Asterisks of Gall(?)

One of the biggest news items in the last week was the release of the Mitchell Report, which investigated the prevalence of steroid use in Major League Baseball. Pretty much everyone has had something to add to the discussion on performance enhancing drugs. I've been following the story as it develops and had some scattered comments of my own (unfortunately, grading lots of tests and finishing up for the semester prevents me from putting this in the usual essay format):

1) The Blame Game - People have been quick to vilify some of the players named in the Mitchell report as cheaters. For some of the bigger names, such as Roger Clemens, the buzz surrounds whether or not they should be inducted to the Baseball Hall of Fame or not. I am having a tougher time burning effigies of these players. Why? Because they aren't the real culprits behind baseball's "steroid era."

Here is my take. Suspicion of widespread use of steroids and other drugs was growing as early as the late 1980s and early 1990s. Major League Baseball did not take any steps as far as stringent testing and penalties until over a decade later. In the meantime, the use of performance enhancers likely lead to increases in wages and length of tenure for the average player. Given the low level of deterrence and potentially large expected benefits, players went for steroids and HGH, their preferences for health and discount rates notwithstanding. Perhaps there were even externalities from usage: a single player or groups of players performing better and accruing higher wage earnings likely upped the ante for everyone else to performance better, further tipping the cost/benefit balance over to usage.

In any case, the MLB did nothing for a really long time. Not only that, post the strike induced lock-out in the early 1990s, the game was essentially "saved" in the eyes of paying fans by the steroid induced home run chase in the summer of 1998. The MLB's inaction and their packaging of the game in terms of increased power hitting and speed likely created the right kind of incentives to induce the marginal player into trying to get the extra boost.

2) Asterisks - Putting asterisks on records held by suspected users of performance enhancing drugs seems like a difficult proposition to me. If the Mitchell Report is indeed the tip of the iceberg, and use of agents like anabolic steroids and HGH was (and is) widespread, it is hard to distinguish between "legit" and "cheater-induced" records and probably unwise to try and do so. Rather, interpretation of statistics should be left up to discerning fans.

Still like asterisks? Given the discussion in (1), try this one: MLB*.

3) "Steroids don't help you ______" - Some players and analysts claim that performance enhancing drugs do not really help you become a better baseball player. Two supporting arguments are generally cited. First, steroids and HGH do not help you develop the mechanics to hit a ball, work a pitch count, etc. Second, many of the players named in the Mitchell Report are scrubs - steroids didn't help them hit 50 home runs or clock 95 on their fastball.

Regarding the first point, here is a quote from Ken Caminiti (just one of a brilliant collection in http://www.baseballssteroidera.com):

"The stronger you get, the more relaxed you get. You feel good. You just let it fly. If you don't feel good, you try so hard to make something happen. You grip the bat harder and swing harder and that's when you tighten up. But you get that edge when you feel strong. That's the way I felt. I felt strong, like I could just try to meet the ball and -- wham! -- it's going to go 1,000 mph. Man, I felt good. I'd think, Damn, this pitcher's in trouble and I'd crush the ball 450 feet with almost no effort. It's all about getting an edge."

The second argument is really easy to deconstruct: we simply do not know how these players would have done had they not use steroids (assuming the allegations are true). The scrubs on the list may have never even made it to the major leagues without the extra jolt. Steroids likely provide a boost to players sitting at any level on the baseball skill distribution: they don't have to make you an all-star, but they may make you slightly better than you were before. In a competitive industry, this might be all the edge you need.

4) "The game of baseball has been denigrated" - Can anyone honestly tell me that this scandal, involving individuals cheating in order to perform better, is worse than the 1919 White Sox scandal and the match fixing scandal in international cricket where, in both cases, teams intentionally threw games? Sports have weathered these storms in the past. Baseball will be always popular and its heroes will come and go, steroids or not.

5) What to do now? - One the one hand, the Mitchell Report suggests stringent testing, harsher penalties and player education to stem the use of performance enhancing drugs in baseball. On the other hand, some analysts argue that it is impossible for testers to keep up with innovations in performance enhancers. After all, existing tests still cannot detect "the cream" and "the clear," substances Barry Bonds is suspected to have used. In fact, Marion Jones, who admitted using these products never tested positive, covering over 160 tests in sum. In this situation, these observers argue that legalizing these agents in the game and regulating their use with physician oversight might be a better way to go in terms of player health and leveling the playing field.

I'm not sure where I stand on this one, though I think I would lean towards trying to rid the sport of performance enhancing drugs. For one thing, I'm not really convinced by the "arms race" argument against more stringency. Following Gary Becker's seminal analysis on crime, suppose that the average player will use steroids if the expected benefits outweigh the expected costs. In this framework, expected costs are equal to the probability of being caught * the value of the costs themselves. Those who think we'll never catch steroid users believe the probabilities will be too low to give any bite to the costs. On the other hand, increasing penalties, publicly "outing" suspected users, and introducing uncertainty into Hall of Fame chances may jack up the costs enough to outweigh the lack of change in the probability. After all, do you think many players or managers are going to try and pull a Pete Rose now given all that he has been through? Social norms and pressure can be powerful and perhaps more stringency, then, could be a good policy to go with.

A thoughtful post by The Sports Economist provides more arguments for "cleaning up" baseball. One of the more interesting thoughts in that piece, which was alluded to earlier here, is that steroid use by a given MLB player has externalities: others will want to use it in order to compete and this will be true all the way down the pipeline. Where it becomes dangerous is at the level of younger people, who do not possess the resources to have a personal trainer monitor their use. This could have adverse health consequences both in the short and long run.

There is some evidence of noteworthy use of steroids in high school. This piece in JAMA suggests that almost 7% of high school senior athletes have used anabolic steroids. Of these, many started on their regimens as early as junior high. 7% seems like a pretty big number to me. What would be nice to have are figures relating likely steroid-driven adverse health events among this group and information on why these kids decided to initiate such regimens. That way we could get a sense of the extent to which externalities are operative in steroid use.

When Bad Inference Happens to Good People

I turned on ESPN yesterday night for some pre-game analysis on the Houston Texans-Denver Broncos contest. I wasn't paying too much attention until I heard the following statement: "One of Houston's keys to victory tonight is to give Ron Dayne 20-25 carries."

I did a double take. Ron Dayne? An NFL journeyman with decent size, but limited speed, who is best utilized in a platoon of running backs? It turns out that the analyst was basing his comment on the following fact: the Texans are 4-1 in the past two seasons when Ron Dayne gets more than 20 carries.

This is another example of people confusing correlation for causation. There are two (or maybe more) explanations for the Ron Dayne tidbit:

1) Ron Dayne is a game changing talent who, if given the ball, will more often than not win the contest for you.

2) Ron Dayne getting 20 carries or so is a symptom of things working right offensively for the Texans. When the Texans are firing on all cylinders, Dayne's rushing opportunities and totals may reflect the fact that linebackers and safeties are playing off the line of scrimmage and drop back into coverage, allowing Dayne to get his 5-10 yard runs, or that offensive line play is so dominant that Dayne is able to run clear through the woods.

I think the second explanation is probably the more likely one. After all, can you imagine a defensive coordinator thinking before a game, "wow, we need to get 8 in the box to stop Ron Dayne"? Ron Dayne is a good player, but he's not LaDainian Tomlinson or even Frank Gore - the 2007 version.

In any case, this innocuous episode reflects the danger of attributing causal stories to what are only correlations. Unfortunately, fates of entire policies have hinged on bad inference, that too in arenas less trivial than professional sports.

Time Inconsistency, Parking Tickets and Health Care

The New Haven police gifted me a parking ticket a couple weeks back. The payment scheme for the ticket works something like this: it's $15 if you pay it within two weeks or so, $30 if within four weeks and $60 thereafter. I still haven't paid my ticket, so I am looking at about $30 right now.

Am I just completely insane? Why didn't I pay my ticket on time? I could have saved at least 15 bucks. Well, as it turns out, I always did (and still do) intend to pay it sooner rather than later. But getting an envelope, writing a check and sending the thing out was (and is) kind of annoying process to me. Every day I would say, "I'll do it tomorrow."

