My friend, former tennis partner and former Yale MPHer Shaan Chatturvedi has just started blogging about his experiences in Guyana, where he is currently a working for the CDC Global AIDS Program. His most recent post, on the swine flu outbreak, is fantastic and promises of good things to come from his blog. Do check it out!
For more on the swine flu, check out this interesting article by Dr. Carlos del Rio, the chair of the Global Health Department of the Emory School of Public Health. There is a lot of interesting stuff in there about different control measures and the reasons why swine flu mortality might be higher in Mexico than in the US.
Wednesday, April 29, 2009
Tuesday, April 21, 2009
Long-Run and Intergenerational Effects of Early Childhood Environments
Great NBER working paper this week on the long-run and next generation returns to early life conditions. Specifically, Eric Gould and co-authors look at consequences driven by the airlift of Yemenite immigrants into Israel. In their own words:
This paper estimates the effect of the childhood environment on a large array of social and economic outcomes lasting almost 60 years, for both the affected cohorts and for their children. To do this, we exploit a natural experiment provided by the 1949 Magic Carpet operation, where over 50,000 Yemenite immigrants were airlifted to Israel. The Yemenites, who lacked any formal schooling or knowledge of a western-style culture or bureaucracy, believed that they were being "redeemed," and put their trust in the Israeli authorities to make decisions about where they should go and what they should do. As a result, they were scattered across the country in essentially a random fashion, and as we show, the environmental conditions faced by immigrant children were not correlated with other factors that affected the long-term outcomes of individuals. We construct three summary measures of the childhood environment: 1) whether the home had running water, sanitation and electricity; 2) whether the locality of residence was in an urban environment with a good economic infrastructure; and 3) whether the locality of residence was a Yemenite enclave. We find that children who were placed in a good environment (a home with good sanitary conditions, in a city, and outside of an ethnic enclave) were more likely to achieve positive long-term outcomes. They were more likely to obtain higher education, marry at an older age, have fewer children, work at age 55, be more assimilated into Israeli society, be less religious, and have more worldly tastes in music and food. These effects are much more pronounced for women than for men. We find weaker and somewhat mixed effects on health outcomes, and no effect on political views. We do find an effect on the next generation – children who lived in a better environment grew up to have children who achieved higher educational attainment.
I find this paper noteworthy for several reasons:
(1) The authors have a credible and interesting source of variation, and the actual early life exposures they look at have immediate policy implications
(2) The authors explore a wide variety of different outcomes, including behavioral aspects. In my dissertation, I argued that long-run returns need to be taken into account when making resource allocation decisions. However, this is difficult if only a subset of long-run returns are known. This paper really hits this gap.
(3) Finally, and more self-serving, the long-run effects of sanitation and clean water jive well with my thesis paper on the National Clean Water Program in Mexico (see the next post).
This paper estimates the effect of the childhood environment on a large array of social and economic outcomes lasting almost 60 years, for both the affected cohorts and for their children. To do this, we exploit a natural experiment provided by the 1949 Magic Carpet operation, where over 50,000 Yemenite immigrants were airlifted to Israel. The Yemenites, who lacked any formal schooling or knowledge of a western-style culture or bureaucracy, believed that they were being "redeemed," and put their trust in the Israeli authorities to make decisions about where they should go and what they should do. As a result, they were scattered across the country in essentially a random fashion, and as we show, the environmental conditions faced by immigrant children were not correlated with other factors that affected the long-term outcomes of individuals. We construct three summary measures of the childhood environment: 1) whether the home had running water, sanitation and electricity; 2) whether the locality of residence was in an urban environment with a good economic infrastructure; and 3) whether the locality of residence was a Yemenite enclave. We find that children who were placed in a good environment (a home with good sanitary conditions, in a city, and outside of an ethnic enclave) were more likely to achieve positive long-term outcomes. They were more likely to obtain higher education, marry at an older age, have fewer children, work at age 55, be more assimilated into Israeli society, be less religious, and have more worldly tastes in music and food. These effects are much more pronounced for women than for men. We find weaker and somewhat mixed effects on health outcomes, and no effect on political views. We do find an effect on the next generation – children who lived in a better environment grew up to have children who achieved higher educational attainment.
