Ken Chay, Jonathan Gurvan and Bhaskar Mazumdar have an interesting working paper looking at the impacts of improved access to health care during infancy and cognitive test scores. The paper follows black cohorts born before and after desegregation of hospitals in the 1960s and tracks their performance on different cognitive test scores. The main result of the paper is that the convergence in black-white test scores can be explained in large part by improve access to health care. As expected, this convergence is greatest in areas which stood to gain most from the Civil Rights Act. This paper is related to an earlier study, which looked at the birth weights of babies born to black mothers before and after desegregation.
The main message of this piece is that early childhood experiences matter and have long-run benefits. While the previous research in this area has tended to look at the impacts of shocks (famines, recessions, droughts, etc), this paper looks at the impacts of an actual policy and is therefore one step closer to policy relevance. I have a forthcoming working paper that takes a similar approach, looking at the long-run impacts of public health investments in Mexico. Like the study discussed here, I, too, find substantial benefits of such interventions. The next step is to quantify these benefits and assess how this affects resource allocation decisions, which is of great interest and utility to policy makers.
Another thing I like about this paper is its attention to the problem of inference. The study is 72 pages long for a reason: establishing causality is difficult, especially with so many things going on during the time the affected cohorts were born. The authors engage in an impressive number of robustness checks and econometric fixes to rule out competing hypothesis. The authors also present many of their results graphically, which helps put everything on the table up front.
I'm almost tempted to print out their paper and use it as a program evaluation reference...
Saturday, June 27, 2009
Sunday, June 21, 2009
Back to the Clinic
I will be starting my third year clinical rotations tomorrow. I'm definitely excited for this: I've been away from medical school for a long time and I look forward to getting back into things and, this time, actually interacting with patients and providers.
Starting third year has a few implications for my blog. First, on difficult rotations I would expect my frequency of posting and length per post to decline. I will try my best not to let this happen, using the blog as my econ outlet especially during months where any substantial research is not realistic to undertake. Second, I will probably include more observations about American health care, especially as it relates to my hospital experiences, than I have in the past. This is a change I welcome: part of what will make my third year more interesting than it would have been pre-PhD is that I now see things with a different set of eyes. I also would like to learn more about American health care, and blogging more about these issues is one step towards that end.
In any case, I look forward to updating this space in the coming months and offering new perspectives and comments. I also look forward to your continued readerships and comments.
Starting third year has a few implications for my blog. First, on difficult rotations I would expect my frequency of posting and length per post to decline. I will try my best not to let this happen, using the blog as my econ outlet especially during months where any substantial research is not realistic to undertake. Second, I will probably include more observations about American health care, especially as it relates to my hospital experiences, than I have in the past. This is a change I welcome: part of what will make my third year more interesting than it would have been pre-PhD is that I now see things with a different set of eyes. I also would like to learn more about American health care, and blogging more about these issues is one step towards that end.
In any case, I look forward to updating this space in the coming months and offering new perspectives and comments. I also look forward to your continued readerships and comments.
Saturday, June 20, 2009
Height, Life Satisfaction and Taxes
Angus Deaton and Rakesh Arora, in a recent NBER working paper, show that:
According to the Gallup-Healthways Well-Being Index daily poll of the US population, taller people live better lives, at least on average. They evaluate their lives more favorably, and they are more likely to report a range of positive emotions such as enjoyment and happiness. They are also less likely to report a range of negative experiences, like sadness, and physical pain, though they are more likely to experience stress and anger, and if they are women, to worry. These findings cannot be attributed to different demographic or ethnic characteristics of taller people, but are almost entirely explained by the positive association between height and both income and education, both of which are positively linked to better lives.
Given the correlation between height and life satisfaction, perhaps stature could be the basis for an optimally designed tax? Mankiw and Weinzeirl explore this idea in another working paper:
Should the income tax include a credit for short taxpayers and a surcharge for tall ones? The standard Utilitarian framework for tax analysis answers this question in the affirmative. Moreover, a plausible parameterization using data on height and wages implies a substantial height tax: a tall person earning $50,000 should pay $4,500 more in tax than a short person. One interpretation is that personal attributes correlated with wages should be considered more widely for determining taxes. Alternatively, if policies such as a height tax are rejected, then the standard Utilitarian framework must fail to capture intuitive notions of distributive justice.