This is what is called time (or dynamic) inconsistency. The basic idea is that one's current self and one's future self (say tomorrow, or next month) have differing ideas on what actions should be taken (present or future). This is more than a theoretical construct: its a pretty big deal in health economics. An example (taken from the above linked wikipedia page):

Each day smokers face a dynamic inconsistency: their best plan is to enjoy smoking today, but to quit tomorrow in order to get health benefits. However, the next day, the plan is the same; enjoy smoking today and quit tomorrow. This goes on, and they never give up, even though they plan to, hence the inconsistency.

You can easily see how this behavior is important in understanding other health behaviors, such as dieting and other weight loss efforts or perhaps even going to the doctor to get some anomaly checked.

If time inconsistency is a strong barrier to self-motivated health efforts, how does one get around this? Yale economist Dean Karlan and law professor Ian Ayres think they have an answer. The two have recently started a company called StickK. Here is the basic idea:

The company will have a Web site offering individuals hoping to reach a goal — anything from sticking to a diet to learning to ride a unicycle — legally binding contracts where they will pay a set dollar amount to charity if they fail in their endeavor.

The author of the book "The Undercover Economist," Tim Harford, is testing out StickK's methodology. He has paid a $1,000 so-called contract bond to the company, and has promised to donate 10% of this deposit to charity if he fails to complete 200 push-ups and 200 sit-ups every week.

"When I signed up to do this, I thought to myself, the contract bond isn't going to matter at all; what's relevant is that I've made the psychological commitment to do these press-ups and sit-ups," he said. "I was completely wrong. There's absolutely no way I would have done these press-ups and sit-ups for the past six weeks had it not been for the commitment bond."

I'm really curious to see a) how many people choose to enter binding contracts and b) how effective these are for the average consumer.

In the meantime, I think I'll pay my parking ticket...tomorrow.

Fashion Show Economics

I watched the Victoria's Secret fashion show a few nights ago. It was just fantastic. Here are a few interesting tidbits I picked up:

1) Heidi Klum is a good singer.

2) Only B-list celebrities appeared to be interested in actually showing up to the event. Ryan Seacrest? The Spice Girls? VS is offering this two day only promotion where any purchase of $60 dollars or more gets you a free Spice Girls CD. A neat little study for an undergraduate or intro stats class: using discontinuities in the sales promotion to identify causal effects, does the prospect of a Spice Girls CD induce more people to shop and buy at the store? Does it move the marginal $56 purchaser to buy the extra item that puts her over the top?

My priors tend towards the null on this one.

3) The most interesting feature of the show were the model biopics. Many of the models were discovered when they were 12-14 years old. I find that really amazing. How much certainty is there in forecasting whether a 13 year old will turn out to be a supermodel or not? I'm not sure where you can get data on this question, especially given the obvious selection bias - for every Selita Ebanks or Adriana Lima, there are probably 100s of others that you don't observe that don't make it.

To get around this, I thought about the compositional change in the popular clique between 7th and 12th grade in high school. The popular clique in any school is generally comprised of the "hot people," and is generally superficial enough to kick out people who move from hot to not as well as embrace people who move in the other direction. I estimate that about 68% of the popular clique in 7th grade continued to be popular in 12th grade. This larger inter-grade correlation can be explained by persistence in looks and social status as well as the bond of friendship, though its hard to pin down the relative contributions of these factors.

Even so, I think making predictions about a 13 year old is still really difficult. Of course there has to be some science to it: some people have a comparative advantage in discovering models and make a career out of doing so. Indeed, there are a lot of industry specific skills that are either innate or learned. If you've watched America's Top Model, it's easy to get a sense of this: Tyra and the other judges rate the contestants on a vector of different characteristics, where some of the elements are obvious and others not so much.

But at the end of the day, you just never know. A pharmaceutical company, for example, mines through a myriad of candidate molecules, finds the ones that are bioactive, and pushes those forward for further testing. The vast majority of these new chemical entities or compounds will fail, either to be refined or scrapped altogether. But some do make it, and the incentives are such that its worth pushing forward and leaving no stone unturned. After all, the next molecule you find might be worth billions.

I'm guessing there's a parallel to supermodels. As a model finder or agency, you don't know if your 13 year old will turn into John Abraham (the Indian one, not the guy on the Jets), on the one hand, or Atheendar Venkataramani, on the other. But you take the risk, and if it is indeed the former case, there are huge returns to be had. And, for a time, those returns might be increasing in the earlier you find the next great supermodel. Indeed, just as competitive forces push Merck and Pfizer into random jungles looking for even more random plants, the modeling industry probably evolved on a margin where those who moved first in finding younger and younger prospects were able to gain a leg up on their rivals.

The Deep Structure of the Universe? (Some Friday Fun)

I went to an interesting talk last week on why individuals don't choose to buy long-term care insurance. While the speaker did not have an answer to that question just yet (it's a work in progress), she did have a lot to say on the use of qualitative methods as a set up for and complement to statistical methods. In the past I've made fun of qualitative work as a "be all, end all" strategy in attacking a given research question ("its not representative," "it takes forever to do," "I don't believe things if there is no math or hard data," etc). But I do agree that qualitative work can help give direction to statistical analysis and aid in the interpretation of sempirical results.

Anyway, in explaining the mechanics behind the qualitative methodology, the speaker pointed out how sampling in qualitative methodology essentially obeys the law of diminishing returns (called the saturation principle, here). Basically, you keep adding to the sample until you stop learning anything new - when the marginal returns to interviewing approach zero. Apparently the majority of qualitative studies saturate somewhere between 25 and 30 subjects/interviewees.

I had a sudden flash of insight when I heard these numbers. The Central Limit Theorem (the big one) posits that the sum of a vector of random variables distributed with finite variance approaches a normal distribution for large values of n. Imagine a really screwed up probability distribution. Draw n numbers from it, and take the sum. Do it over and over and look at the distributions of the sums. Boom! Its looks normal! Its a beautiful result, and the proof is quite elegant, too.

The Central Limit Theorem appears to kick in around n of 30 or so. Thats whyI got so excited about the saturation numbers: its just interesting that two apparently distinct phenomena attain right around the same sample size. Obviously, I could be exhibiting a classical behavioral economics bias and attributing patterns to what are basically unrelated phenomena that just so happen to agree with one another. On the other hand, maybe there is more to it - something fundamental and deep.

Some more: If you like these kind of oddities and puzzles, you should read Fermat's Last Theorem by Simon Singh. It's one of the best books I've read in a long time. Basically it covers the 300+ year history of this annoying and outstanding math problem that kids can understand but adults (including Hall of Famers like Euler) could not solve for several centuries. The beast was laid to rest in 1993 by a Princeton mathematician who spent something like a decade of his life working on this problem and this problem alone. While the problem for a long time looked like some trivial curiousity, the Last Theorem ultimately speaks to some deep connections between branches of mathematics thought to be distinct.

The book is chock full of short biographies of all the mathemeticians who made contributions to solving the problem, interesting nuggets about number theory and the fundamental importance of prime numbers, irrational numbers, etc, and insights into how seemingly trivial mathematics could have mighty big things to say about the natural and physical world. It's a great read, and allows us normal folk to catch a glimpse into the beauty of mathematics.

How Can You Not Love Fantasy Football?

I've copied a recent post from our fantasy league discussion board below. When I realized how ridiculous it would sound to people who aren't part of our league (or are non-participants in fantasy sports in general), I started laughing and couldn't stop. I'm still laughing now.

Just to put it in context, we have twelve teams in our league and six playoff spots. This is the final week of our regular season. Three teams (myself included) have clinched playoff spots and a whopping seven teams, all 6-6, are fighting for the other three.

Here goes:

I don't know if we've ever had a week as exciting as this right before the playoffs. Each of the 6-6 teams could end up in the playoffs.

Homechickens has to win to get the 1st round bye.

Hufflepuff and Bum Bum are playing for the first 1st round bye.

Then it gets really interesting.

Harmonica and FightingIrish control their own destiny and are into the playoffs with a win.

Regal, Detroit, Drunken, and Buckeye are also competing with each other for points scored this week b/c they are all within 40 pts. of each other.

dags needs to win and have DetroitLions4eva lose to make the playoffs.

It's pretty cool b/c everyone has something to play for.

Cheer for my team!