I find this paper noteworthy for several reasons:
(1) The authors have a credible and interesting source of variation, and the actual early life exposures they look at have immediate policy implications
(2) The authors explore a wide variety of different outcomes, including behavioral aspects. In my dissertation, I argued that long-run returns need to be taken into account when making resource allocation decisions. However, this is difficult if only a subset of long-run returns are known. This paper really hits this gap.
(3) Finally, and more self-serving, the long-run effects of sanitation and clean water jive well with my thesis paper on the National Clean Water Program in Mexico (see the next post).
Friday, April 3, 2009
Correlation Does Not Imply Causation. And...?
Since I started grad school four years ago, I've noticed that the general public is much more attuned to idea of correlation not always implying causation. Of course, the indoctrination is not complete just yet, and there are plenty of instances where an association is mistaken for something more, but the fact that people are becoming better consumers of statistics is gratifying. I attribute this to the spate of popular press economics and statistics books/blogs in the last few years (though I might be in danger of confusing correlation and causation myself by saying this!)
The standards in empirical research reflect how seriously people are taking this motto: finding a clever instrumental variable or even experimental variation is no longer good enough. Papers without extensive "robustness" checks and falsification tests have less credibility now than they would have even five years ago. This, like the trend in the general public, is a good development.
However, with these positives come some more troubling tendencies. Specifically, I have a beef with the overuse of the causation-correlation dictum. Now, anybody can bring down a paper simply by saying "correlation does not imply causation" without having to provide a reason why this might be the case. For example, I am working on a paper looking at the long-run causal effects of birth year exposure to a clean water and sanitation efforts (I'll post a link to this paper in a month or so when a good draft is ready). I have a plausible identification strategy, and also include all sorts of controls, trends and falsification checks in my analysis to further establish causality. My results check out.
However, someone recently remarked told me that I should be concerned about omitted variables. When I pressed her on what these might be, she wasn't sure but commented that "there are always omitted factors."
Clearly, this isn't helpful. It's really easy to look/sound clever and point out that correlation does not imply causation: it is technically a true statement! But I think people who make this claim should talk about how it applies to the analysis at hand (i.e., have some kind of model or story that makes more explicit the nature of the potential biases and where they come from). Otherwise, the statement by itself is pretty uninformative and does little to advance our knowledge.
The standards in empirical research reflect how seriously people are taking this motto: finding a clever instrumental variable or even experimental variation is no longer good enough. Papers without extensive "robustness" checks and falsification tests have less credibility now than they would have even five years ago. This, like the trend in the general public, is a good development.
However, with these positives come some more troubling tendencies. Specifically, I have a beef with the overuse of the causation-correlation dictum. Now, anybody can bring down a paper simply by saying "correlation does not imply causation" without having to provide a reason why this might be the case. For example, I am working on a paper looking at the long-run causal effects of birth year exposure to a clean water and sanitation efforts (I'll post a link to this paper in a month or so when a good draft is ready). I have a plausible identification strategy, and also include all sorts of controls, trends and falsification checks in my analysis to further establish causality. My results check out.
However, someone recently remarked told me that I should be concerned about omitted variables. When I pressed her on what these might be, she wasn't sure but commented that "there are always omitted factors."
Clearly, this isn't helpful. It's really easy to look/sound clever and point out that correlation does not imply causation: it is technically a true statement! But I think people who make this claim should talk about how it applies to the analysis at hand (i.e., have some kind of model or story that makes more explicit the nature of the potential biases and where they come from). Otherwise, the statement by itself is pretty uninformative and does little to advance our knowledge.
