The Great Moderation hides a lot of volatility

It has become difficult to make much sense of the business cycle lately.
The first puzzle was the so-called Great Moderation, as somehow business cycle fluctuations across the world became more dampened over the last two decades or so. The second one is what we are currently witnessing. Add to this a curious phenomenon that Natasha Xingyuan Che is documenting: while aggregate volatility was reduced during the Great Moderation, idiosyntract volatility (at the firm level) was actually higher. This is an indication that aggregate volatility changes were not just the consequence of a general change in volatility, but rather that the way the economy is organized has changed.

Che verifies this conjecture both empirically and using a model where organizational capital is crucial. Indeed, this intangible capital creates considerable idiosyncratic risk, but it also considerable reduces the comovement between firms. By definition, organizational capital is firm specific, basically whatever would give a firm value above the tangibles. Count in a customer base, work morale, reputation, "how to do things", etc. So, this capital seems quite independent of other firms, one can even argue that it creates a negative comovement with other firms: if, say, a firm gets a negative reputation shock, it lowers its sales and the competitors pick up a larger share of total demand.

Lead papers are not particularly better

Much is made about lead papers in journals. Some editors like to put what they think is the best article of a review in front. Is there any truth that this signals quality? Tom Coupé, Victor Ginsburgh and Abdul Noury use a natural experiment to test this idea: The order of articles in European Economic Review was alphabetical by author in some issues from 1975 to 1995. One can accept that this is a random ordering on the quality dimension.

The results are sobering. It turns out papers appearing first do have a citation advantage. This means that at least part of the citation advantage of lead papers is due to their position, not their quality. And knowing how the alphabet ranking of your name matters, it appears latter authors were doubly screwed in the European Economic Review.

Genetic diversity and development

What can explain the persistent differences in development acorss the world? While the dispersion of income has increase with the Industrial Revolution, it was already very high before that. Some have claimed that the timing of the transition for hunting and gathering to agriculture during the Neolithic Revolution is crucial, in other words the luck of geography is determinant. But maybe genes are more important.

This is what Oded Galor and Quamrul Ashraf claim. Specifically, they say that genetic diversity within a population can have important effects on the development of an economy. On the one hand, genetic diversity leads to lower social cohesion, and therefore mistrust and coordination failures, which leads to a depressed economy. On the other hand, genetic diversity allows to exploit complementarities and thus increase (faster) total factor productivity. Thus the impact of geeneti diversity is ambiguous.

The empirical analysis reveals that diversity is beneficial at low levels of diversity, and detrimental at high levels. This analysis was performed using expected heterozygosity at the ethnicity level: what is the likelihood that two random people form the same ethnicity would share genes. In this, distance from East Africa, following the migration patterns of early humans, proves particularly useful.

Looking at data for AD 1 to 1500, where economic development can be somewhat reliably be measured by population density (this was a Malthusian world after all), the authors claims that between 15% and 42% of economic development dispersion across the world can be explained by genetic diversity. Surely not negligible. And intriguing.

The American Dream is a nightmare

A major part of the American Dream is home ownership and this dream is heavily supported by public policy through mortgage rate tax deductability, support for first time buyers, other tax advantages, and recent bailouts. So why do we have all this support for home owners? Does ownership make people happier? Does it make a better society? Yes in both cases according to popular belief, but is this actually true?

Grace Wong Bucchianeri addresses these questions using a survey conducted in Franklin County, Ohio. This survey has time use data, include various measures of happiness throughout a sample day for women in rented or owned single houses. Along with all sorts of other controls, the focus here is to determine whether home owners are different from renters. And the results are:

• Happiness: home owners are not happier in any dimension. In fact, they appear to suffer more pain from house and home than renters.
  
• Self-esteem: no difference between ownership categories.
  
• Health: home owners are less satisfied about their health, and for a good reason: they a fatter, for an average of twelve pounds.
  
• Time use: home owners have less leisure, spend less time friends, and like it less when they do.
  
• Relationship: home owners are less happy with their partner, and with other people in general.
  
• Participation in civic activities: no differences.
  
• Neighborhood: home owners suffer less pain from their neighborhood. Finally a positive...
  

So why is the American Dream so heavily subsidized again?

Free textbooks

I have reported before about what a rip-off textbooks are. The obvious solution is to teach without one, but today's students insist on them. But help seems to appear on the horizon, in the from of Flat World Knowledge, a commercial publisher that sells hard copies, at lower prices than the competition, and offer the PDF files for free. This is quite an interesting commercial strategy, which has also been adopted by some open access journals that provide print-on-demand services at some cost but otherwise keep the journal free. In economics, Theoretical Economics comes to mind.

Hattip: Against Monopoly

The sorry state of the PhD labor market

It is not a good year to go on the job market for US Economics PhDs. Most state schools are not hiring, and the financial sector is dead. Regarding private schools, those with larger endowments are still hiring, though moderately. Those with smaller endowments are scared to hire as they do not know yet how many students will show up in the Fall.

Bad years can happen, the question is what comes next. I have the strong suspicion that there will be many last minute visiting positions, especially among the smaller private schools. Those positions, if they happen, may convert to tenure-track next year. State schools will, however, not hire next year, even if the economy improves. Next year's cohort of PhDs will join this year's backlog chasing few positions. The excess supply of PhDs will persist for several years, as we have seen after the previous recessions.

There is little prospect of significant absorption of the excess supply abroad. The only hope is the government sector, which is supposed to increase its regulatory oversight and plenty of projects to launch. This could also mean more jobs with consultants, but those have not materialized yet.

Do new drugs reduce medical costs?

There is good evidence, foremost by Eric (corrected: Frank) Lichtenberg, that the introduction of new drugs improves health outcomes. But at the same time, there is a perception that new drugs increase health care costs, and maybe so more than it improves lives.

Rexford Santerre dismisses this idea showing that new drugs even reduce medical costs, primarily by making medical procedures less necessary. The empirical analysis is performed using aggregate data by health category, by regressing the change in expenditures on the previous year's change, the change in income and the number of new drugs. I find it heroic to make claims on causation based on such a "model". All you have is a correlation after controlling for income. If you want to say anything about causation, write down a proper model with testable hypotheses, and test those, not some random equation.

Another point where I think this paper misses the mark is in the presumption that drug price controls would be bad. The pharmaceutical industry enjoys some of the highest returns thanks to the protection given by patents. These firms need to be regulated for that very reason. In fact, it would be better to drop the patenting system in the first place: this would increase the competition to be ahead of competitors, instead of hampering progress with strategic patenting. Also, drug prices would be much lower.