Obesity in Developing Countries? Part II

More on the association between early life circumstances and later obesity. Check out this new working paper by Anne Case and Alicia Menendez on gender differences in obesity in South Africa. Here is the abstract (emphasis mine):

Globally, men and women face markedly different risks of obesity. In all but of handful of (primarily Western European) countries, obesity is more prevalent among women than men. In this paper, we examine several potential explanations for this phenomenon. We analyze differences between men and women in reports and effects of the proximate causes of obesity -- physical exertion and food intake -- and the underlying causes of obesity -- childhood and adult poverty, depression, and attitudes about obesity. We evaluate the evidence for each explanation using data collected in an African township outside of Cape Town. Three factors explain the greater obesity rates we find among women. Women who were nutritionally deprived as children are significantly more likely to be obese as adults, while men who were deprived as children face no greater risk. In addition, women of higher adult socioeconomic status are significantly more likely to be obese, which is not true for men. These two factors can fully explain the difference in obesity rates we find in our sample. Finally (and more speculatively), women's perceptions of an 'ideal' female body are larger than men's perceptions of the 'ideal' male body, and individuals with larger 'ideal' body images are significantly more likely to be obese.

Root for the Underdog of the Season!

For the last nine years, I've been playing Yahoo! Fantasy Football with the same group of college and high school buddies. In this time span, I've only been to the playoffs in four times and have yet to win a single playoff game. I fielded my best team in 2002, destroying the opposition to go 10-3 and finish regular season number one. Then, in the flameout of all flameouts, I lost each of my three playoff games and finished in 6th place.

Basically, as the "owner" of my team, I would fire myself as GM and Coach. I might as well set up the team and outsource all the decision making to someone who knows better.

Anyway, this season, with two games left in the regular season, I am sitting in second place at 8-3, having scored more points that each of the teams below me, and just five points off the pace of the first place squad. I've clinched a playoff spot, and I am hoping to win it all.

I think you should root for my team this year, especially because since my squad is the kind of underdog everyone would want to root for. Here is why:

1) I've overcome adversity at multiple points this season - I lost Ronnie Brown, who was an early season fantasy hoss, for the year, Jevon Walker for most of the season, and David Gerrard for a crucial four game stretch. Despite this, I keep winning. I attribute this to my unusually good waiver wire strategies (see 3).

2) My squad is made up of a lot of cast-offs and feel good stories - For example, my starting QBs are Jeff Garcia, a journeyman, elderly statesman, and David Gerrard, who wasn't even supposed to start when I drafted him. My backup QB is Vinny Testerverde, a guy my father remembers seeing play when he was in grad school. My second starting RB is Jesse Chatman, Ronnie Brown's replacement in Miami who kept getting kicked off of his past teams for being overweight. My defense was drawn entirely off the waiver wire (I missed the live draft when I was in South Africa). Finally, even my lovable uber-star, the incomparable LaDanian Tomlinson, is having an off year (by his standards, anyway).

3) The owner really needs this win - My college roommate, a three or four time champion, keeps pointing out how I've historically sucked at fantasy. In the past, other owners have criticized admittedly stupid roster moves I've made (for every mid season trade for Larry Johnson, I've drafted rookie WRs in the fourth round). I need to win both to earn respect and to offset what has been a ridiculously dry semester of research.

Also, did I mention that I haven't won a playoff game in nine years? There is only one way to describe that: hapless.

4) Finally, my team is named Hufflepuff's Cup, in honor of the kind but ultimately unremarkable Hogwarts House. Its funny how my team has turned out to be just like them: no stars, just solid performers who put their hearts and bodies on the line for me every week. How can you root against a team like that!?

So, for the next five weeks, root for Hufflepuff's Cup. It's like cheering for Rocky or those Chak De India girls: its a tough ride but, in the end, I think you'll be glad you stuck with 'em.

Thanksgiving: A Good Time to Think About Obesity

Related to my earlier post, I just came a recent article about the driving forces behind obesity in the developed world. Here is a link to a non-technical summary of the paper (a link to the actual article is nested within) and here is nice analytic piece by the Healthcare Economist.

The major take home point is that most (over 90%) of the increase in obesity seems to be driven by the fact that people are eating more now than before. The authors of the paper contend that the other side of the equation, decreased caloric expenditure, is quantitatively less important, though still non-trivial.

The main question then is: why are people consuming more calories? The theories out there to explain this generally fall into two categories:

1) high monetary and opportunity costs of healthy foods relative to unhealthy foods (the proliferation of fast food joints, putative effects of US agricultural subsidies, etc)
2) lower costs of calories in general due to improvements in agricultural technology

I don't know if anyone has really been able to assess the relative (or even absolute) importance of these explanations in the data. I do know that obesity is a scorching hot area of research and that the coming years should provide us with a slew of new research evidence for us to feast on. A good example: a new working paper assessing the fast food joint-obesity link.

In the meantime, Happy Thanksgiving and enjoy the inevitable feast!

Obesity in Developing Countries?

I'm doing some research on nutrition, child health and public programs in Mexico and, in the process of looking for a paper, came across this interesting article in JAMA about obesity among the Mexican poor. It turns out that obesity rates among the poor in Mexico rival those in the United States (obesity rates in general have followed a similar trend to the US, with large increases occurring between the 1980s and 1990s). This is especially interesting given that poor Mexicans live in conditions similar to the developing world, where obesity is only common among the upper strata of the population (though this is starting to change; exs: rural India and China). Doubly interesting is the growing phenomenon of young children who are both stunted and overweight, an interesting paradox of early life deprivation, on the one hand, and excess on the other.

Causes for the rapid increase in Mexican obesity are likely similar to those in the U.S.: changes in technology and policy that alter the balance between caloric input and output. For example, this paper notes that increasingly sedentary lifestyles and changes in diet are likely largely responsible for increased fattening. While I'm not sure if anyone has really stepped in and done some kind of accounting exercise or decomposition trying to explain time-trends in Mexican obesity, this doesn't seem to be a bad conjecture to make given the evidence.

We know from the United States that the poor are much more susceptible to these secular trends: healthy food appears to be a normal good, fast foods inferior, and exercise a luxury good. At least from what I can gather from the Mexican evidence, this is likely to be the case south of the border, as well. But are there reasons, external to basic economic theory, that might explain why the poor tend to be more obese?

There are some interesting biological theories that suggest that individuals who are deprived of nutrition while in the womb but exposed to relative abundance thereafter are more likely to become obese, diabetic, and develop cardiovascular disease. The idea is that fetus' adapt to scarcity, which results in permanent metabolic/endocrine changes. While these changes are advantageous in scarcity, the might actually be maladaptive in situations of relative abundance. Some evidence supporting this theory in (laboratory) animal and human populations can be found on pp 44-45 of this very thorough survey on the economics of health and socioeconomic status in developing countries (a must read for all interested in health and development as an area of research).

So tying this back to poverty: poor individuals are either more likely to be born in situations of deprivation or, in the case of economy wide shocks, unable to smooth their consumption so as to prevent under-investments in their kids during the fetal period and early childhood years. Faced with falling (unhealthy) food prices and secular changes in the level of human activity, if the biology behind the aforementioned theory is sound, these individuals might be doubly affected in terms of developing metabolic and cardiovascular conditions. Notice that the theory would also explain the stunted/overweight kids: stunting is a result of the fetal adaptation to scarcity, and overweight the result of exposure to abundance.

While some work on the Dutch and Chinese famines support this hypothesis (see the previous link), I am not aware of any other work looking the interaction between early life conditions/endowments and secular changes in technology. As a result, and since the marginal cost of adding this on as a project is low (I am using a well-suited Mexican dataset for another purpose, anyway), I've decided to have a go at the theory and see what I find. I'll keep you posted.

Review: Chris Cornell 2007 North America Tour

A few weeks ago, I decided to take a five minute break and visit rock-icon Chris Cornell's website. In July, I was lamenting the fact that I would be unable to attend any of his summer concerts, set up to promote his new solo album Carry On, because of a trip to India and South Africa. Actually, I wasn't lamenting it all that much since I was excited to go abroad and Carry On was pretty bad. Anyway, I had heard a rumor that Chris would be starting a new North America tour and wanted to get a sense of whether I would be able to go to any of the concerts.

To my surprise, Chris was set to play at Northern Lights in Clifton Park, NY, on Nov. 10th. The venue is literally 0.9 miles from my parents' place! Within five minutes, I had already bought my tickets and had told pretty much everyone I know that I would be going to the concert. According to the website, Cornell and his touring band would be playing hits from his 13 album career, spanning bands like Soundgarden, Temple of the Dog and Audioslave, as well as some of his solo work.

