The 10,000 Year Explosion

The subtitle is How Civilization Accelerated Human Evolution and the authors are Gregory Cochran and Henry Harpending.  I do think that such topics should receive open debate but, as with Greg Clark's book, I'm not convinced.  There is plenty on dog breeding, lactose intolerance, Genghis Khan and his children, the difficulties of settling the Andean Highlands, and just-so stories about medieval Ashkenazi Jews.  What's missing is a sense of what the hypothesis does not explain, what its limitations are, and also what exactly is being claimed beyond the particular cited examples.  The stories of "lots of recent change overall" and "current groups differ" are jammed together but of course they are very different.  Epigenetics don't receive much attention, even critically, and the lower levels of Ashkenazi social achievement before 1800 are dismissed quickly.  It's fine and indeed correct to claim they were oppressed but that opens up many doors to explain many other observed correlations.  The authors report that we have Neanderthal genes even though this seems to fly in the face of recent discoveries and more importantly the evidence that such interbreeding (if it occurred) mattered is extremely speculative.  Perhaps the authors are right but the reader is not given the tools to see why their understanding is a superior one.

Razib liked this book (see the first Amazon review) and I suppose it is a good introduction to this point of view, but overall I didn't come away feeling I obtained a superior understanding of the issues.

The multiplier in wartime

Robert Barro writes:

What do the data show about multipliers? Because it is not easy to
separate movements in government purchases from overall business
fluctuations, the best evidence comes from large changes in military
purchases that are driven by shifts in war and peace. A particularly
good experiment is the massive expansion of U.S. defense expenditures
during World War II. The usual Keynesian view is that the World War II
fiscal expansion provided the stimulus that finally got us out of the
Great Depression. Thus, I think that most macroeconomists would regard
this case as a fair one for seeing whether a large multiplier ever
exists.

I have estimated that World War II raised U.S. defense expenditures
by $540 billion (1996 dollars) per year at the peak in 1943-44,
amounting to 44% of real GDP. I also estimated that the war raised real
GDP by $430 billion per year in 1943-44. Thus, the multiplier was 0.8
(430/540). The other way to put this is that the war lowered components
of GDP aside from military purchases. The main declines were in private
investment, nonmilitary parts of government purchases, and net exports
— personal consumer expenditure changed little. Wartime production
siphoned off resources from other economic uses — there was a
dampener, rather than a multiplier.

We can consider similarly three other U.S. wartime experiences —
World War I, the Korean War, and the Vietnam War — although the
magnitudes of the added defense expenditures were much smaller in
comparison to GDP. Combining the evidence with that of World War II
(which gets a lot of the weight because the added government spending
is so large in that case) yields an overall estimate of the multiplier
of 0.8 — the same value as before. (These estimates were published
last year in my book, "Macroeconomics, a Modern Approach.")

There are reasons to believe that the war-based multiplier of 0.8
substantially overstates the multiplier that applies to peacetime
government purchases. For one thing, people would expect the added
wartime outlays to be partly temporary (so that consumer demand would
not fall a lot). Second, the use of the military draft in wartime has a
direct, coercive effect on total employment. Finally, the U.S. economy
was already growing rapidly after 1933 (aside from the 1938 recession),
and it is probably unfair to ascribe all of the rapid GDP growth from
1941 to 1945 to the added military outlays. In any event, when I
attempted to estimate directly the multiplier associated with peacetime
government purchases, I got a number insignificantly different from
zero.

I'm a little confused by his definition of the multiplier (how does it relate to "crowding out"?; what he calls a multiplier of zero I would call a multiplier of one), but I think you get the point.  By the way, I ran across this interesting short paper on fiscal policy and the fetishization of measured gdp, from Japan.

Singapore fact of the day

I am surprised that Bryan Caplan didn't already tell me this:

A controversial amendment to legalize the payment of compensation to
organ donors was put before the Singapore parliament this week and
while the health ministry is yet to decide on the upper limit for
reimbursement, it is expected to be at least S$50,000 (US$33,000).

Here is much more.  I thank Bob, a loyal MR reader, for the pointer.  And don't forget about the new Sally Satel book on organ sales and why they are a good idea.

Who survived the Titanic and why?

Bruno Frey, David Savage, and Benno Torgler report:

This
paper explores the determinants of survival in a life-and-death
situation created by an external and unpredictable shock. We are
interested in seeing whether pro-social behaviour matters in such
extreme situations. We therefore focus on the sinking of the RMS
Titanic as a quasi-natural experiment to provide behavioural evidence
that is rare in such a controlled and life threatening event. The
empirical results support that social norms such as “women and children
first” survive in such an environment. We also observe that women of
reproductive age have a higher probability of surviving among women. On
the other hand, we observe that crew members used their information
advantage and their better access to resources (e.g. lifeboats) to
generate a higher probability of surviving. The paper also finds that
passenger class, fitness, group size, and cultural background matter.

You’ll find a more speculative treatment here:

British passengers on the Titanic died in disproportionate numbers
because they queued politely for lifeboats while Americans elbowed
their way on, an Australian researcher believes.

David
Savage, a behavioural economist at the Queensland University of
Technology, studied four 20th-century maritime disasters to determine
how people react in life and death situations. He concluded that, on
the whole, behaviour is influenced by altruism and social norms, rather
than a “survival of the fittest” mentality. However, on the Titanic he
noted Americans were 8.5 per cent more likely to survive than other
nationalities, while British passengers were 7 per cent less likely to
survive.

“The only things I can put that down to are: there
would have been very few Americans in steerage or third class; and the
British tend to be very polite and queue.” (The ship’s first-class
staterooms were closest to the lifeboat deck.)