According to the Gallup-Healthways Well-Being Index daily poll of the US population, taller people live better lives, at least on average. They evaluate their lives more favorably, and they are more likely to report a range of positive emotions such as enjoyment and happiness. They are also less likely to report a range of negative experiences, like sadness, and physical pain, though they are more likely to experience stress and anger, and if they are women, to worry. These findings cannot be attributed to different demographic or ethnic characteristics of taller people, but are almost entirely explained by the positive association between height and both income and education, both of which are positively linked to better lives.
Given the correlation between height and life satisfaction, perhaps stature could be the basis for an optimally designed tax? Mankiw and Weinzeirl explore this idea in another working paper:
Should the income tax include a credit for short taxpayers and a surcharge for tall ones? The standard Utilitarian framework for tax analysis answers this question in the affirmative. Moreover, a plausible parameterization using data on height and wages implies a substantial height tax: a tall person earning $50,000 should pay $4,500 more in tax than a short person. One interpretation is that personal attributes correlated with wages should be considered more widely for determining taxes. Alternatively, if policies such as a height tax are rejected, then the standard Utilitarian framework must fail to capture intuitive notions of distributive justice.
Friday, June 12, 2009
Public Goods and Dentists
A really interesting paper by Katherine Ho and Matthew Neidell looks at how public goods (goods that people cannot be excluded from, and goods for which use by one person does not diminish use for another) impact businesses. Specifically, they look at fluoridation and the dentistry business. In their own words:
In this paper we consider how the dental industry responded to the addition of fluoride to public drinking water. We take advantage of the staggered introduction of fluoridation throughout the country to analyze the changes in numbers of within-county dentists relative to physicians in the years surrounding the change in fluoridation status. We find a significant decrease in the number of dental establishments and an even larger reduction in the number of employees per firm following fluoridation. We also find that fluoridation in neighboring markets was associated with an increase in own-market dental supply, suggesting that dentists responded to the demand shock by moving from fluoridated areas to close-by markets. Further analysis suggests that some dentists may have retrained as specialists rather than moving geographically. Our estimates imply that the 8 percentage point change in exposure to water fluoridation from 1974 to 1992 may have led to the loss of as many as 0.6 percent of dental establishments and 2.1 percent of dental employees, suggesting a substantial net impact of this public good on the dental profession since its inception.
Pretty good stuff. Neidell has used this identification strategy before, but to look at the effects of good teeth on wages.
In this paper we consider how the dental industry responded to the addition of fluoride to public drinking water. We take advantage of the staggered introduction of fluoridation throughout the country to analyze the changes in numbers of within-county dentists relative to physicians in the years surrounding the change in fluoridation status. We find a significant decrease in the number of dental establishments and an even larger reduction in the number of employees per firm following fluoridation. We also find that fluoridation in neighboring markets was associated with an increase in own-market dental supply, suggesting that dentists responded to the demand shock by moving from fluoridated areas to close-by markets. Further analysis suggests that some dentists may have retrained as specialists rather than moving geographically. Our estimates imply that the 8 percentage point change in exposure to water fluoridation from 1974 to 1992 may have led to the loss of as many as 0.6 percent of dental establishments and 2.1 percent of dental employees, suggesting a substantial net impact of this public good on the dental profession since its inception.
Pretty good stuff. Neidell has used this identification strategy before, but to look at the effects of good teeth on wages.
Friday, June 5, 2009
Politicians and Poverty Reduction
A long line of work in political science centers around the topic of clientelism, also known as vote buying. The idea is that politicians (the patrons) provide goods, services or benefits to the public or to those not in positions of power in exchange for votes. (Such favors, for example, could involve the allocation of a large development project to a swing-locality or district). There are lots of reasons to be displeased with "vote-buying" but a big one concerns the marginal returns to public expenditure: funds that are allocated for political reasons may not be allocated productively from the standpoint of some other societal goal. For example, if we are interested in poverty reduction, public funds should be allocated to those who are actually poor (yes, I am oversimplifying here!). Obviously, there is no guarantee that funds allocated by a political formula will follow this more technocratic logic.