If that sounds incredible to you, get this: the concert surpassed my expectations on every level. The opening act, the multi-racial Earl Greyhound from New York City, brought in some hard, soul power to the proceedings. A nice little appetizer for ridiculously incredible stuff that was to come.

Cornell made a grand entrance with "Let Me Drown", from the Soundgarden album, Superunknown. Standing at 40+ years, mellowed out, and in the middle of a transition into an adult contemporary like-solo career, Cornell still came out and worked it like old times. A six song acoustic set (which I really enjoyed), including "Call me a Dog," "Like a Stone," "I am the Highway," and his now infamous rendition of "Billie Jean," along with "Arms Around Your Love" was the mellowest this show got. The rest of show featured Cornell screaming and slamming through vocally demanding selections like "Outshined," "Jesus Christ Pose," "Rusty Cage," "Ty Cobb," "Cochise," and "Show Me How to Live."

All in all, he ended up performing 28 songs, with a lot of Soundgarden and Audioslave for the (relatively) older and younger fans alike. I'm guessing its got to be hard to please everyone when sampling from your greatest hits spanning a 20+ year period. It's a testament to the quality, depth and variety of this concert that my only complaint was that Cornell did not perform "Burden in My Hand." No worries, though: the multi-song encore more than made that little point irrelevant.

I could go on all day praising this concert. Instead of doing that, though, I'm going to let the proceedings speak for themselves. Check out this snap and video clip. The sound quality on the latter is quite suspect, mainly because I was so close to the stage and, therefore, the speakers. I hope you can make out that this is a snippet from "Spoonman." Enjoy.

Public Health in India: Some New Data

The Ministry of Health and Public Welfare in New Delhi recently released data from the third National Family Health Survey (NHFS-3), based on a nationally representative sample of women aged 15-49 year women. The survey provides information on health and welfare for nearly 200,000 women, as well as their spouses and children. For a variety of reasons, this survey is a potential gold mine for public health, health economics, and public policy research projects. You can have a look at the details here. The summary report, which is very thorough and serves as an excellent reference for all things public health in India, is available via the same link. It is essential reading for all Indophiles, whatever your discipline or persuasion may be.

I've glanced through the summary report myself and have found some really interesting things (some of which will likely serve as fodder for research in the coming months). Here is a sampling:

1) The NFHS-3 is the first large scale all-India survey to include HIV testing. Surprisingly, despite local resistance in states like Nagaland, nearly 82% of eligible women and men were tested. This is a lot higher than I would have imagined given stigma around HIV/AIDS combined with voluntary testing. The survey finds that 0.28% of adults 15-49 have tested positive for HIV, that the prevalence of HIV is much higher in urban areas and among men. Also, HIV in India does not seem to discriminate by caste or level of wealth. In fact, the highest positive rate is among one of the top wealth quintiles in the sample.

2) Over 70% of children under 5 are considered to be stunted (i.e., below 2 sd from the median height for a child of given gender and age in months). However, only 32.9% of all children in the sample received services from the Integrated Child Development Services (ICDS) program, a village level intervention designed to provide basic health, nutrition and educational services mothers and young children, which now has very wide coverage in India. This isn't an issue of coverage: that 32.9% figure applies to all children who live in an area with ICDS facilities. I find this really interesting. ICDS offers free services and free food and children are malnourished. So why aren't more mothers taking it up? There are a variety of reasons why this could happen: ICDS is perceived to be ineffective; supply-side problems, such as failure to staff the clinics; high opportunity costs to attending ICDS (long-queues, remote locations); lack of knowledge among mothers or heterogeneous treatment effects that induce self-selection among certain classes of families. I think it would be interesting to compute (heterogeneous?) returns to the ICDS program and get a sense of why people are not going.

3) Less than half of all households in India use adequately iodized salt. This could have tremendous long-term consequences, especially for young children. Check out this important and interesting paper by Erica Field, et al, for more information.

4) The data is representative at the state level as well, and its always fun to compare how different states do with respect to various health indicators. Obviously, there is a great deal of variance among states in population health status.

5) There is plenty of other interesting information on anemia among men, women and children, female bargaining power and domestic violence, knowledge and attitudes about HIV/AIDS, household socioeconomic status, and so forth. Again, its a pretty rich survey for public health stuff, and I encourage you to check it out.

The Salience of Personal Experience

I had an interesting discussion with my mom today about a new working paper on arranged marriage. The basic finding in the paper is that, among a large sample of families in Mumbai, India, men who find their partners via arranged marriage are much less likely to marry college-educated and/or working women. The paper makes a valiant attempt to show that this is being driven by arranged marriage specific parental preferences rather than omitted variable bias.

My mom, an extremely intelligent person who, like all mothers, "knows best", had the following comments:

1) I am not sure whether this finding would hold up in other parts of India.
2) I don't buy the finding because I know so and so, and they married someone highly educated through an arranged marriage process.

My mom makes a valid statistical argument with the first point: underlying parameters may indeed differ across populations. There is no way to know whether these findings replicate in Chennai without getting data and giving it a go. Go mom.

Its the second point that interests me more. Regression coefficients basically give you some average effect, conditional on whatever else you control for. Put less loosely, the regression model in this paper tells you the expected change in spousal education for a given change in type of marriage holding constant family background, income, etc. While any handful of individuals might behave contrary to the prediction, these folks are averaged out the the large number of people who follow rank-and-file.

What's interesting is how my mom completely rejected the average effect based on her experience with a few relatives of ours. I think this is an extremely common phenomenon and speaks towards to power of personal experience in shaping expectations and behavior. No doubt, behavioral economics probably has a lot to say about this kind of thinking (which I am prone to on almost a daily basis!).

The whole episode reminded me of a comment made by Yale School of Management behavioral economist Keith Chen in our departmental seminar. Paraphrasing a bit, his point was that people are much more likely to rely on their next door neighbor's experience in making a decision to buy, say, a car rather than Consumer Reports. This is irrational since the former represents a single draw from a distribution of reviews, whereas the latter gives the expected value of this underlying distribution.

Another U.S. Health Care System Myth?

This time its about uncompensated care. Here is a link to the paper in question, by economists Jon Gruber and David Rodriguez. Here is the abstract:

The magnitude of provider uncompensated care has become an important public policy issue. Yet existing measures of uncompensated care are flawed because they compare uninsured payments to list prices, not to the prices actually paid by the insured. We address this issue using a novel source of data from a vendor that processes financial data for almost 4000 physicians. We measure uncompensated care as the net amount that physicians lose by lower payments from the uninsured than from the insured. Our best estimate is that physicians provide negative uncompensated care to the uninsured, earning more on uninsured patients than on insured patients with comparable treatments. Even our most conservative estimates suggest that uncompensated care amounts to only 0.8% of revenues, or at most $3.2 billion nationally. These results highlight the important distinction between charges and payments, and point to the need for a re-definition of uncompensated care in the health sector going forward.

The U.S. Health Care System: Not So Bad?

I am currently serving as a TA for two courses, a basic undergrad health economics class given through the economics department and a health policy class for MPH students via the School of Public Health. At the beginning of the semester, the professors in each class put forth the following question: "How many of you think that the American health care system gives good value for the dollar?" Surprisingly, about 1/3 of the undergrads answered "yes." Not surprisingly, the public health-ers unanimously answered "no."

I think there are two things to take from this. First, there is a great deal of self-selection on the margin of political leanings in public health. Most MPH students tend to identify with democrats/liberals (or, in one of my more cynical moments, "pink-os"), which probably is what induces them to pursue a service-oriented field like public health in the first place. (I'm not sure if the causality works the other way: does learning about public health shift people's voting preferences to the left?).

Second, and most germane to this post, is that, despite what Michael Moore says, not everyone thinks the U.S. health care system is a complete disaster. Slowly but surely, some recent press and research work suggests that the American system isn't really as bad as it seems when making general comparisons with systems in other OECD countries.

For some insight into this, check out recent New York Times article by Greg Mankiw. It is actually the post that I wanted to write and had already written part of before finding out I was scooped. Given that I was about the say the same thing, I think his commentary is very sensible. Here are the major points (I'm not going to give too much away, so as not to destroy any incentives to read the real thing):

1) Cross-country differences in infant mortality rates and life expectancies are mismeasured and overstated when judging different health systems.

2) The 47 million uninsured statistic that everyone quotes masks a lot of things that actually aren't very worrisome, at all.

