Tyler Cowen notes some relevant trends here . I talk to people and they say that applied micro has suffered over the last 15 years as top Americans have gone to Wall Street rather than the professor route. When I was a graduate student 20 years ago, my entering class was 50% American. Now I believe that at Chicago it is 15%. So what? I'm go back and forth on the causes and consequences of the globalization of research economics. I look at the MIT faculty. It is a highly international group and they are certainly churning out great research except when the World Cup is played and then the place turns into the United Nations.

A deeper question might ask; "Why are Americans not entering academic economics?" Is it simply the "pull" of Wall Street big money? Unfortunately, I am slightly worried that economics has hit diminishing returns. There is a huge intellectual payoff from starting to know basic economics and statistics but are there increasing returns here?

I think of Watson and Crick and the Double Helix with many research teams all simultaneously trying to crack the same research question. They were working in a "stationary" environment. I don't believe that DNA changes over time.

Economics is harder. The agents we are studying form expectations of the future, are highly heterogeneous, their choices are often strategic and some claim that they even make mistakes. These agents have private information concerning their past history and this past set of choices and outcomes affects their decisions today (non-separable) On top of this, the economies we study are not stationary as they are bombarded with shocks (climate change, financial news, new products) that change the equilibrium we observe. If we could study a stationary process where people play the same games and situations over and over, I'm highly optimistic that we could use revealed preference methods to tease out interesting facts about people, firms and governments and then use our "structural findings" to inform policy debates.

I do have the sense that modern applied micro is too spread out. Our collective research covers a vast number of topics. I would find it satisfying to be in a field where there is one core question and everyone is trying to make progress on that question. In contrast, we have sprawled. Perhaps I know too little about other fields and they are equally sprawled.

Well, I just received a revise and resubmit email so please let me end this blog
to get back to the research frontier. Lucas please call me!

UPDATE: I see that people are reading this blog entry so I want to offer a quick
follow up.

I am proud to be a Ph.D. applied economist. If I was 22 again, I think I would make the same career choice. This is certainly a very good life. But in 2009, are the next 30 years brighter for academic economics or academic biology meets computer science or neuroscience? If in the year 2039, economics is in the midst of a "golden age" --- this would be a very happy surprise to me when I am a 73 year old man.

I want to be wrong here because it would be quite exciting to be part of a field whose cumulative insights are accelerating. What can economics do to maximize the likelihood that this remains an exciting time for our field?

A couple of "micro" ideas

1. Google could create a centralized data clearinghouse so that all data sets would be archived there after publication. No more ISSR. Journals such as the AER that require such archiving could forward on the data sets to Google.

2. The National Academy of Sciences could strongly lobby the government of the U.S and others around the world to reconsider what types of data are collected and to reconfigure panel data sets.

3. The U.S tax authorities should offer special tax deals for data companies to share proprietary data with academic nerds. I pay a lot of money for micro data sets from companies that sell real estate data or vehicle registration data. There is no reason for why I need to face such monopoly pricing when the true marginal cost of data delivery equals zero. This is slowing down science.

#1- #3 would improve data quality and guarantee replicability. It would lower the barrier to entry -- we know that the number of papers written would rise but would average quality rise? Given that we only care about the max of the set --- so what? but someone would have to review all of these papers.

I just stumbled across this recent speech by Alan Krueger. He appears to agree with me.

I am not smart enough to answer the riddle of the future of macro. We started with the 1 sector growth model with representative agents and common production technology. We now agree with the 2000 Nobel Laureate concerning the fundamental role that heterogeneity plays along many many dimensions in our modern economy. Once we allow the "heterogeneity genie" out of the bottle, how do we generalize from the field experiments we run? How do we do empirical work when we are accumulating high numbers of unobserved state variables that the agents are aware of and responding to but that the econometrician does not observe?

Well, we know we can't screw in a lightbulb but that can be outsourced. Auction theorists know that they have made a difference in the real world. Want proof? Click here . Preston McAfee serves up a very interesting recent intellectual history.

What else are we good for?

On improving the design of health care policy, here is an example from MIT's jon gruber.