Monday, March 30, 2009
Peer Effects in Technology Adoption and Consumer Decisions and Other Interesting Links
1. Emily Oster and Rebecca Thorton have an interesting new paper that uses individual-level randomization to understand, among other things, how peers affect a woman's decision to utilize newly introduced menstrual cups in Nepal.
2. Enrico Moretti looks at the importance of social learning from peers in consumption decisions - particularly the decision to see different movies. I really like this paper: Moretti starts with a theoretical model and uses the uniqueness of the film industry to test it. It's great stuff. And he goes on to find that social learning is non-trivial:
Overall, social learning appears to be an important determinant of sales in the movie industry, accounting for 32% of sales for the typical movie with positive surprise. This implies the existence of a large “social multiplier” such that the elasticity of aggregate demand to movie quality is larger than the elasticity of individual demand to movie quality.
3. Behavioral economics strikes again! Apparently a good way to save money is to carry around Benjamins over Abes and Georges.
4. The Economist is right on about the decision to move the Indian Premier League cricket matches to South Africa because of the upcoming election in India. What kind of aspiring superpower justifies moving a thriving capitalist enterprise by claiming that they cannot guarantee the safety of the players and spectators? Isn't this exactly what terrorists want to happen?
2. Enrico Moretti looks at the importance of social learning from peers in consumption decisions - particularly the decision to see different movies. I really like this paper: Moretti starts with a theoretical model and uses the uniqueness of the film industry to test it. It's great stuff. And he goes on to find that social learning is non-trivial:
Overall, social learning appears to be an important determinant of sales in the movie industry, accounting for 32% of sales for the typical movie with positive surprise. This implies the existence of a large “social multiplier” such that the elasticity of aggregate demand to movie quality is larger than the elasticity of individual demand to movie quality.
3. Behavioral economics strikes again! Apparently a good way to save money is to carry around Benjamins over Abes and Georges.
4. The Economist is right on about the decision to move the Indian Premier League cricket matches to South Africa because of the upcoming election in India. What kind of aspiring superpower justifies moving a thriving capitalist enterprise by claiming that they cannot guarantee the safety of the players and spectators? Isn't this exactly what terrorists want to happen?
Thursday, March 26, 2009
Is the Row Over AIG Bonuses Getting Ridiculous?
Yes.
Certainly, handing out a bonus package running in the hundreds of millions of dollars during a recession seems like poor form. Especially so when the firm involved played a big role in bringing the house of cards down. However, the public vitriol over this mess has taken on a disturbing character.
A recent open resignation letter by a former AIG VP printed in the New York Times does a pretty good job of laying out the argument. Basically:
(1) Salaries at AIG are low and most people make money through bonuses.
(2) The people responsible for the failure of AIG are no longer working there. The contended bonuses weren't meant to be given out to people in unrelated divisions doing unrelated things.
(3) The bonuses were part of a contractual obligation to get good workers to stay on during tough times. But more fundamentally, the bonuses were part of a compensation package promised to employees before AIG became the demon.
My beef with the whole row hinges on (3). It's ridiculous for people to demand the bonuses to be paid back (or to try and tax these at the rate of 90% or something like this). Nobody should be able to meddle with contracts retroactively. This is because this kind of activity could discourage people from generating real wealth during these tough times: why would anyone try to make money in this climate if they believe they are going to be demonized and that the government will try to take their money away. The bonuses row could serve as a huge disincentive for undertaking the kind of economic activities that we desperately need now.
Reason (2) also deserves some attention. While I don't see it as the best argument against the retroactive penalities (the whole company as a team argument), we need to think about how a few people could derail an entire financial system despite being around a majority of people who were engaged in activities that ostensibly generated real wealth. Perhaps the Geithner regulatory plan, to be announced sometime soon, will address this in a constructive way that doesn't hamper wealth creation.
Whatever the case may be, it is time to put down the pitchforks and start thinking about these issues in a more constructive (and less obviously destructive) manner.