3) Rising health care costs may be a sign of progress rather than impending doom. At the very least, putting a value judgment on that 16% of GDP tidbit is misguided.

These points don't just stem from conservative, free-market dogmas. Rather, they should be taken seriously for their attention to measurement issues and economic principles. It isn't the first time that alternate, less pernicious interpretations can be given to stylized facts that initially seem quite alarming. Check out an earlier post for another example of this, which also happens to be drawn from the health care arena.

The obvious bottom line: we need to learn from both sides of the health care debate in order to make reasonable policies.

Developing an Area is Hard

There has been a good deal of talk recently about the UN Millennium Village project. Spearheaded by rock-star economist Jeffrey Sachs, the project is a direct extension of the ideas put forth in his book The End of Poverty. Here is a good description of the basic aims:

The Millennium Project is trying to show how a few simple reforms, seven in all, can substantially improve lives and provide livelihoods. These are: fertiliser and seed to improve food yield; anti-malarial bed nets; improved water sources; diversification from staple into cash crops; a school feeding programme; deworming for all; and the introduction of new technologies, such as energy-saving stoves and mobile phones.

There are around 12 such villages in existence now, with the hope that the program will be expanded to over 1000 villages by 2009. Furthermore, Sachs and co. look to scale-up village-level interventions so as to generate "trickle-up" returns for districts and perhaps even countries. While Sachs himself seems to agree that many of these interventions may not be sustainable (i.e., they will require constant external funding to continue in place), the UN website for the project spends a good deal of time talking about "local ownership." This is basically a fancy way of saying that the average villager Joe and Jane will be able to have a say in the interventions, so as to tailor the program in ways that best resonate with the community. "Local ownership" is also a buzzword used to describe how external funded programs can become sustainable in the long-run: even after the donors leave, individuals in the village are left with the resources, expertise and desire to continue the efforts.

Time will tell whether the project goals are met. But it's always fun to speculate and form expectations about what might actually happen. On the one hand, the recent reviews about the millennium villages have been positive and, at times, quite breathtaking. On the other hand, others agree with this Marginal Revolution post and believe that the project will be difficult to scale up and sustain in over time.

Why exactly might such programs be hard to sustain? Obviously, there are a multitude of reasons. Some really interesting recent work can be used a lens to understand the roadblocks a bit more.

1) One good example is a provocatively titled paper by economists Michael Kremer and Ted Miguel called "The Illusion of Sustainability." This paper is a follow up on their classic experimental study on the economic impacts of deworming in Kenya. The basic idea is that deworming has externalities: treating some people provides benefits for everyone since some links in the transmission chain are now eliminated. In the "Illusion" paper, the authors look at four traditionally touted ways to promote sustainability and see whether these are effective in inducing people to take up deworming drugs and best practices. Learning from peers (some of whom were experimentally assigned to deworming in the original study) actually led to lower take-up, perhaps because, in a public goods world, individuals realize that the private benefit (which is less than the societal benefit because of the externality) of taking the drug is lower than the cost (side effects, etc). They also find that cost-sharing, educational interventions, and community mobilization efforts (i.e., encouraging "local ownership") did not work, either.

Miguel and Kremer go on to finish with a short discourse on why aid agencies might focus on sustainability even when such a goal is impossible. That alone is worth the price of admission here.

2) This next paper shows how well intentioned interventions can have unintended consequences. Its a clever study, and good reading for grad students or econophiles given the very intuitive and powerful theoretical section. I'll let the author explain the results himself, as the abstract is very transparent:

Water supply improvements are a frequent policy response to endemic diarrhea in developing countries. However, these interventions may unintentionally cause community sanitation to worsen. Such a response could occur because improved water supplies mitigate the consequences of poor sanitation for the community. Since sanitary behaviors have large externalities, the negative health impact of this endogenous response may overwhelm the direct benefit of clean water. This paper shows how the expansion of municipal piped water in Metro Cebu, the Philippines has exacerbated public defecation, garbage disposal, and diarrhea. I rely on instrumental variables and household fixed effects to rule out non-causal explanations for these results, and find that a neighborhood’s complete adoption of piped water increases the likelihood of observing excrement or garbage by 15-30 percent. Such a change increases diarrhea incidence by 35-40 percent.

3) Santosh forwarded me an interesting study by Abhijit Banerjee, Esther Duflo, and Rachel Glennerster, about an experimental intervention run amok in India. I wasn't able to find a link for this, but I will post the abstract here. The basic message? Existing governing and administration structures need to be brought into the intervention decision and implementation
process before they become a hindrance. If the stake-holders aren't participating (or are indifferent), you've got an uphill task.

The Indian Health Care system is plagued by high staff absence; low effort by the providers; and limited use by potential beneficiaries, who prefer private alternatives. This paper reports the results of an experiment carried out with a district administration and a nongovernmental organization (NGO). The presence of government nurses in government public health facilities (sub-centers and aid-posts) was recorded by the NGO, and the government took steps to punish the worst delinquents. Initially, the monitoring system was extremely effective. This shows that nurses are responsive to financial incentives. But after a few months, the local health administration appears to have undermined the scheme from the inside, by letting the nurses claim an increasing number of “exempt days.” Eighteen months after its inception, the program had become completely ineffective.

A Small Window...

...into why I love econ.

Check out this excerpt from a recent post on the Freakonomics blog:

Then, of course, there’s the matter of satisfaction derived from the money itself. Just as a beautiful woman could be described as a “depreciating asset,” so could a rent-free apartment with an unlimited shopping budget. A platinum card may thrill for a few months, but, particularly given the required tradeoff of supplying sexual favors to a man who describes himself as “Danny De Vito with a nicer suit,” it’s also likely to offer diminishing returns.

This Marginal Revolution post about the value of a sports agent is pretty good too.

Both are excellent examples of economic intuition applied to everyday events. I think there are two lessons that come from this. The first is to never underestimate the power of a disciplinary lens. Economics is a powerful method, and allows for systematic analysis into a range of phenomena. The second is to be wary of the danger of going all narrow: sometimes there are insights to be gained from other perspectives. This isn't to say that we should all be jacks-of-trades - I'm a big believer in comparative advantage and returns to specialization. Rather, I think its useful to know the contributions and limits of any one approach, and know where other approaches might fill in any existing gaps.

The 'Dar He Blogs Guide to San Francisco

I spent a week in the bay area about two weeks ago. I had a blast. It was the first time I really got to explore San Francisco and vicinity in some depth. Special thanks to Maheer and my folks for taking me to all the cool joints. In the event you might find yourself in the area, this post can serve as a useful starting point to plan your time/journey. Enjoy!

1. When in San Francisco, be sure to visit ritzy malls and take arty photographs.
Here, Maheer's shadow is seen in the uber shiny floor tiles, as if superimposed on the pattern in the rotunda.
















2. When in Rome, do as Romans do. When in Alcatraz...
Re-enact your favorite scene from The Rock.
















3. Visit less well known monuments and make them famous by advertising to your friends on your partially eponymous blog.
This is probably one of two things that are actually worth seeing in Sunnyvale. I call it the "Sunnyvale Pyramid", but in reality it has something to do with the Summer and Winter Solstices (Solsti?). In any case, I think I look good in this picture.




















4. Wine Country is guaranteed to be fun.
That is to say, if it's not initially, the likelihood that you will find it fun by the end of your stay is increasing in the number of free samples you consume (though the function probably reaches some max and is strictly decreasing thereafter - as you can see, I did not sample optimally).





















5. If you must go to the opera, bring friends.
A few of us went to this opera called Appomattox, about the Civil War surrender and its aftermath. It was in English and, while at times moving, really funny and ridiculous. Imagine this exchange in sung in the Opera style:

President Lincoln: "What is the aim of General Lee?"
Ulysses S Grant: "I don't know."

This actually happened. I think I reached my cultured-ness maximum very early on: I spent the first half hour giggling. Luckily, my friends Maheer and Vivian found it equally ridiculous and probably had a good chuckle here and there themselves. This is why its good to bring friends: you don't feel bad for finding serious things funny if your buddies do, too. Simple social acceptance. On the other hand, I tend to laugh when other people do, so I think we fed off each others giggling.

