Month: January 2012
4. Incentives matter, Indonesia style.
5. How is real estate evolving in the DC area?, by Steven Pearlstein.
…In December, officials from the country’s tourism board decided that they would hand over the reins of their @sweden Twitter account to a different citizen each week.
So far, the project, which has been called “the world’s most democratic Twitter account,” has featured tweets from a female priest, an advertising executive and an organic sheep farmer, Reuters reported.
This week, Sweden’s tweets are from Hanna, “just your average lesbian truck driver.”
“Gosh, I really enjoy being @sweden,” tweeted Hanna. “They’ll have to grab the account out of my dying hands.”
By mobility I mean whether people are crossing into different income quintiles or deciles than the ones they were born into, or the ones they enjoyed at an earlier period of life.
1. If the general standard of living is rising (and I am more than willing to admit problems in this area for the United States), mobility takes care of itself over time. I find it more useful to focus on slow growth, if indeed that is the case. Just look at income growth for non-wealthy families and that is more useful than all the mobility measures put together.
2. Measured mobility in the United States does not seem to be falling, or at least not falling much, as shown by Scott Winship.
3. For a given level of income, if some are moving up others are moving down. Do you take theories of wage rigidity seriously? If so, you might favor less relative mobility, other things remaining equal. More upward — and thus downward — relative mobility probably means less aggregate happiness, due to habit formation and frame of reference effects.
4. Why do many European nations have higher mobility? Putting ethnic and demographic issues aside, here is one mechanism. Lots of smart Europeans decide to be not so ambitious, to enjoy their public goods, to work for the government, to avoid high marginal tax rates, to travel a lot, and so on. That approach makes more sense in a lot of Europe than here. Some of the children of those families have comparable smarts but higher ambition and so they rise quite a bit in income relative to their peers. (The opposite may occur as well, with the children choosing more leisure.) That is a less likely scenario for the United States, where smart people realize this is a country geared toward higher earners and so fewer smart parents play the “tend the garden” strategy. Maybe the U.S. doesn’t have a “first best” set-up in this regard, but the comparison between U.S. and Europe is less sinister than it seems at first. “High intergenerational mobility” is sometimes a synonym for “lots of parental underachievers.”
5. How much of immobility is due to “inherited talent plus diminishing role for random circumstance”? Is not this cause of immobility very different — both practically and morally — from such factors as discrimination, bad schools, occupational licensing, etc.? What are you supposed to get when you combine genetics with meritocracy? I do not know how much of current American (or other) immobility is due to this factor, but I find it discomforting that complaints about mobility are so infrequently accompanied by an analysis of this topic.
6. I am more than willing to hear arguments than a less mobile society is a less stable society, or otherwise a society which makes worse political decisions. But I haven’t seen serious arguments here. By “serious arguments” I mean those which take endogeneity into account and go beyond noting that Denmark is a better polity than Brazil, and so on.
7. I would like all measurements in this area to take into account the pre-migration incomes of incoming entrants. Denmark, which doesn’t let many people in, is a much less upwardly mobile society once you take this into account. Sweden deserves more praise, and in general this factor will make the Anglo countries look much, much more supportive of mobility.
Addendum: Here is more from Scott Winship.
From Peter Seebach, I like this idea very much:
This leads to a concept: A restaurant called Placebo. What do they sell? A 50% discount. Which is to say: The entire menu is framed with everything at about twice the price you’d otherwise expect to pay for it, but then your check gets a 50% discount. So say you have a steak roughly of the same quality as the $13 steaks at the Outback Steakhouse. The menu says $26, your bill when it arrives has a 50% discount. But everything you order feels expensive.
And a bit more:
For extra credit, you could do interviews and arrange waiters to adopt personalities which suit the customers. Someone comes in who likes Good Wholesome Cooking? We can set you up with a waiter who thinks fancy food is ridiculous. Or, we can set you up with a waiter who is a total food snob, and you can have a wonderful meal knowing that the waiter is missing out on Good Wholesome Cooking. Your call.
The basic idea here is… people aren’t going out to eat for the food, they’re going out for the experience. Why not sell the experience as-such as the product? And thanks to some lovely research done on placebos in the 60s or so, we know that in some cases they work even if you know it’s a placebo — they’ve been shown to treat depression effectively even when explained.