Certainly, handing out a bonus package running in the hundreds of millions of dollars during a recession seems like poor form. Especially so when the firm involved played a big role in bringing the house of cards down. However, the public vitriol over this mess has taken on a disturbing character.
A recent open resignation letter by a former AIG VP printed in the New York Times does a pretty good job of laying out the argument. Basically:
(1) Salaries at AIG are low and most people make money through bonuses.
(2) The people responsible for the failure of AIG are no longer working there. The contended bonuses weren't meant to be given out to people in unrelated divisions doing unrelated things.
(3) The bonuses were part of a contractual obligation to get good workers to stay on during tough times. But more fundamentally, the bonuses were part of a compensation package promised to employees before AIG became the demon.
My beef with the whole row hinges on (3). It's ridiculous for people to demand the bonuses to be paid back (or to try and tax these at the rate of 90% or something like this). Nobody should be able to meddle with contracts retroactively. This is because this kind of activity could discourage people from generating real wealth during these tough times: why would anyone try to make money in this climate if they believe they are going to be demonized and that the government will try to take their money away. The bonuses row could serve as a huge disincentive for undertaking the kind of economic activities that we desperately need now.
Reason (2) also deserves some attention. While I don't see it as the best argument against the retroactive penalities (the whole company as a team argument), we need to think about how a few people could derail an entire financial system despite being around a majority of people who were engaged in activities that ostensibly generated real wealth. Perhaps the Geithner regulatory plan, to be announced sometime soon, will address this in a constructive way that doesn't hamper wealth creation.
Whatever the case may be, it is time to put down the pitchforks and start thinking about these issues in a more constructive (and less obviously destructive) manner.
Wednesday, March 18, 2009
Experiments, Natural Experiments and Learning about Development Policy - I
A while back I blogged about the Jameel Poverty Action Lab, a non-profit organization started and run by economists carrying out randomized field experiments all over the developing world. The purpose of these experiments is to build an evidence base to inform policy-making, and randomization as a tool towards this end has become quite popular of late. Proponents of randomization, now called "randomistas", argue that, as with medical clinical trials, field experiments are the "gold standard" in development policy evaluation.
But is this really so? In two recent pieces, Angus Deaton and Martin Ravallion argue that the answer is "no." One of their main arguments centers around the idea of heterogeneity in treatment effects, which basically refers to how policies do not have the same impacts for everyone. Consider an example where we are thinking about implementing some large policy and want to learn whether it might be effective. To do so, we consult data from a recent experiment in which some individuals in the sample have been randomized to receive "treatment." We then compare the treatment and control group outcomes.
Randomization of individuals to treatment gives us confidence that the results of the experiments are not biased. However, the concern is whether one can learn something useful about the policy from this experiment. In most field experiments, individuals in the treatment group are either enrolled in a program or incentivized to participate in some way. In most cases, not everyone complies, and some groups of individuals tend to be more likely to comply than others.
The important thing to note is that the program effects that are recovered from the experiment is most reflective of the returns to the group of compliers. This is referred to as a "local average treatment effect", or LATE. Here is where the problem comes in: the LATE that an experiment recovers may not always be policy relevant and, unlike the issue of limited external validity (experimental results in one setting may not apply to others), it is not clear that replications will help get around this problem. To reiterate, the benefits of the program that infer from an experiment may or may not be informative about this program on a larger scale.
Ultimately, this is problem of experiments being "atheoretical." That is, simply looking at experimental averages is not enough: we have to understand who in the treatment group actually responds to the randomization and takes up treatment and whether this group is of interest to the broader policy picture. Building this understanding brings us back to economic theory: we need a model. In this sense, the argument goes, proponents of randomization who argue that field experiments are "easy" by obviating the need for models or (strong) assumptions are badly mistaken.