6. On second thought, don't go with friends.

7. Eat at the following restaurants.
Recommended by Maheer, taste tested and confirmed by me.

La Tacqueria
Mitchell's Ice Cream
Zazie's
Chez Maman
Burma Superstar
Dottie's True Blue Cafe (breakfast)
Saigon Sandwiches
Truly Mediterranean
Little Star
Ganim's
Citrus Club
Chaat Paradise

We also went to some yogurt bar (forgot the name) which is very well known for its excellent yogurt and fresh ingredients. I had a basic yogurt with fresh mango and raspberry topping. Possible the greatest food item I've ever had.

Behavioral Economics in the News Today

Here's some educational Sunday morning fun for you:

1. Check out this ESPN article about sports fans trying to work some action at a distance to help out their teams. This reflects how people mistakenly and irrationally believe that they have some kind of influence over external events that don't directly involve them.

2. This morning's Foxtrot, about using framing to obtain more candy on Halloween.

Wildfires, Pollution and Health (And Other Interesting Links)

I was watching an interesting report on CNN this morning about how many Southern California residents have reported various respiratory symptoms, likely due to wildfire induced particulate matter in the air. It's probably obvious to most people that forest fire related smoke will have adverse health consequences. Even so, its worth trying to get a sense of whether this holds up in the data and what the magnitude of the effect really is.

Some interesting research on the 1997 forest fires in Indonesia provides insight into these issues. This paper by Seema Jayachandran suggests that the fire led to a 17% increase in childhood (here under-2) mortality rates. The effect was larger in poor Indonesian districts, again something that most would expect a priori. Frankenberg and co-authors find effects among adults as well. Exposed individuals had more difficulty with activities of daily-living and were more likely to report respiratory symptoms.

A quick, but important digression: Forest fires are a good way to study the effects of pollution on health. First, variation in forest fire intensity is plausibly exogenous. The location and intensity of forest fires are essentially "random" conditional on typical region and individual level controls. Second, for more recent events, there are usually very good atmospheric measurements of particulate matter, which allows the economist/epidemiologist/statistician to directly estimate the effect on salient pollution factors on health.

I think the existing research can be extended on several margins. For example, what are the long term effects of those exposed in utero. That is, how do kids who survive the insult do later in childhood and later in life? What is the biology behind this? Another interesting question stems from Jayachandran's finding that the impacts of pollution decline with increasing regional wealth. It's worth trying to tease apart why this is so: What is it about richer regions that shields their residents from the effects of dirty air? Do the wealthy live in houses with better ventilation? Are they more mobile?

More stuff: how much does an individual's productivity decline as a result of pollution? Finally, conditional on income, can we use information on the choices people make to avoid exposure to pollution say something about an individual's own valuation of his/her health status?

As unfortunate as the So-Cal fires are, perhaps some good can come out of the fact that it can generate some rich research. I'll be interested to see how the current state of the pollution literature will be advanced.

Other Interesting Links:

1) Kenneth Chay and Michael Greenstone have written some of the seminal papers on pollution and infant health. You can find some of them here and here. I like these papers because they are extremely rigorous. That kind of stuff makes for good graduate student reading.

2) Interesting post at the Freakonomics blog about the potentially substantial benefits to malaria eradication on health and economic outcomes.

3) Do grants increase research productivity? Check out this paper if you are interested in finding out the answer.

What's that 'Racquet'?

Exactly 10 years ago, I was starting my senior year in high-school. More than SATs and the usual college application stress, I had one thing on my mind: our tennis team winning the New York State Section II crown after years of looking like the second iteration Cleveland Browns.

I was pretty crazy about tennis then, and my interests in the sport ranged from strategy to equipment. I was especially fanatic about the latter: I spent hours reading the yearly racquet- issue in Tennis magazine. This special issue was about twice as thick as a normal issue and catalogued every new stick released in the last year and some of the more popular sticks from years past. Each description had a picture of the racquet, its specs (swing weight, balance, string pattern, stiffness, etc), and a description of what the magazine staff thought of the stick. I think I was drawn to this because it was kind of science-y. Indeed, several of the descriptions would feature comments from an MIT engineering professor.

I bought two racquets during my high school tennis career: the Head Pro Tour 280 and the Head Radical Tour. The former is perhaps the best racquet I have ever played with: it truly felt like an extension of my right arm. I felt like I could do anything with the ball, short of cooking it and putting it in a sandwich. Kick serves, sharply angled backhands, low volleys, and funky slices were all within my reach. Sadly, this wonderful blue stick was discontinued just two years after being introduced into the market and mine was destroyed within two years of its purchase over a trip to India, where my little cousins used it as a trampoline, thus deadening the string bed/frame nexus. The Head Radical Tour was bought as the closest replacement I could find for the 280.

I've gotten some good mileage out of my Radical, but its been frustrating. In the back of my mind I knew that I had already found the perfect racquet for me and, the Head corporation's marketing decisions notwithstanding, I hadn't done enough to cultivate a continuing relationship with that particular piece of equipment. After all, I could have bought two (or three) racquets instead of one. Or I could have been more vigilant in keeping it out of the hands of unwitting toddlers. Regrets, regrets: I could have tried so much harder!

A few weeks ago, after having played only sporadically in college, medical and grad school, I decided to get serious about tennis again. While playing with one of my mates, my trusty but ultimately unexciting Radical broke, the butt cap coming free from the handle. I took it to the pro shop to see if I could get it fixed but deep down I knew the thing was dead.

Given the inevitable, I was now racquet-less. I did the first thing I could think of: I went to eBay and some of the online tennis wholesalers to see if I could find a still unused Pro Tour 280. No luck. I lamented to the pro shop proprieter. He told me to get over it, dry my eyes, and move on. Racquet technology has really improved and perhaps I'll find a good fit in some of the new stuff?

One thing led to another, and I ended up joining his demo program. This is basically like a tennis racquet library: you borrow two racquets at a time and try them out. Based on what you tell the pro, he'll set you up with sticks that might work for your style of play (swing speed, court positioning, weaknesses, etc). I went home with the Babolat Aero Storm and Head Radical Tour Pro Microgel.

I was skeptical. My first impression was that racquet demo-ing was that this was like speed dating (which I have never tried - this is not the first time in this blog where I've discussed something I know nothing about): you get a few moments to make a decision on whether you want another go with the person or racquet. On the one hand, a few moments sounds like a crock: what if you happen to have an unusually great day when you hit with a racquet thats not quite right? On the other hand, Malcolm Gladwell talks about the power of first impressions in Blink, where even 30 seconds might be plenty of time to distill the situation and figure things out.

In any case, my skepticism probably came out of some need to make excuses for not wanting to try something new: I already found the right racquet years ago, and now its no longer possible to purchase that particular stick. Whats the point of working so hard to find something that I believe won't be as good? Why go through the disappointment? I even ignored the fact that I made my decision to buy the Pro Tour 280 with even less information: my choice was purely based on a quarter page blurb in Tennis that I read over and over.

Well, I'm happy to report that the Babolat Aero Storm has blown me away. Its 98 square inches and 11.7 ounces of ridiculously good control and spin. I can sit back and swing away, and still keep everything in the court. My volleys are crisp and the slices stay low. I absolutely love the stick. I am currently testing out the Technofibre Tfight 325 and some gimmicky Prince racquet that I can't stand. I kind of like the Technofibre, too, but I think the Babolat's the one.

So, over 10 years later, I finally found a racquet that really works (and is popular enough not to be discontinued). I'm really looking forward to the winter season, where I plan on playing team tennis. Who knows: maybe I'll get back to a solid 4.5-5.0 and enter tournaments again. Right now, though, its just nice to know that, after so many years, I found a stick that jives with me.

Elementary, My Dear Watson

Nobel Prize winner James Watson created quite the ruckus this past week thanks to his comments on race and intelligence. His basic thesis is pretty easy to distill:

The scientist, who won the Nobel prize for his part in discovering the structure of DNA, was quoted in an interview in The Sunday Times saying he was “inherently gloomy about the prospect of Africa” because “all our social policies are based on the fact that their intelligence is the same as ours - whereas all the testing says not really.”

Watson recently clarified his statements, probably in an attempt to address the tidal wave of criticism hurled in his direction. His new material, while sticking to his main point, sounds less inflammatory:

-"If I said what I was quoted as saying, then I can only admit that I am bewildered by it."

-"We do not yet adequately understand the way in which the different environments in the world have selected over time the genes which determine our capacity to do different things."

-"This is not a discussion about superiority or inferiority, it is about seeking to understand differences, about why some of us are great musicians and others great engineers."