So are we destined to an equilibrium where the incentives of politicians and the public are not well-aligned? Not so, according to two recent studies which examine the political impacts of conditional cash transfer programs (CCTs), which are schemes that provide cash to poor families who meet certain objectives (i.e., attending monthly check-ups, sending their children to school, etc; see here for a beautifully detailed account of CCTs the world over) and have been shown to have had numerous positive benefits on health, schooling and general circumstances faced by the poor. The first, by Yale political scientist Ana de la O, looks at the impact of the Mexican CCT, Progresa. Progresa was initially rolled out to a randomly selected subset of localities before more universal rollout a year and a half later. De la O uses this variation to show that people randomly exposed to Progresa longer are around 5 percentage points more likely to vote for the incumbent.
In the second study, Marco Manacorda, Ted Miguel and Andrea Vigorito use a regression discontinuity approach to identify the political impacts of Uruguayan CCT PANES. Comparing individuals just on either side of a pre-designated eligibility score (based on a composite of household and individual socioeconomic characteristics), they find that cash transfers lead to a whopping 21-28 percentage point increase in the probability of voting for the incumbent!
What I like about these papers, besides the use of program evaluation methods to identify causal impacts on voting behavior, is that it suggests that there is a better equilibrium out there: politicians can get re-elected on the basis of policies that have demonstrated large and positive effects on human development rather than through doling out public funds in potentially unproductive ways. My hope is that this catches on in other parts of the world...
So are we destined to an equilibrium where the incentives of politicians and the public are not well-aligned? Not so, according to two recent studies which examine the political impacts of conditional cash transfer programs (CCTs), which are schemes that provide cash to poor families who meet certain objectives (i.e., attending monthly check-ups, sending their children to school, etc; see here for a beautifully detailed account of CCTs the world over) and have been shown to have had numerous positive benefits on health, schooling and general circumstances faced by the poor. The first, by Yale political scientist Ana de la O, looks at the impact of the Mexican CCT, Progresa. Progresa was initially rolled out to a randomly selected subset of localities before more universal rollout a year and a half later. De la O uses this variation to show that people randomly exposed to Progresa longer are around 5 percentage points more likely to vote for the incumbent.
In the second study, Marco Manacorda, Ted Miguel and Andrea Vigorito use a regression discontinuity approach to identify the political impacts of Uruguayan CCT PANES. Comparing individuals just on either side of a pre-designated eligibility score (based on a composite of household and individual socioeconomic characteristics), they find that cash transfers lead to a whopping 21-28 percentage point increase in the probability of voting for the incumbent!
What I like about these papers, besides the use of program evaluation methods to identify causal impacts on voting behavior, is that it suggests that there is a better equilibrium out there: politicians can get re-elected on the basis of policies that have demonstrated large and positive effects on human development rather than through doling out public funds in potentially unproductive ways. My hope is that this catches on in other parts of the world...
Thursday, June 4, 2009
Some Graduate School Advice
I just graduated with my PhD a few weeks ago and have been spending some time thinking over my grad school experience. In the coming weeks, I'm sure I have a lot to say about choosing a grad school, a research field, an advisor, etc, but I thought I'd start by talking about the most important things I learned during the journey. Here goes:
(1) Follow all your leads and persevere: The most important piece of advice I've got. Most projects will not go smoothly, either because of lack of data, some weird programming bug, or some other unforeseen difficulty. If you think it's a good project, with your intuition screaming "yes" and you sense that a breakthrough is possible, KEEP GOING. Sometimes you need to hit your head against the wall, over and over, till it breaks down. I was in this position about seven months ago, needing a third paper for my dissertation and not sure if I was going to get it to work in time to graduate by May. I found some interesting preliminary results on the long-run effects of clean water and I decided to go forward, working really hard to get data and program what turned about to be conceptually easy, but difficult in practice. It paid off, and I am hoping to expand this paper over the next year in several ways.