I find this argument compelling. Indeed, there is a parallel literature in the "natural experiments" world that makes similar points. Ultimately, policy design and resource allocation decisions require a great deal of information, only some of which we can get from randomized experiments. Experiments that incorporate theory and heterogeneity, Deaton argues, will be good step towards making the method more useful towards policy decisions. In the next post, I will list a few examples of experimental and quasi-experimental studies that take an approach more grounded in theory.
But is this really so? In two recent pieces, Angus Deaton and Martin Ravallion argue that the answer is "no." One of their main arguments centers around the idea of heterogeneity in treatment effects, which basically refers to how policies do not have the same impacts for everyone. Consider an example where we are thinking about implementing some large policy and want to learn whether it might be effective. To do so, we consult data from a recent experiment in which some individuals in the sample have been randomized to receive "treatment." We then compare the treatment and control group outcomes.
Randomization of individuals to treatment gives us confidence that the results of the experiments are not biased. However, the concern is whether one can learn something useful about the policy from this experiment. In most field experiments, individuals in the treatment group are either enrolled in a program or incentivized to participate in some way. In most cases, not everyone complies, and some groups of individuals tend to be more likely to comply than others.
The important thing to note is that the program effects that are recovered from the experiment is most reflective of the returns to the group of compliers. This is referred to as a "local average treatment effect", or LATE. Here is where the problem comes in: the LATE that an experiment recovers may not always be policy relevant and, unlike the issue of limited external validity (experimental results in one setting may not apply to others), it is not clear that replications will help get around this problem. To reiterate, the benefits of the program that infer from an experiment may or may not be informative about this program on a larger scale.
Ultimately, this is problem of experiments being "atheoretical." That is, simply looking at experimental averages is not enough: we have to understand who in the treatment group actually responds to the randomization and takes up treatment and whether this group is of interest to the broader policy picture. Building this understanding brings us back to economic theory: we need a model. In this sense, the argument goes, proponents of randomization who argue that field experiments are "easy" by obviating the need for models or (strong) assumptions are badly mistaken.
I find this argument compelling. Indeed, there is a parallel literature in the "natural experiments" world that makes similar points. Ultimately, policy design and resource allocation decisions require a great deal of information, only some of which we can get from randomized experiments. Experiments that incorporate theory and heterogeneity, Deaton argues, will be good step towards making the method more useful towards policy decisions. In the next post, I will list a few examples of experimental and quasi-experimental studies that take an approach more grounded in theory.
Tuesday, March 3, 2009
Private Equity Firms, Orange Juice, and Other Interesting Links
1. Private equity firms spent much of the last decade throwing around large sums of money buying out companies and selling them out for profit after a series of adjustments. The high profile nature of these buyouts and the sheer amount of capital being thrown around begs the following question: what is/was it all for? In a recent working paper, Philip Leslie and Paul Oyer ask whether private equity firms "create value." Their results depressingly suggest than the answer is "no."
2. Steven Levitt has a great post on the intersection between orange juice, environmentalism, and behavioral economics.
3. Will the financial downturn mean less US money for global health? Karen Grepin reports that these outlays are safe for now.
4. Bouts of occasional stupidity are apparently very good for your development as a researcher (summary of the article here). I have yet to see any returns from this. (HT: Melanie Elliot)
2. Steven Levitt has a great post on the intersection between orange juice, environmentalism, and behavioral economics.
3. Will the financial downturn mean less US money for global health? Karen Grepin reports that these outlays are safe for now.
4. Bouts of occasional stupidity are apparently very good for your development as a researcher (summary of the article here). I have yet to see any returns from this. (HT: Melanie Elliot)
Thursday, February 26, 2009
Kenya to Deworm, Female Bank Robbers and Other Random Links
I'm in full-scale dissertation writing mode, so all you're getting from me between now and March 16th are links (if that). Enjoy!
1. Kenya has decided to roll-out a nationwide, school-based deworming program. The impetus for this likely came from some now famous experimental research carried out by Poverty Action Lab researchers Edward Miguel and Michael Kremer, showing that deworming (a) has large effects on school attendance and that these impacts are underestimated if one doesn't account for externalities (i.e., worms are infectious) and (b) is a highly cost effective way to improve schooling.