Savage admits there is no direct evidence for his hypothesis concerning the Americans.

I thank Leonardo Monasterio, a loyal MR reader, for the pointer.  Here is Leonardo’s post on Greg Clark.

Don’t touch when you are shopping, or the new endowment effect

Be careful how you reach out:

A new study suggests that just fingering an item on a store shelf can create an attachment that makes you willing to pay more for it.

Previous studies have shown that many people begin to feel ownership of an item – that it "is theirs" – before they even buy it. But this study, conducted by researchers at Ohio State University, is the first to show "mine, mine, mine" feelings can begin in as little as 30 seconds after first touching an object.

Here is the full story.  I thank Deron Bauman for the pointer.

Stimulus Contest

The WashingtonWatch.com blog is having a contest.

Take any part of the stimulus bill
and write a short case for why it’s good or bad. (Recommended: search
the bill for “$” – there are more than 350 of them.) Pick anything –
from an entire government department to the smallest program. You can
even pick a non-spending provision in the bill that you think will do
good or bad.

Entries are limited to 150 words, and they will be judged on
clarity, persuasiveness, creativity, and originality. You don’t have to
be an economist – if you are, you really must avoid being boring. If it
takes a haiku or an infomercial-style pitch to make your case, do it.

Winners will receive $100.  Enter in the comments section here.

New issue from Econ Journal Watch

The issue is here, I was sent this summary of the articles:

In this issue:

The
Race between Education and Technology
is the title of a new
book by Claudia Goldin and Lawrence Katz. In a review essay, Arnold Kling
and John Merrifield hail the book for its formulation of the problem and
theoretical core, but find ideological distortions in the execution,
diagnosis, and prescriptions. 

Are the most capable women and the most
capable men equally capable?
Previously, Garett Jones, John
Johnson, and Catherine Hakim questioned Christina Jonung's and
Ann-Charlotte Ståhlberg's call for more women in economics. Now
Jonung and StÃ¥hlberg respond. 

Guns-crime ricochet: Ian Ayres and
John Donohue reply to Carlisle Moody and Thomas Marvell. 

Bandwagon
zigzag:
Micha Gisser, James McClure, Giray Ökten, and Gary
Santoni investigate the upward-sloping segment of Gary Becker's (1991)
bandwagon demand. 

Eviction notice:
Blair Jenkins reviews an Econlit-based sample of articles on rent
control. 

Power Computing

I'm in the market for a new computer since my old machine just can't grok the large datasets that I am throwing at it.  I asked Paul Heaton, a very smart and productive econometrician with RAND who works with very big datasets, for his advice.  He sent me the following which I thought might interest others.  Your comments appreciated as well. 

1. It is very hard to find
a desktop system that accepts more than 8 GB of RAM, and RAM is probably
the biggest factor affecting Stata performance.  A 64 bit workstation or server architecture allow for more processors and more RAM, but these components usually cost 3-4 times as much as a
comparably performing desktop. If you want the absolute best performance
(i.e. more than 4 processor cores, 16 or 32 GB of RAM), you'll probably
need to go the workstation route. A good configuration will run you
$4K versus probably $1K for a top-end desktop.

2. I've use a top-end desktop configuration with a quad-core processor
and 8 GB of RAM to run things like NIBRS or value-added models using all
the students in New York City and gotten adequate performance but expandability is key.

3. If you want to run Windows, you'll need a 64-bit version. I use
Vista business which seems to work well for me. You'll need Stata to
send you a 64-bit version and a new license; converting your Stata
license from 32 to 64-bit is cheap. You'll also want to pay to upgrade
Stata to support the appropriate amount of processor cores in your new
machine (much more expensive), this boosts performance appreciably.

4. I suggest setting up your hard drives in a RAID configuration. You
buy four identical hard drives of size X GB instead of just one and a
controller card. The controller card spreads your data across two of
the drives and makes a mirror copy of those drives on the other two;
this is done transparently so from the user's perspective it is as
though you have a single drive of size 2X GB (there are other ways of
doing RAID, but these are less relevant for your situation). There are
2 major advantages to this: 1) The hard drive is often the bottleneck,
particularly when loading large datasets; by parallelizing the
operations across four drives instead of one, your datasets load and
write a lot faster. 2) Because there is a complete copy of your data
that is maintained on-the-fly, when one of your hard drives fails,
instead of losing data or being forced into an onerous restoration of
backups, you simply see an alarm alerting you to the problem.  Decent RAID cards run about $200, and disk storage is cheap, so I think
this is something everyone who does serious data analysis ought to be
doing.

Why bank nationalization is a last resort

Banks don't function well at low levels of capitalization, so there is a strong and understandable tendency to want to "do something."  Everyone says nationalization is not intended as a long-term solution but the question is whether government ownership will succeed in building up a greater capital cushion for the banks.  If the environment for banking is not favorable, it won't and banks will have to stay nationalized.

How many years of profits are needed to create the cushion of capital which is required for re-privatization?  And how many years of government ownership will be needed to generate that many years of profits?  Will banks owned by the government be allowed to pursue profits, rather than lending to troubled industries in the districts of influential Congressmen?  Or will government just stick money in the bank and hope they have thereby created a sound enterprise?

You might take the line: "Government is bad at running bail-outs, but it sure is good at running banks," but of course that's a tough sell.

Those are the questions you should be asking.  Admittedly the alternatives to nationalization don't currently look so great either.

Kevin Drum adds some good points.  Felix Salmon offers ongoing coverage.