From the excellent Scott Winship:
Krueger’s claim of a shrinking middle class relies on the same peculiar definition. Specifically, “middle class” is defined as having a household income at least half of median income but no more than 1.5 times the median. I re-ran the numbers using the same definition and data source as Krueger and found that the entire reason the middle class has “shrunk” is that more households today have incomes that put them above middle class. That’s right, the share of households with income that puts them in the middle class or higher was 76 percent in 1970 and 75 percent in 2010—two figures that are statistically indistinguishable. For that matter, I am not discovering fire here; Third Way made the same point in early 2007 (page 7). A shrinking middle class is only a problem if it reflects fewer people reaching the middle class.
The post is excellent throughout and it contains many more points of interest.
As another swipe at the West, Iranians will soon be able to buy toy versions of the US spy drone that it captured in December, Iranian media reported.
Models of the bat-wing RQ-170 Sentinel – which Iran’s military displayed on TV after it was downed near the Afghan border – will be mass produced in a variety of colours, reports said.
Here is more, mostly on the cultural war against Barbie dolls in Iran.
My favorite sandwich (ever) is the Hawaiiana, at “Tortas Chapultepec,” turn left out of the front of Hotel Camino Real in Polanco, and it is on the corner at Victor Hugo and Mariano Escobedo. They usually are open by 9:30 and I suspect they close fairly early.
Pujol does wonderful things with vegetables and is perhaps the best fancy place to try; I recommend the Menu de la Tierra.
They have done away with the food stalls at the Zócalo. In Mexico City calorie-counting menus are common and gelato is being replaced by frozen yogurt (!).
Tres Marias is a “food village” right off the highway on the way to Cuernavaca. Look for the place on the southbound side which specializes in green chilaquiles and also chorizo tacos, but in general standards along that strip are remarkably high.
Overall, Mexico City is becoming a safer city, and compared to four years ago one sees many signs of economic progress.
A working paper titled What Happens After Enrollment: An Analysis of the Time Paths of Racial Difference in GPA and Major Choice by Duke university economists Peter Arcidiacono and Esteban Aucejo and sociologist Ken Spenner is creating a stir. The authors track a sample of Duke students from admissions to graduation in order to determine the effects of affirmative action.
Under one theory of affirmative action the goal is to give minority students an opportunity to catch-up to their peers once everyone is given access to the same quality of schooling. On a first-pass through the data, the authors find some support for catch-up at Duke. In year one, for example, the median GPA of a white student is 3.38, significantly higher than the black median GPA of 2.88. By year four, however, the differences have shrunk to 3.64 and 3.31 respectively.
Further analysis of the data, however, reveal some troubling issues. Most importantly, the authors find that all of the shrinking of the black-white gap can be explained by a shrinking variance of GPA over time (so GPA scores compress but class rankings remain as wide as ever) and by a very large movement of blacks from the natural sciences, engineering and economics to the humanities and the social sciences. It’s well known that grade inflation is higher in the humanities and the social sciences so the shift in college major can easily explain the shrinking black-white gap in GPA. (The authors show that grades are higher in the humanities holding SAT scores constant and also that students themselves report that classes in the sci/eng/econ are harder than classes in the humanities and that they study more for these classes).
The shift of black students across majors is dramatic. Prior to entering Duke, for example, 76.7% of black males expect to major in the natural sciences, engineering or economics but only 35% of them actually do major in these fields (almost all Duke students do graduate so this result is due to a shift in major not dropping out). In comparison, 68.7% of white males expect to major in sci/eng/econ and 63.6% of them actually do graduate with a major in these fields (this is from Table 9 and is of those students who had an expected major). White and black females also exit sci/eng/econ majors at high rates, although the race gap for females is not as large as for males. The authors do not discuss the consequences of dashed expectations.
An important finding is that the shift in major appear to be driven almost entirely by incoming SAT scores and the strength of the student’s high school curriculum. In other words, blacks and whites with similar academic backgrounds shift away from science, engineering and economics and towards the easier courses at similar rates.
I have argued that the United States would benefit from more majors in STEM fields but that is not the point of this paper. The point is that there is no evidence for catch-up at Duke and thus to the extent that affirmative action can work in that way it may have to occur much earlier.
Hat tip: Newmark’s Door.
