. 

Mexican immigration

Here is my New York Times column; the topic is familiar but the slant is new: I consider the problematic incentives for Mexican education.  Here is the beginning of the problem:

A high school diploma brings higher wages in Mexico,
but in the United States the more educated migrants do not earn
noticeably more than those who have less education. Education does not
much raise the productivity of hard physical labor. The result is that
the least educated Mexicans have the most reason to cross the border.
In addition, many Mexicans, knowing they may someday go to the United
States, see less reason to invest in education.

Here is another commonly neglected point:

Unfortunately, we cannot expect a wealthier Mexico to resolve migration
problems, at least not within the short- or even medium-run. The
evidence suggests that good times in Mexico give the poor the means to
leave, while keeping the better-educated males at home in good jobs.

More economists get picked up

The Economist blog reports:

We have also heard that Doug Holtz-Eakin, another former Bush administration official who went on to head the Congressional Budget Office, will be John McCain’s top economic advisor. Mr Holtz-Eakin is giving up his current job–running the Centre for Geoeconomic Studies at the Council on Foreign Relations–to work full-time for the McCain team.

Thanks to Martin Scriblerus for the pointer.

From WSJ Washington Wire

Massachusetts Gov. Mitt Romney’s less-than-stealth positioning to join the
2008 presidential race took another baby step forward today, when two noted
economists – former chairmen of the Council of Economic Advisors Glenn Hubbard
and Greg Mankiw – signed on to lead his PAC’s Economic Advisory Council. Another
former Bush official, Cesar
Conda
, also signed on.

Thanks to Carrie Conko for the pointer.

Poorly designed objects

Bruce Charlton asks:

What is the worst designed everyday object?

Bruce Charlton answers:

My vote would go to the standard, hard plastic, hinged CD case.

Its functionality is terrible at best, and it breaks way too easily;
especially the hinge – upon which functionality depends.  And I have
hundreds of them!

That was my answer too.  I am also frustrated by the prevalence of non-sharp knives, although perhaps this is best for the children.  Do you all have other answers?

Time inconsistent agreements

Matt Yglesias proposes an exchange:

There’s an obvious deal to be cut here — NATO membership for the Baltics is a done deal, but we can return Russia’s "near abroad" to Russia in exchange for Russian cooperation on Iran and North Korea, or else we can have a series of standoffs across a wide Eurasian arc.  Some would call this appeasement and, frankly, the shoe fits decently.  It strikes me, however, as preferable to either going to war with Iran or to having Iran build a nuclear bomb.

I might add that Natasha still thinks I promised to take out the trash every evening.

Department of Why Not?

Kieran Healy writes:

This reminds me of one of my favorite books, encountered during research for Last Best Gifts: Ed Brassard’s Body For Sale: An Inside Look At Medical Research, Drug Testing, And Organ Transplants And How You Can Profit From Them.
This is a how-to guide for selling the renewable and non-renewable bits
of yourself and also for getting accepted into paying clinical trials
of all kinds.

Should we discount the future for radical uncertainty?

A few points:

1. Whatever the chance that the future (or rather our role in it) simply won’t exist, that should be discounted directly by the relevant probability of extinction.  That said, while I do worry about asteroids, I take this probability to be relatively small over the next five hundred years.

2. Our uncertainty about the future is good reason for performing an expected value calculation, but it does not provide additional reason for time discounting.  It will shape the p’s that go into the expected value calculation.

3. Austrians and Knightians may believe that our uncertainty about the future is deeply radical and that the entire expected value calculation is meaningless. 

I am closer to a Bayesian myself.  But even if we take the Knightian view at face value, it does not diminish the importance of the future.  Whether or not we call expected value calculations "scientific" or "stupid," we still need to make choices about the future.  A woman might think "I simply can’t imagine what sort of man I might marry."  He might even be some hitherto unimagined extraterrestrial being.  But her parents should still set aside some money for the possible ceremony. 

To make the uncertainty stronger and more general, perhaps the parents think "We have *no* idea what will happen with our daughter, marriage or not.  Perhaps she will sell kitchen equipment, perhaps she will be turned into a sweet potato."  In any case there is no general reason for the parents to think they should save less rather than more.  The potential outcome might require a very large expenditure on their part. 

Some of my technically inclined readers are already thinking about the
third derivative of the utility function and the precautionary motive
for saving
.  The intuition is this: if the effect of your savings is very uncertain, you might either eschew savings altogether ("who knows what it will bring?"), or you might feel a need to save all the more.  The third derivative will determine which is the correct decision, and this is not a matter of the discount rate per se.

4. The party analogy: Let’s say you have no idea who will show up at the party (or what the future will look like).  How can you buy the food until you know whether the guests are Hindu, Muslim, or whatever.  Fair enough, perhaps we should wait.  But given the  uncertainty, we might want to set aside more savings for future contingencies, and not spend all the money today. 

Let’s consider this "third derivative" business in a little more detail.  When does radical uncertainty justifiably mean the future should be ignored?  A Christian might believe that he should not save up for Rapture.  Perhaps Rapture, once it comes, will be so different and so unexpected in its nature that current precautions simply were not worth making.  Odds are your mutual fund won’t make it into heaven (or hell?).  Fair enough.

Alternatively, let’s say you are worried about an avian flu pandemic, but you don’t have a good idea what such a pandemic would look like.  You probably still should buy more bottled water, not less, and pickle more kimchee, not less.

The practically-minded can debate which of these two cases more closely resembles global warming.

The Friedman Magic

One of my favorite Friedman papers is "The Effects of Full-Employment Policy on Economic Stability: A Formal Analysis" which you can find in Essays in Positive Economics.

Friedman sets up a very simple model, Z(t)=X(t)+Y(t) where Z(t) is income at time t, X(t) is what income would be if there were no counter-cyclical government policy and Y(t) is the amount added to or subtracted from X(t) by the history of government policy.

You wouldn’t think that much could come out of such a simple model but Friedman takes the model, notes that the formula for the variance of two random variables is V(Z)=V(X)+V(Y)+2 r(X,Y) Sd(X) Sd(Y) (where V is variance, r correlation and Sd is standard deviation) and proceeds to show that:

In order to cut the variance of income fluctuations in half (which would cut the standard deviation by less than a third), r(x,y) must exceed .7.

The result is powerful because once you start thinking about the correlation coefficient, r, it’s hard to see how it could be as high as .7.  Very few government actions taken in time t have an effect in time t – there are lags between recognizing a problem, deciding what to do about the problem and implementing a policy.  Once the policy is implemented there are lags before the policy takes effect.  All of these lags are of uncertain and changing length so actions taken in t-5, t-4, t-3, and t-1, may influence Y(t) making a high correlation between X and Y unlikely.  Moreover, Friedman’s bound is an upper bound, requiring optimally sized interventions – when we recognize that the size of the intervention might be too little or too much and that in both cases this will reduce the decrease in variance we have a strong case for skepticism about the efficacy of counter-cyclical policy.

But was Friedman right?  In the thirty or so years after he wrote, when counter-cyclical policy was in vogue, the variance of the US economy was much lower than in the pre-World War I years.  Reality it appeared, refuted Milton Friedman.

Friedman, however, lived to see his simple model proved correct (Essays in Positive Economics!).  In a series of papers beginning in 1986, Christina Romer showed that the pre-WWI volatility was an artifact of the way the data was collected.  Once the pre-WWI and post-WWII data were collected consistently, using the same methods, the post-WWII economy showed no big drop in volatility.

Almost nothing in, a surprising and powerful result out, and an implicit prediction proven correct after thirty years.  That’s the Friedman magic.