On designing well functioning carbon mitigation legislation, I can point you to Dr. Stavins' input .

We are trying to be as socially useful as dentists. But the patient takes the advice that the dentist offers. There is no strategic game played between the patient and the dentist. The dentist leads (she looks in your mouth) and you do what she tells you to do. I am going to dental school.

Here is proof that I can publish in a history journal. The Costa/Kahn book was reviewed in a history journal and we were invited to reply. I wish that the Journal of Economic Literature would allow me to respond to Ed Mills' review of my Green Cities book.


Books: Awaiting the Heavenly Country: The Civil War and America's Culture of Death
Mark S. Schantz
Ithaca NY: Cornell University Press, 2008
ISBN-13: 978-0801437618 ; 245 pp.; £20.95.00


Heroes and Cowards: The Social Face of War
Dora L. Costa and Matthew E. Kahn
Princeton, NJ: Princeton University Press, 2008
ISBN-13: 978-0691137049 ; 336 pp.; £19.95

Reviewer: Brian Holden Reid
King's College London

Citation: Brian Holden Reid review of Awaiting the Heavenly Country: The Civil War and America's Culture of Death, by Mark S. Schantz and Heroes and Cowards: The Social Face of War by Dora L. Costa and Matthew E. Kahn (review no. 811)
URL: http://www.history.ac.uk/reviews/paper/reidb.html
Date accessed: Thursday, 29-Oct-2009 15:56:16 GMT


Author's response (Dora L. Costa and Matthew E. Kahn)

We appreciate the opportunity to respond to Brian H. Reid’s thoughtful review of Heroes and Cowards: The Social Face of War. Given book review publication lags, we have eagerly awaited the first set of reviews written by historians to appear. We have wondered how a book that is set in the Civil War but is not about the Civil War would strike historians.

Our book differs from the hundreds of Civil War books published every year in two ways. One is methodological. The second is that our book has implications beyond those four years of bloody combat and its immediate aftermath. We examine four main questions that are basic to social science research. First, when are men willing to sacrifice for the common good? We answer this by looking at why men deserted during the Civil War and find that men in more homogeneous companies, companies that were more similar in occupation, ethnicity, and age, were more loyal. Our second question is what are the benefits to men of friendship and of community? Loyalty to comrades raised men’s chances of dying during the Civil War. We find that the stronger the ties between men (and ties were stronger when men had more in common – whether because they were related or because they were of the same ethnicity), the more likely men were to survive the hell holes that were Civil War POW camps. Our third question is how do communities deal with betrayal? We found that during the Civil War men who had betrayed their communities by deserting moved away, driven out by shame and ostracism. We conclude that community codes of conduct are reinforced not just by loyalty but also by punishments. Our work shows that more diverse communities are less cohesive. Their members are less willing to sacrifice and derive fewer benefits from being part of the community. Our fourth and final question is whether there are any benefits to living and working in a diverse community. When we look at the lives of black soldiers after the Civil War, the tensions between the short-run costs of diversity and its long-run benefits become apparent. Men did not like to serve with those who were different from them, so much so that they were more likely to desert, but in the long run the ex-slaves who joined the Union Army learned the most from being in units with men who were different from themselves.

Our book is about the costs and benefits of diversity in any organization, not just in Civil War companies. The same factors play out in terrorist organizations, in United States cities, on college campuses, and in towns in developing countries. Men may measure similarity in different ways across time and space. The distance between us may now be more likely to be education rather than ethnicity, but the basic lesson remains the same. A community of similar people is likely to be cohesive and its members are likely to sacrifice time, effort, and even their lives for each other. But in a diverse community members can learn from one another.

Much of history is written as if each case were unique. While each case does have unique features, we approach history as allowing us to uncover basic facts about human behaviour.

Our work is a quantitative history. Unlike many historians, we avoid using diaries and letters as our primary sources of evidence. Not only is ‘talk is cheap,’ but it is also the talk of the literate. Many black soldiers’ stories cannot be told if one does not ‘crunch the data’. Second, sophisticated men may ‘spin’ their diaries with an eye to history as they re-write events to play up bravery and downplay cowardice. We therefore focus solely on outcomes we can observe in our data. Who deserts? Who survives? Who migrates where after the war? Who deserts? Who survives? Who migrates where after the war? These are well defined, costly choices that are easily amenable to statistical analysis.