Acemoglu and Autor present a few non-controversial stylized facts about labor markets, including falling wages of low-skill workers, flattening of the wage premium for workers with less education than college completion, non-monotone shifts in inequality, polarization of employment in advanced economies, and skill-replacing technologies (and don’t forget the new Brynjolfsson and MacAfee book; it is important).
The simplest model is that, because of information technology, employers demand more skills. The job market responds accordingly, and eventually the education system responds too. The major shifts are driven by changing productivities of human capital, and that is one reason why the human capital model of labor markets has proven so robust. It accounts (mostly) for the big changes in labor market returns.
What would a signalling model predict as the results of skill-biased technical change? I am never sure. Those models are tricky with comparative statics predictions for at least three reasons:
1. Multiple equilibria are common and arguably essential,
2. It is assumed that employers cannot in the short run (medium run?) observe the marginal products of workers, and
3. The (supposed) relevant factor for employers, the degree, is past history and, if not quite carved in stone, credentialed retraining remains the exception in many market segments. It hardly drives wage outcomes or observed changes in wages.
The simplest (non-signaling) model is that wages follow MP, albeit with some lag, and adjusting for a suitably sophisticated notion of marginal revenue product, including morale effects on other workers.
Again, how should skill-based technical change matter in a signaling model? In the model, no employer observes (across what time horizon?) that the MPs of some workers have gone up and that other workers’ MPs have gone down. Yet it seems that changing MPs matter at margins. And if employers can sniff out changing MPs, this implies they can sniff out large MP differences more generally, which limits the scope of educational signaling.
It is a strong result these days that occupation and also job tasks predict earnings better than before (see pp.26-27 in the first link), including relative to level of education. That also seems to run counter to what signaling theories predict. Most likely we are now better at measuring the quality of workers and their educational signals don’t matter as much as they used to. The higher returns to post-secondary education, which account for most of the recent growth in the returns to college degrees (p.145 and thereabouts), are skill-based and they are tightly connected to occupation and job tasks.
These are all reasons why the signaling model for education is not growing in popularity, namely that it does not speak well to current comparative statics and to the current big stories in labor markets.
It is an embarrassing question for signaling models to ask: with what lag do employers get a good estimate of a worker’s marginal product? If you say “it takes 37 years” it is hard to account for all the recent changes in wage rates in response to technology, as discussed above.
Alternatively, let’s say the lag is two years. There are several RCT estimates of the return to education, based on earnings profiles measured over twenty or thirty year periods. The estimated returns to education are high, and if those returns were just signaling-based you would expect the IV-elevated individuals to show up as underskilled and for the credentials-based wage gains to fall away with a few years’ time. That doesn’t happen (if you are wondering, the IV-elevated individuals are those who for essentially random reasons end up getting more education, or an instrumental variable proxies as such, without the elevation being correlated with their underlying quality as workers,).
In other words, the signaling model is caught between two core results — high long-term measured returns to the education of IV-elevated individuals, and technology drives wage changes in the medium-term. It is hard for a signaling model to explain both of those changes at the same time.
There is a way to nest signaling models within human capital models, rather than viewing them as competing hypotheses. Using matching theories, let’s say employers learn the quality of workers they have, but find it hard to estimate the quality of workers they don’t have. IV-elevated workers can’t fool the market/the employer for very long, and so their high pecuniary returns from education really do measure productivity gains. Nonetheless there can be undervalued “diamonds in the rough.” Think of them as geniuses, or at least good workers, who hate getting the education.
From the point of view of these students (or dropouts, as the case may be), the signaling model will appear to be true. They will resent the education and they won’t need the education. If it is costly enough to sample worker quality from the “outsiders bin,” it will remain an equilibrium that a degree is required to get the job, at least provided workers of this kind are not too numerous. If there were “lots and lots” of such workers, more employers would scrounge around in the outsider’s bin. In other words, the anecdotal evidence for signaling fits into a broader model precisely because such cases aren’t too common.
I find only this article in Portuguese, in any case very sad. Here is Mussa on Google Scholar. Here is one of his most famous pieces on exchange rates. Here is a short biography. Here is Mussa on monetary policy in the 1980s. I am sorry to have never known him (I met him once), but many admired him.
Addendum: Here is some good English language coverage.