2. Martin Anderson, a former Yale MPHer and now a PhD student in Health Economics at Harvard, has started writing for the Social Science Statistics Blog (linked in the sidebar). His first post, on Medicaid drug procurement and the market for pharmaceuticals, is awesome.
3. Will tax credits stimulate the economy? Evidence from 2008 suggests not.
4. The number or share of bank robberies committed by women: a new leading or coincident indicator?
1. Kenya has decided to roll-out a nationwide, school-based deworming program. The impetus for this likely came from some now famous experimental research carried out by Poverty Action Lab researchers Edward Miguel and Michael Kremer, showing that deworming (a) has large effects on school attendance and that these impacts are underestimated if one doesn't account for externalities (i.e., worms are infectious) and (b) is a highly cost effective way to improve schooling.
2. Martin Anderson, a former Yale MPHer and now a PhD student in Health Economics at Harvard, has started writing for the Social Science Statistics Blog (linked in the sidebar). His first post, on Medicaid drug procurement and the market for pharmaceuticals, is awesome.
3. Will tax credits stimulate the economy? Evidence from 2008 suggests not.
4. The number or share of bank robberies committed by women: a new leading or coincident indicator?
Friday, February 20, 2009
Rising Incomes and Health Care Expenditures
We all know that health care expenditures as a percentage of GDP (per capita) has increased greatly over the last few decades and that this phenomenon has been observed in the US and foreign countries alike. Recent research has tried to understand the determinants of this increase and one common explanation is that health care is a luxury good: that is, as incomes rise people demand more and more of it. In some sense, this might make rising health care expenditures less ominous: we spend more only because it is an expression of our preferences.
Empirical evidence linking incomes to health generally supports the luxury good hypothesis and is based on establishing correlations between the two in micro and aggregate data. However, in a recent working paper, Daron Acemoglu, Amy Finkelstein, and Matthew Notowidigdo argue that this evidence may be misleading for two reasons. First, simple correlations do not capture other unobserved factors associated with income that might affect health. Second, such models do not distinguish between/account for partial and general equilibrium effects: for example, rising demand for health care generated by income may increase spending both through increased local demand, but also through supply side changes in medical technology or practices that respond to changes in demand. In addition, rising incomes and demand may lead to changes in the politics around health care and health services. In either case, it is important to understand both partial and general equilibrium t truly characterize the relationship between income and health.
Acemoglu, Finkelstein and Notowidigo try to get around both of these issues by utilizing shocks to oil prices. The basic idea of their paper is the following:
1) Look at a bunch of smaller areas which may or may not have pre-existing oil industries.
2) Changes in world oil prices, which are not driven by small industry in any single area will affect localities with oil industries differently than those without them. Thus, these two types of areas will experience different "shocks" to income. (Thus, the effect of income on health care demand is identified by the interaction between pre-existing oil industries and world oil price shocks). The next step is to look at the association between predicted income from oil price shocks and measures of health care demand.
3) Establish that general equilibrium effects occur at the level of localities and that it is unlikely that changes in local demand have equilibrium effects on larger regions (such as nations or the world).
The authors findings strongly suggest that health care is NOT a luxury good and that rising incomes likely cannot explain an important portion of the rise in health care expenditures.
Neat paper on an interesting area of research, and definitely worth reading.
Empirical evidence linking incomes to health generally supports the luxury good hypothesis and is based on establishing correlations between the two in micro and aggregate data. However, in a recent working paper, Daron Acemoglu, Amy Finkelstein, and Matthew Notowidigdo argue that this evidence may be misleading for two reasons. First, simple correlations do not capture other unobserved factors associated with income that might affect health. Second, such models do not distinguish between/account for partial and general equilibrium effects: for example, rising demand for health care generated by income may increase spending both through increased local demand, but also through supply side changes in medical technology or practices that respond to changes in demand. In addition, rising incomes and demand may lead to changes in the politics around health care and health services. In either case, it is important to understand both partial and general equilibrium t truly characterize the relationship between income and health.