I'm not going to call Watson a racist or anything like that: it would be scientifically unproductive and irrelevant to do so. Instead, I'd like to address the merits of his hypotheses. Here is what I think:

1) Unless humans evolved independently in more than one location, all of us have descended from the same human line and, therefore, some specific geographic location. Obviously, as human migrated away from each other differential selection pressures helped generate different traits (like skin color, facial morphology, etc). In that sense, its not hard to imagine that different population groups might vary across a set of traits. However, it is harder to imagine that something like intelligence would be selected on differently across space: I would expect the returns to being smart to be relatively similar across different populations, especially in the days around and prior to the agricultural revolution.

You might think that this argument is as tenuous as Watson's. You are right. However, my point is to apply the "huh" test to his reasoning. When one does that, the whole thing seems somewhat shaky.

2) Here is a stronger argument: racial gaps in ability might be explained primarily by differences in childhood investments and early life environments. Indeed, there is a great deal of scientific evidence that indicates that this may be the case. I'll pick one of my favorites as an example. In an earlier post, I talked about a paper by Douglas Almond and Ken Chay, looking at the impact of Civil Rights movement induced hospital integration on the intergenerational transfer of health status among black individuals. The authors found that the children of women born just after hospital integration report higher birthweights, better apgar scores, and lower infant mortality. Here's the kicker: they also find that the black-white test score gap among this advantaged cohort is much thinner.

It's no stretch to posit that the effects of environment are large, powerful and very real. Given how salient these factors are, it makes a great deal of sense to try and understand the process of cognitive development and its relevant inputs before resorting to blanket genetic statements. Indeed, other papers suggest that the entirity of the ability gap can be explained by early-life socioeconomic factors. Check out this post by Steven Levitt for some information on his interesting work.

3) Uncovering the determinants of ability should command a great deal of research attention. All credible hypotheses should be taken seriously and addressed with the best scientific methods. On that note, I do not believe that Watson's hypotheses are very compelling, and perhaps this is not where we should be focusing our attention when it comes to future research.

What Does Small Area Variation Actually Say About Health Care in the US?

In the 1970s, John Wennberg and Alan Gittelsohn noted something very peculiar about health care delivery in the United States: they found a great deal of variation within a sample New England towns in the rates of various surgical procedures. For example, the rates of hysterectomies and tonsillectomies in Vermont varied wildly across hospital service areas, with most intense areas sporting 3 and 10 times the number of procedures per capita as the least intense areas, respectively!

Since Wennberg and Gittelsohn's original paper, a great deal of work has been done on this phenomenon, coined "small area variation." This research has shown that (a) county/area level demographics, per capita income and other socioeconomic variables do not always explain away the cross-area variations and (b) variation in service delivery persists even today. (For a sense of (b), check out the Dartmouth Atlas of Health Care, a great resource and a fun way to spend a half hour or so.)

As you can probably imagine, the small-area variation literature created a huge health policy firestorm, whose echoes continue to reverberate in the present day. Basically, policymakers concluded the following things from this literature:

1) Wide variation in service delivery reflects uncertainty among physicians about what best practices are. This suggests that either physicians don't know as much as originally assumed, that information about best practices does not diffuse quickly among doctors or both.

2) In addition to (1), it may be that physicians in certain areas are more likely to get their patients to agree to certain procedures. The technical term for this is supplied-induced demand.

3) Areas that have higher rates of various procedures and, therefore, ostensibly spend more do not have better health outcomes. This suggests that the high intensity areas are wasteful. The empirical finding of no association between treatment rates/spending and outcomes lends even more support to (1) and (2).

Not surprisingly, small-area variation is widely seen as both a cause and symptom of very messy U.S. health care system, its existence viewed as indicative of pernicious processes that need to be curbed.

However, are there other explanations behind the empirical findings in the small area variations literature? Let's start with the question of why small area variation exists in the first place. Are there other theories besides supplied-induced demand and poor diffusion of information in the context of area-specific norms that can explain these empirical observations?

In a recent paper in the Journal of Political Economy, economists Amitabh Chandra and Douglas Staiger suggest the answer is "yes." In particular, the propose a theory where the key feature is that the benefit of a single procedure over another is contingent on the number of other patients receiving that procedure in the same area. How could this happen? First, since doctors learn from each other, a physician becomes more productive with a given procedure if he/she has more peers in the area doing the same thing. Second, support services in area hospitals that make a given procedure more productive might arise due to various historic factors. Third, doctors may self-select and practice in areas with different treatment intensities. Regardless of the relative importance of these factors, the key point is that these "productivity spillovers" are plausibly less icky than more "evil" stories like uninformed and tricky docs.

Chandra and Staiger test their theory in the data, looking at treatment patterns for heart attacks (intensive-surgical versus non-intensive-pharmacological) among a sample of Medicare patients, and find a very good fit. From a grad student perspective, the beauty of this paper is how the authors use their theory not only to explain the existing facts in the small-area variation literature, but also to generate further predictions that can be tested in the data. This is the key: what differentiates one theory from the other are the predictions it makes and, as a result, the only way to tease apart the underlying driving forces are to focus on predictions unique to each theory.

What about the consequences of small-area variation? Past research exploited this variation to conclude that increased treatment intensity and increased expenditure have no effect on health outcomes. Some recent research, however, suggests that this may be wrong. In a recent working paper (thanks to Brian Elbel for the reference), Joseph Doyle notes that past estimates of expenditure effects might be plagued by omitted variable bias: more money might be spent in areas where health outcomes are worse, thus biasing the relationship between the two towards zero. Here is how he gets around this:

The main innovation in this paper compares outcomes of patients who are exposed to different health care systems that were not designed for them: patients who are far from home when a health emergency strikes. The universe of emergencies in Florida from 1996-2003 is considered, and visitors who become ill in high-spending areas have significantly lower mortality rates compared to similar visitors in lower-spending areas. The results are robust across different types of patients and within groups of destinations that appear to be close demand substitutes.

Of course, the main threat to inference in this strategy is that richer tourists or visitors might self select to go into richer counties. Doyle has a variety of robustness checks to address this hypothesis. Check out the paper and see if you buy it.

I think this finding is interesting. Many people think that the U.S. is wasteful with its health care dollars and this might be true in some contexts. However, as the trajectory of the small-area variations literature illustrates, it is worth having a fresh look at our priors before making sweeping policy statements. Things may not be as bad as they seem.

I paid $0.02

A few days back I talked about the new Radiohead album and the band's innovative "pay-what-you-want" pricing scheme. I also went ahead and asked people what they would shell out for the new tracks. While my sample was very small (thank you Maheer and James), I believe it is fairly representative: most people on various other blogs also commented that they would pay well above the $0.02 minimum for In Rainbows.

After a great deal of thought, I went ahead and officially purchased the new album today. I decided to pay the minimum price, which actually worked out to about $1.00 thanks to credit-card related transaction costs (45 pence). Why did I pay so little? My reasons were the following:

1) I am a poor student
2) I will probably end up spending $100+ for concert tickets and another $15+ for the official disc version of In Rainbows (which will feature an additional 8 tracks, including the sensational "Bangers 'N Mash")
3) If they are allowing me to spend next to nothing, why not? I can collect on all that extra consumer surplus.

What's even more interesting was how guilty I felt right after the transaction was processed. Here were my post-purchase thoughts in the order that they happened:

1) Man, I am a really bad Radiohead fan.
2) Other people will think I am a bad Radiohead fan when they find out how much I paid for this album.
3) I feel like I'm stealing: I would have paid so much more in the store. Another way of saying this: I paid far, far less than my personal valuation of the good.

I'm willing to bet that a lot of people would go through this reaction, conditional on what they paid for the album. After all, I think it is for the above reasons that people were willing to pay more than the required minimum in the first place, why we overtip waiters and waitresses, why we donate $15 instead of $5 for entry into a large public museum, etc. In this case, from the standpoint of a standard economic model, there is no rational reason to pay more, so the psychology behind this behavior must be quite rich. This is a long way of saying that aspects like signalling to other consumers (2) and guilt (3) play a large role in these decisions.

Any thoughts?

The Rap on Crime

You may have heard that Congress held hearings last week focusing on profane and violent lyrics in popular rap music. The Daily Show had a great segment on straight-laced Congressmen bashfully quoting and walking through some pretty hardcore lyrics. Despite the hilarity surrounding the Representatives struggling through the profanity, the implicit message behind their words is more serious and crystal clear: violent and profane imagery in rap spurs on violence and other illegal behaviors in society at large.