At MIT, King, 63, and then-professor Ben S. Bernanke, 58, had adjoining offices in 1983, spending the early days of their academic careers in an environment where economics was viewed as a tool to set policy. Earlier, Bernanke and European Central Bank President Mario Draghi, 64, earned their doctorates from the university in the late 1970s, Draghi with a thesis entitled “Essays on Economic Theory and Applications.”
Fischer, 68, advised Bernanke’s thesis on “Long-Term Commitments, Dynamic Optimization and the Business Cycle,” and taught Draghi. Greek Prime Minister and former ECB vice president Lucas Papademos and Olivier Blanchard, now chief economist for the International Monetary Fund in Washington, earned their doctorates from MIT at about the same time.
Other monetary policy makers who have passed through MIT’s doors include Athanasios Orphanides, head of the Central Bank of Cyprus, Duvvuri Subbarao, governor of the Reserve Bank of India and Charles Bean, King’s deputy in the U.K.
Central banking is filled with former attendees of the Cambridge, Massachusetts, university not just because it was and is one of the world’s top schools for economics.
Arnold Kling comments.
I’ve wondered about this question for a while. Let’s say that bank manager/CEOs can play a profitable moral hazard game by risking that the lower left tail of the returns distribution won’t happen. Write some far out-of-the-money naked puts, or more generally synthesize that position. If you are a sports fan, imagine betting against the Washington Wizards to win an NBA title every year. Most years you earn some above-normal profits. Every now and then you go bankrupt. From the manager’s point of view there are bonuses in the good years and in the bankruptcy year the worst that can happen is getting fired. You might even be rehired rather quickly, if shareholders like such strategies too, at the expense of bondholders or taxpayers. Think of that as a private arbitrage opportunity, albeit one with negative social value.
The question is, what happens to the price of that strategy? Does it adjust to choke off more “going short volatility” at the margin? I see at least two options:
1. The return from writing a naked put (and related synthetic positions) falls somewhat, as many banks play that strategy or would play that strategy if the prices of the relevant bets did not adjust. What is then the story for the market as a whole? Are some of the “moral hazard gains” shared with those who buy naked puts? Why should the “tax incidence” problem stop there? Where exactly in the system do those gains come to rest? For sure there are gains to the early users of this moral hazard strategy, but once market prices are adjusting where do the gains go? Can excess returns be seen in observed securities prices?
Of course that there are *many* synthetic ways of writing the naked put or shorting volatility. Do the prices of all of them adjust, over time, as the early users of the strategy scurry from one opportunity, see it closed off by price shifts, and then move on to the next?
The cynic will think that hedge funds are doing well on this one.
2. Perhaps some banks play this strategy but their trades, relative to liquid markets, are not big enough to push around the price. Or maybe arbitrage is too strong and it keeps securities prices in line with standard theory.
Imagine that the fundamental value of a security was $40, but a beautiful woman would give a trader a kiss every time he bought the security, bringing his net private return to $41. Due to arbitrage and short sales, the price of the security will remain at $40, although the private gains will persist from the purchases.
In the latter case banks can’t raise enough liquidity to budge the market price, relative to the power of the other side of the market. Along related lines, legal and institutional constraints may limit the “short volatility” strategy and also blunt the effect of those strategies on market prices.
Which case is better/worse for the world as a whole? Does it matter for financial regulation which case is true?
I thank an anonymous hedge fund manager for a conversation on this topic, Interfluidity as well.
Remember those old debates on MR as to what opportunity cost is exactly supposed to mean? Joel Potter and Shane Sanders have an interesting follow-up paper:
Abstract: Ferraro and Taylor (2005) asked 199 professional economists a multiple-choice question about opportunity cost. Given that only 21.6 percent answered “correctly,” they conclude that professional understanding of the concept is “dismal.” We challenge this critique of the profession. Specifically, we allow for alternative opportunity cost accounting methodologies—one of which is derived from the term’s definition as found in Ferraro and Taylor— and rely on the conventional relationship between willingness to pay and substitute goods to demonstrate that every answer to the multiple-choice question is defensible. The Ferraro and Taylor survey question suggests difficulties in framing an opportunity cost accounting question, as well as a lack of coordination in opportunity cost accounting methodology. In scope and logic, we conclude that the survey question does not, however, succeed in measuring professional understanding of opportunity cost. A discussion follows as to the concept’s appropriate role in the classroom.