Acemoglu, Finkelstein and Notowidigo try to get around both of these issues by utilizing shocks to oil prices. The basic idea of their paper is the following:
1) Look at a bunch of smaller areas which may or may not have pre-existing oil industries.
2) Changes in world oil prices, which are not driven by small industry in any single area will affect localities with oil industries differently than those without them. Thus, these two types of areas will experience different "shocks" to income. (Thus, the effect of income on health care demand is identified by the interaction between pre-existing oil industries and world oil price shocks). The next step is to look at the association between predicted income from oil price shocks and measures of health care demand.
3) Establish that general equilibrium effects occur at the level of localities and that it is unlikely that changes in local demand have equilibrium effects on larger regions (such as nations or the world).
The authors findings strongly suggest that health care is NOT a luxury good and that rising incomes likely cannot explain an important portion of the rise in health care expenditures.
Neat paper on an interesting area of research, and definitely worth reading.
Friday, February 13, 2009
Financial Crisis Trickling Down...
Time Magazine recently put out a piece identifying "25 People to Blame for the Financial Crisis." Actually, their piece should be retitled "300 Million People to Blame..." because one of the parties they accuse is the set of American consumers. The charge? Living beyond their means.
On this note, I've noticed recently that everyone is taking small steps to try and survive the downturn, sometimes in the most unexpected places/ways. Consider what happened to me yesterday:
1) I was told that I would have to provide my own cake for my upcoming thesis defense because the Graduate School was no longer making such purchases.
2) I was kicked out of Au Bon Pain because the management wanted to close up shop an hour early. One of the employees told me that the reason for this was that the cost of paying him for the extra hour and using the electricity far exceeded anything they would get from additional business. He went on to mention that, recently, the store would close early if number of customers was low, and urged me to bring my friends to ABP as well as to the nearby also suffering Gourmet Heaven.
Will the forthcoming tax breaks/credits and wages paid out to the labor force soaked up in infrastructure related jobs induce us to stimulate the economy by spending more money at ABP or on cakes? Only time will tell. At present though, the difference between our habits last year this time and our actions now are striking. I wonder if our new found parsimony will persist even after the crisis weathers: some recent research by Ulrike Malmendier and Stefan Nagel (see here for a summary) has shown that recession/depression era cohorts do have different investment habits (those experiencing macroeconomic hardship at young ages tend to be less risky and are less likely to participate in the stock market). Perhaps this extends to savings and spending behaviors, as well. Thoughts?
On this note, I've noticed recently that everyone is taking small steps to try and survive the downturn, sometimes in the most unexpected places/ways. Consider what happened to me yesterday:
1) I was told that I would have to provide my own cake for my upcoming thesis defense because the Graduate School was no longer making such purchases.
2) I was kicked out of Au Bon Pain because the management wanted to close up shop an hour early. One of the employees told me that the reason for this was that the cost of paying him for the extra hour and using the electricity far exceeded anything they would get from additional business. He went on to mention that, recently, the store would close early if number of customers was low, and urged me to bring my friends to ABP as well as to the nearby also suffering Gourmet Heaven.
Will the forthcoming tax breaks/credits and wages paid out to the labor force soaked up in infrastructure related jobs induce us to stimulate the economy by spending more money at ABP or on cakes? Only time will tell. At present though, the difference between our habits last year this time and our actions now are striking. I wonder if our new found parsimony will persist even after the crisis weathers: some recent research by Ulrike Malmendier and Stefan Nagel (see here for a summary) has shown that recession/depression era cohorts do have different investment habits (those experiencing macroeconomic hardship at young ages tend to be less risky and are less likely to participate in the stock market). Perhaps this extends to savings and spending behaviors, as well. Thoughts?
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