We are not arguing that statistical analyses do not come without their drawbacks. (These are not, however, the drawbacks pointed out by Brian Reid. For example, when we say that ‘A good soldier was older’ we are not drawing any inferences beyond unit loyalty. The physical demands of the job are a completely different matter.) We acknowledge that one of the limitations of our study is that we have very little to say about the importance of leadership. We do find that having one of your own officers (and most of these officers were non-commissioned officers) with you in a POW camp, improved your survival probability. We can say that for black soldiers having an abolitionist officer decreased desertion rates but that the effect was relatively small. We agree that we could have done more with the non-commissioned officers for the white troops. The empirical challenge that a researcher faces in measuring the effects of ‘good leadership’ is to identify before combat begins who are the ‘good leaders’ and who are the ‘bad leaders’.

Finally, we want to emphasize that we do not just ‘exploit the 41,000 computerized soldiers’ records in the National Archives.’ Dora Costa has spent almost 20 years working on the digitalization and analysis of these records. The Nobel Laureate, Robert Fogel, has spent more years on this project. The final product is a unique data base that provides the life histories of men before the war, during the war, and after the war. A unique feature of our study is our ability to recreate each soldier’s peer network. We can do this because of the way the sample was drawn. The Union Army was built from companies of roughly 100 men. Our sample is based on randomly sampling companies and then conducting a 100 per cent census of all men in a randomly selected company. Without jargon, this means that for any soldier in our sample we also know information about all the other soldiers in his war company. These men lived together 24 hours a day and were forced to interact with each other continuously.

Our book does not reveal the full power of the Union Army data base. The data base has been used in studies of health and of retirement. Work is underway to continue to expand the data base to examine specific subpopulations. The data base is currently available at http://www.cpe.uchicago.edu . We encourage other researchers to use this unique resource.

October 2009

People in New York City want clean water to drink and access to cheap natural gas. This article highlights the tradeoff. To protect the water supply from pollution at the drill site, the energy company has been pushed not to drill in upper New York State. Given that the company believes that a huge amount of natural gas is located there, they are frustrated. Would a Torts lawyer have come up with a contract to encourage the energy company to devote careful effort to minimize the liability concerns? Is zero drilling "optimal"?

The "big issue" here is how much risk (to the water supply in this case) are we willing to take on in return for some benefits? If the water supply can really be poisoned by the energy company's pollution, then I certainly support this decision but is that true? There is really no way to craft a moderate position here?

Of course, I want my mom (in New York City) to have clean water and there are 20 million people like her in the region. But, what is the cost of banning this drilling?

In this Economix Piece , Ed remembers a great economist. It is striking that a great man's life can be boiled down to roughly 2000 words. You live for 25,000 days (if you are lucky). At 10 days a word, this piece is a powerful reminder of John Meyer's key contributions to economics.

Today, transportation economics is a vibrant field. With the rise of GIS techniques and some efforts to model the political economy of where infrastructure is built; the causes and consequences of transportation investment is an ongoing research effort. Meyer gets a lot of the credit for this.

According to this article , Columbia University plans to move some Nobel Laureate faculty from their current Medical School location to a new location. Will this raise or lower productivity of the Medical School as a whole? Presuming that the Nobel Laureates offer positive local spillover effects (is this always true?), the losers will be their current neighbors. The article quotes a colleague of theirs who implies that it would be a bad thing to move them. Now, I don't know if their destination is randomly assigned but this design bears some similarity to Josh Zivin and Pierre's work on Superstar Scientists. Now they use death as a measure of breaking the network. I guess I am assuming that migration away from the "Mother Ship" is equivalent to death.

If the productivity spillover effect is so high, why are the Deans moving the laureates? Do the Deans not know the true parameters of the model? If they are risk averse why are they rocking the ship? While I'm cracking jokes, a Dean is supposed to be a benevolent planner who internalizes externalities. If these guys can't achieve an efficient allocation of resources within the firm, then maybe Oliver Williamson needs to be called in for some Nobel to Nobel consulting.