While some artists (most notably Dancing with the Stars ringer Master P) agree with this, several people at the hearing (read: industry executives) pointed out that Congress may be getting the direction of causality wrong. So the question is: Does rap induce violence or simply reflect it?

I wonder if we can chip away at this question with some data. It shouldn't be hard to get yearly statistics on different kinds of crime committed, sales of rap albums, and a bunch of socioeconomic indicators (per capita income, average age, population breakdown by race, etc). With multiple years of data, one could control for state-specific effects that don't change over time.

However, this alone likely won't be enough: we still can't say whether its changes in rap album sales or changes in violence (or both) that drive the story. What we really need is a variable that predicts rap sales but does not influence violent crimes through another independent channel. I wonder if rap, like grunge, started in one part of the country and slowly diffused out. If so, it might be possible to interact geographic distance from "epicenter" and share of young and minority population to form an instrumental variable (though the epicenter argument probably applies differentially to the spread of old school rap, and thus the local average treatment effect we would derive would not be policy relevant). One might also want to look at lagged rap sales as well.

Any thoughts?

Review: Better than a Killer, by Black Market Radio

After an entire summer of listening to Audioslave, Rage Against the Machine, and Soundgarden over and over, I felt ready to move on to some newer music. Having been in the mood for heavier music for the past few months, I wanted to continue on that line and find something grungy in the Soundgarden or Nirvana style, with lots of screaming, loud guitars and messy riffs.

Black Market Radio is a Seattle based group that attempts to deliver these goods. The group's frontman is Peter Cornell, who happens to be the brother of - you guessed it - Chris Cornell, of Soundgarden and Audioslave fame. Keith Mannino (bass, backing vocals and the occasional guitar) and Johnny D (drums) round out the trio.

Better than a Killer is the group's most recent album and features a decent dose of 90s style grunge for those who are nostalgic or for those who didn't listen to this stuff during middle and high school and only got into it less than a year ago (the latter is me). The title track is pretty good, but the middle of the album is where the meat is. "Link," "Big Stones," "Fight of Your Life" and "Suicide Parlour" are quite good, with introspective and oft depressing vocals combined with some heavy sounds. The rest of the 12-track album is passable. You can listen to some BMR here (definitely have a look and let me know what you think).

The main strength of the album is Peter Cornell. I guess great voices run in that family. Many other reviews note the strong resemblance in the brothers' voices. When Peter goes off in "Link":

So I raise my glass to the fallen angels...
I tip my hat to the fallen angels...

you feel like you're listening to Chris from his Badmotorfinger days.

But I think Peter has distinct and memorable moments that are very much unique to him and him alone. He cultivates his own style and works wonders across a wide variety of songs. For example, I could never imagine Chris belting out "Ghost" the way Peter does.

I'm not sure what the future will look like for Black Market Radio. I haven't seen too many reviews for this album (which released early-mid August) and the buzz hasn't picked up (yet). I definitely hope that this changes and that Peter Cornell gets noticed more than he has and ascends above the label "Chris' Brother."

In an interview early last year, Cornell claimed, "It's like [BMR is] involved in a renaissance of that [older, high quality] sound...It needs a resurgence. There's a lot of fans online that have felt neglected over the last three or four years." The band's motto then was "together we will save rock 'n roll."

Have they succeeded in that quest? I definitely think BMR's sound is, for the most part, a welcome distraction from the tired out stuff that bands like Linkin' Park put out. However, there are times when the band descends into the worn world of new school rock. Perhaps it can't be helped (unless you are the White Stripes).

I rate the album at 6.75/10.

New Radiohead Album October 10th!

I just saw this NYT article about the new Radiohead album, "In Rainbow." Apparently, the album will be available on October 10th, and you can download it from the band's website. The price is - here is the kicker - whatever you want it to be!

This is mind-blowing on so many levels. First off, Radiohead has to be one of the most innovative bands ever, and their new album promises to be incredible. I know this because I've downloaded most of the new set they were playing live on tour last year and, even in the raw form, its amazing stuff.

Second, their pricing and distribution scheme is absolutely revolutionary. Here is an excerpt from the Times piece:

There is no maximum price, nor any other guidance, setting up what is may be the biggest experiment in digital-era music-industry pricing to date. What are people willing to pay for music? How many will pay full price? How will the average price compare to what a typical record company would likely have charged? Will people pirate it anyway?

I would love to talk more in depth about the economics of this here, but I just found out I was beaten to it: Tyler Cowen at the Marginal Revolution gives his thoughts on this new scheme here. No worries: Radiohead and econ in the same morning? Rad.

Just a few weeks ago, I saw a report that Radiohead was finished with the new album and was looking to release it mid-2008 upon finding a new label. But I knew that was bogus because, for quite some time, frontman Thom Yorke has been talking about how he wanted to use the internet as a means of music dissemination. And I was right. Three cheers to Radiohead:

Cheer 1) Your music rocks
Cheer 2) Way to embrace the digital age
Cheer 3) You just made the rest of my 2007.

So I have some questions for you readers:

1) Are you a Radiohead fan?
2) How much would you actually dish out for the new album?

Your comments on this post are so important that I will randomly choose one of them to win a hitherto unnamed prize.

Finally, I whole-heartedly thank Wisconsin-ite Nick Rhodes for putting me on to Radiohead. Nick has great taste in music, and somehow everything he does has instant street-cred. He's good people.

The Balance Sheet on Managed Care? (And Other Interesting Links)

As US health expenditures skyrocketed in the late 70s and 80s, managed care started to proliferate as a potential cost saving measure. The basic idea was (and is) simple: combine providers and insurers into a single organizations and incentivize providers to use the least amount of resources as necessary for a given patient. Along with that, throw in an emphasis on preventative care so as to cut costs further down the line.

This system was revolutionary compared to what was going on before, where doctors were mostly paid by third party insurers on a fee-for-service basis. Many argue that this system encourages doctors and patients to use more resources than necessary. Today, payments to physicians take on a variety of different flavors, and fee-for-service and managed care incentives both coexist.

However, there may be a dark side to managed care , as well. The 'managed care backlash' was basically driven by uneasiness over whether necessary care would be disincentivized by typical managed care instruments such as utilization review, capitation payments, pay for performance, etc. Thus, managed care could be good or bad for patients, and the whole thing comes down to an empirical question.

So where does the axe ultimately fall? Anna Aizer, Janet Currie and Enrico Moretti's recent paper in the Review of Economics and Statistics provides some interesting insight into this issue:

Poor and uneducated patients may not know what health care is desirable and, if fully insured, have little incentive to minimize the costs of their care. Partly in response to these concerns, most states have moved a substantial portion of their Medicaid caseloads out of traditional competitive fee-for-service (FFS) care, and into mandatory managed care (MMC) plans that severely restrict the choice of provider.

We use a unique longitudinal data base of California births in order to examine the impact of this policy on pregnant women and infants. California phased in MMC creating variation in the timing of MMC. We identify the effects of MMC using changes in the regime faced by individual mothers between births. Some counties adopted single-carrier plans, while others adopted regimes with at least two carriers. Hence, we also ask whether competition between at least two carriers improved MMC outcomes. We find that MMC reduced the quality of prenatal care and increased low birth weight, prematurity, and neonatal death. Our results suggest that the competitive FFS system provided better care than the new MMC system, and that requiring the participation of at least two plans did not improve matters.

What I like about the paper is the use of quirks in public policy (like phase-ins), great data, and sound econometrics in coming up with an answer to a policy relevant question. I think the most convincing evidence in this paper comes from comparing siblings, whose mother was exposed to different "incentive regimes." This allows the authors to control for fixed factors that induce selection bias at the level of a given mother. Good stuff.

Other Links:

1) John Stossel doesn't think US health care system is as bad as everyone says it is. Check out this link as well as the articles listed in the sidebar on the right. I'll have more to say about this in a future post.

2) On that note, check out this recent working paper looking at differences in the US and Canadian health care systems. Here is a nice sentence from that piece:

We also find that Canada has no more abolished the tendency for health status to improve with income than have other countries. Indeed, the health-income gradient is slightly steeper in Canada than it is in the U.S.

3) I miss Audioslave. Check out their live cover of "Seven Nation Army." Even Omar Siddiqi enjoyed this.