As far as the "following all your leads" part, if you think of an interesting question, find some data (it's usually very cheap!) and spend an hour or two seeing if you can't get some preliminary evidence or "proof of concept." If you do, follow it up: the results may surprise you and might have an interesting project on your hands.
(2) But know when to stop: This applies to two situations. The first is with a project that just won't work out anytime soon. And the second is with a mostly complete project. In both situations, the marginal hour, or tweak here and there, will likely not lead anywhere. In the first case, stop, but always keep it in your mind: you're breakthrough could happen a few years later. In the latter case, send the thing out already!
Of course, while you're in the thick of it it's hard to distinguish between when you should take route (1) or (2) [I've been late to pull the trigger on several occasions!]. I think that's part of what graduate school gives you, an intuition of when things will work and when they won't. Until you get there, the best way to distinguish between (1) and (2) is to outsource the experience and intuition based calls to people who have a comparative advantage in these things: your advisors.
(3) Sell, sell, sell!: This is something I really picked up in the last six months of grad school. How well your paper does or how well your talk is received is really based on (a) whether your intended audience gets what you are saying and (b) how well you couch your work in the larger scheme of things. Basically, people need to understand what you are doing and realize that it is important. The only way to get this is with a nice sales job.
For people in fields that are necessarily interdisciplinary (health economics or health service researchers both fit that bill), you need to be able to communicate to people who look at problems with a different disciplinary lens. I noticed that my talks went a lot better when I cut out the economics jargon and explained things in a more universal language. My writing got better from this, as well.
In motivating talks and papers, it is always important to bring in the larger literature first, show where your study is situated, and, at multiple junctures, point out exactly why your study is important and all the new stuff it adds to our knowledge. Humility is good, I've learned, but too much gets you left behind. (On the same plane, too much boasting is bad, too. Never oversell your paper!)
(4) Get really good at fundamentals: My personal view is that it is a lot easier to learn about different topics than it is to pick up different skills. As such, I think the best investment during your graduate years, especially when you are taking classes, is to invest in skills. In any statistics based field, being a quant jock makes you the cool kid at school: everyone will want to work with you.
This doesn't mean that one shouldn't read up on interesting topics. Far from it (see below)! Just make sure you get the requisite tools.
(5) Always work the margins: Grad school is full of ups and downs. On the research side, you'll go from being uber productive to not so productive and back again. I think its really important to have a strategy of riding out low marginal productivity months. This might be the time that you (a) read a lot (b) write a lot (c) take a vacation. Whatever you do, make sure you do it with relish. At some point you will become productive again and have a storm of ideas. When you do, embrace it and go to town.
Some other nuggets of note:
(6) Keep a notebook or pda with a list and short description of all your ideas: Some of them won't pan out initially, but you might be able to revisit them in the future.
(7) Read the popular press: Two of my working papers have come from taking data to statements and problems outlined in newspaper/magazine articles.
(8) Read the literature, but don't binge on it: Some good advice that I got early in grad school was to know the literature, but don't read so much that it destroys your creativity. If you think of an interesting idea, play with it in your mind and ask yourself how you'd address the research question. Once you do, Google Scholar it and see if its been done. If it has, pat yourself on the back for coming up with an interesting question and do it again if the authors adopted your methodology. If not, go to town.
(1) Follow all your leads and persevere: The most important piece of advice I've got. Most projects will not go smoothly, either because of lack of data, some weird programming bug, or some other unforeseen difficulty. If you think it's a good project, with your intuition screaming "yes" and you sense that a breakthrough is possible, KEEP GOING. Sometimes you need to hit your head against the wall, over and over, till it breaks down. I was in this position about seven months ago, needing a third paper for my dissertation and not sure if I was going to get it to work in time to graduate by May. I found some interesting preliminary results on the long-run effects of clean water and I decided to go forward, working really hard to get data and program what turned about to be conceptually easy, but difficult in practice. It paid off, and I am hoping to expand this paper over the next year in several ways.