We roughly know what economists do all day (teach?, blog?) but what about everybody else? In this interview, UCLA's Richard Ambrose sketches his background and explains why he studies water systems.

Now that I know the modern research university, I still think I would have entered academic economics. A good friend once told me that I would have been a homeless person had I not become an economist. Now, that's comparative advantage!

Merely out of self interest, the other fields require that you do 1 or 2 Post-Docs. Some very talented scientists are not guaranteed academic jobs. While the Scientists are given expensive lab equipment, their salaries tend to be low. In terms of intellectual substance, it certainly would be exciting to come up with a cure for cancer or baldness but I do not have that type of mind. I know that I couldn't have cracked such problems. I do see the links between random ideas. So, I'm a permutation guy. I read a lot of stuff and then I see how stuff that looks independent and unrelated actually fits together and out comes a new paper based on this "Resses Peanut Butter Cup".

James Hamilton has written a great pithy piece on the possible causes of the recent deep recession. As a retired macroeconomist (I dropped out in 1988), I wonder how modern macro guys will figure out how to disentangle the possible explanations that he poses. What calibration exercise will count as a "test"? How will model builders nest the various possible explanations? We seem to have more theories than data points so as "scientists" what happens next?

I do find the "fundamentals" versus "sunspots and panic" explanations to be pretty stark but how do we disentangle these? I must admit that when Hank Paulson and Ben Bernanke were talking "doom and gloom" to justify the TARP (circa November 2008?) they spooked me out. I can't say that I panicked (I didn't change my portfolio at all) but I did assume that they had better information than me about the real state of the relevant state variables. So, my point is that the game theorists must enter macro. What was Bernanke "maximizing"? What game did he think he was playing with Congress and the taxpapers? How did his announcements shift expectations?

I woke up at 430am this morning to participate in this debate on Japan's efforts to reduce its CO2 emissions. I'm glad I did it. The other NHK panelists were smart. The challenge is that I do not speak Japanese so the translator was constantly taking my words and translating them so there was a delay. I had to look at myself on the TV monitor and that was a scary sight. There was also a slight delay in transmission so when I moved in real life, I moved slightly on the tv screen 1 second later. This took some getting used to. I also learned that my mother is right. When I'm normally listening to a person , I have a slight scowl on my face and this looks like I'm in a bad news. To counter this, I forced myself to half smile while the other panelists were speaking. This (costly) action made me look like a "normal" person.

In terms of substance, the conservatives in Japan's government have estimated that this carbon mitigation legislation will be very costly in the short run. While I agree that carbon legislation is not a free lunch, I argued that the CGE models that estimate precise numbers for how households will fare in the face of carbon legislation should not be taken very seriously.

I pushed the panel on whether Japan could meet its co2 reduction mandate by ramping up nuclear production of electricity and lower reliance on oil and coal in generating power. The panel agreed but said that the Japanese public fears "too much" nuclear power. So this sounds like a nimby issue.

We talked about a number of relevant issues. I argued that the success of the Toyota Prius as an export product highlights that in the face of globalization, japan could help its economy in the medium to long term with this green push if this pushes green innovation that yields future export products.

Who said that California no longer creates jobs? Here is a new "green job". Your office will be pretty close to mine and you may actually see me once in a while. In sunny Los Angeles, I mainly work outside but I certainly do appear at the UCLA Institute of the Environment. In my humble opinion, this is an excellent job. I will be serving as one humble member of the search committee. I seek someone who can help me raise my productivity.

More seriously, Junior faculty and new PHDs should apply if they have a real desire to work in an interdisciplinary research environment. If you are a structural IO guy who is only interested in formal identification results, then this is not the right job for you. You won't "backdoor" your way into UCLA economics. You can have as much contact with UCLA's excellent economics dept as you wish but at the end of the day our new hire's focus will be the IOE.

To read more about the IOE and who we are go to www.ioe.ucla.edu .