As far as the "following all your leads" part, if you think of an interesting question, find some data (it's usually very cheap!) and spend an hour or two seeing if you can't get some preliminary evidence or "proof of concept." If you do, follow it up: the results may surprise you and might have an interesting project on your hands.
(2) But know when to stop: This applies to two situations. The first is with a project that just won't work out anytime soon. And the second is with a mostly complete project. In both situations, the marginal hour, or tweak here and there, will likely not lead anywhere. In the first case, stop, but always keep it in your mind: you're breakthrough could happen a few years later. In the latter case, send the thing out already!
Of course, while you're in the thick of it it's hard to distinguish between when you should take route (1) or (2) [I've been late to pull the trigger on several occasions!]. I think that's part of what graduate school gives you, an intuition of when things will work and when they won't. Until you get there, the best way to distinguish between (1) and (2) is to outsource the experience and intuition based calls to people who have a comparative advantage in these things: your advisors.
(3) Sell, sell, sell!: This is something I really picked up in the last six months of grad school. How well your paper does or how well your talk is received is really based on (a) whether your intended audience gets what you are saying and (b) how well you couch your work in the larger scheme of things. Basically, people need to understand what you are doing and realize that it is important. The only way to get this is with a nice sales job.
For people in fields that are necessarily interdisciplinary (health economics or health service researchers both fit that bill), you need to be able to communicate to people who look at problems with a different disciplinary lens. I noticed that my talks went a lot better when I cut out the economics jargon and explained things in a more universal language. My writing got better from this, as well.
In motivating talks and papers, it is always important to bring in the larger literature first, show where your study is situated, and, at multiple junctures, point out exactly why your study is important and all the new stuff it adds to our knowledge. Humility is good, I've learned, but too much gets you left behind. (On the same plane, too much boasting is bad, too. Never oversell your paper!)
(4) Get really good at fundamentals: My personal view is that it is a lot easier to learn about different topics than it is to pick up different skills. As such, I think the best investment during your graduate years, especially when you are taking classes, is to invest in skills. In any statistics based field, being a quant jock makes you the cool kid at school: everyone will want to work with you.
This doesn't mean that one shouldn't read up on interesting topics. Far from it (see below)! Just make sure you get the requisite tools.
(5) Always work the margins: Grad school is full of ups and downs. On the research side, you'll go from being uber productive to not so productive and back again. I think its really important to have a strategy of riding out low marginal productivity months. This might be the time that you (a) read a lot (b) write a lot (c) take a vacation. Whatever you do, make sure you do it with relish. At some point you will become productive again and have a storm of ideas. When you do, embrace it and go to town.
Some other nuggets of note:
(6) Keep a notebook or pda with a list and short description of all your ideas: Some of them won't pan out initially, but you might be able to revisit them in the future.
(7) Read the popular press: Two of my working papers have come from taking data to statements and problems outlined in newspaper/magazine articles.
(8) Read the literature, but don't binge on it: Some good advice that I got early in grad school was to know the literature, but don't read so much that it destroys your creativity. If you think of an interesting idea, play with it in your mind and ask yourself how you'd address the research question. Once you do, Google Scholar it and see if its been done. If it has, pat yourself on the back for coming up with an interesting question and do it again if the authors adopted your methodology. If not, go to town.
Wednesday, June 3, 2009
Easterly/Sachs Debate and Other Links
1. Bill Easterly and Jeffrey Sachs have a lively back-and-forth going on the Huffington Post about how best to tackle global poverty (see here and click the links for previous posts). The debate is informative and also fun from an entertainment standpoint.
2. Nice post from Steve Levitt about how free-markets and poverty reduction strategies can co-exist.
3. If you're bored or devoid of fun these days, here you go.
2. Nice post from Steve Levitt about how free-markets and poverty reduction strategies can co-exist.
3. If you're bored or devoid of fun these days, here you go.
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