Archive for the ‘economics’ Category
Two years ago, President Obama announced a plan to create government ratings for colleges—in his words, “on who’s offering the best value so students and taxpayers get a bigger bang for their buck.”
The Department of Education was charged with developing such ratings, but they were quickly mired in controversy. What outcomes should be measured? Initial reports suggested that completion rates and graduates’ earnings would be key. But critics pointed to a variety of problems—ranging from the different missions of different types of colleges, to the difficulties of measuring incomes along a variety of career paths (how do you count the person pursuing a PhD five years after graduation?), to the reductionism of valuing college only by graduates’ incomes.
Well, as of yesterday, it looks like the ratings plan is being dropped. Or rather, it’s become a “college-rating system minus the ratings”, as the Chronicle put it. The new plan is to produce a “consumer-facing tool” where students can compare colleges on a variety of criteria, which will likely include data on net price, completion rates, earning outcomes, and percent Pell Grant recipients, among other metrics. In other words, it will look more like U-Multirank, a big European initiative that was similarly a response to the political difficulty of producing a single official ranking of universities.
A lot of political forces aligned to kill this plan, including Republicans (on grounds of federal mission creep), the for-profit college lobby, and most colleges and universities, which don’t want to see more centralized control.
But I’d like to point to another difficulty it struggled with—one that has been around for a really long time, and that shows up in a lot of different contexts: the criterion problem.
Planet Money had a fun podcast a couple of days ago about Eric Meyer, the young founder of Haystack, a Baltimore-based app that allowed people to auction off their (public) parking spot to the highest bidder. MonkeyParking, a similar app, got attention last year in San Francisco.
The founders, in both cases, focused on the time-saving, traffic, and environmental benefits of such an app. Clearly there are real costs to people spending long periods of time circling the block in search of parking. UCLA economist Donald Shoup has argued that 30% of traffic in central business districts results from people looking for parking.
But these apps quickly generated enormous hostility. People used words like “disgusting,” “evil” and called it “JerkTech”—all to the apparent surprise of Meyer, at least. Within months, Boston and San Francisco had passed ordinances forbidding the selling of public parking spots. Haystack and MonkeyParking were basically shut down by the end of the year. (MonkeyParking has since retooled as a way to sell the parking in your driveway.)
This is a familiar story to economic sociologists. Some area of life that was previously outside of the market is suddenly brought into it. Violent feeling erupts, as such transactions are seen to challenge the moral order. (See Zelizer, Healy, Quinn, Chan, etc.) Generally, the market wins, and morality adapts.
There aren’t too many things—humans, organs (though even that’s eroding)—where a bright line still forbids buying and selling. Why, then, do Haystack and similar apps generate such hostility?
I think there are a couple of independent things prompting the hostile reaction.
1. Something that was, at least superficially, free, suddenly comes to cost money. People really don’t like being charged for things that used to be free, even if they were always paying for it somehow. (See: airline fees.)
2. Someone is making money by selling public property. This one is probably more important to city officials than city residents. From this perspective, the problem isn’t selling the spot, but who’s receiving the gains. Indeed, some of the same cities that reacted so negatively to these apps (I’m looking at you, San Francisco) have introduced dynamic pricing of parking, which allows prices to fluctuate with demand. (Think: Uber surge pricing.)
3. Now only the well-off can afford to park. This objection is to my mind the most legitimate. And while I fully recognize that it is really wasteful to have people circling around looking for parking, I don’t think it can easily be dismissed.
Now, I don’t want to stake any big claims around the inalienable right of Americans to park their cars. After all, you have to have a certain amount of money to have a car in the first place. And in general I think policies that discourage driving are good.
And it’s the very basis of capitalism to accept that there are things that some people can afford and others can’t, and to make one’s peace with that. But the thing about price caps (whether the cap is zero, as for street parking, or some flat rate, as with taxicabs) is that while they are inefficient, they are also democratizing. Yes, you may have to circle the block for 20 minutes. But dammit, so do the tech entrepreneurs who are pricing you out of your apartment. There are some things you can’t buy your way out of.
We live in a society in which inequality continues grow. At the same time, technology is improving our ability to make people who are willing (and able) to pay a lot do just that. That may be efficient. But it further reduces the sense that we’re all in this game together. And that’s the issue we don’t have a good solution for.
The mathematician John Nash recently died as the result of an taxi accident in New Jersey. His importance as a scientist is based mainly on a very productive period in his early 20s before he was crippled by the onset of mental illness. His two main scientific contributions are the discovery of the Nash equilibrium for finite games and an extremely important theorem in differential geometry, which essentially states that there exists a vector space where you can embed a smooth surface without self-intersection in a distance preserving fashion.
Here, I want to focus a little on why Nash’s game theory work became so important. He was not the first to study competition within the framework of game theory. Before Nash, a number of economists and mathematicians had worked on game theory, but they got stuck. Some ran into technical problems and could not get beyond the concept of zero sum games. Other had a lack of imagination. The great mathematician Johnny Von Neumann, for example, focused on cooperative games.
Nash’s approach was simple and deep. If you could write down the pay-off matrix of a game, you can come up with the “best response.” If A follows strategy X1, then B’s best answer is Y1. Similarly, if A plays X2, then B will play Y2. It is not hard to see that you can parameterize this argument – you can continuously move from X1 to X2 and thus the other player will move from Y1 to Y2. The profound idea is that having an equilibrium means that the “curve” connecting X1 to X1 intersects the curve connecting Y1 to Y2 and the intersection always exists due to a super-deep theorem called the Kakutani fixed point theorem.
Nash’s approach is ingenious on many levels. It turned an economic modeling problem into a geometry problem. It is very general and works for any game with a finite number of moves. And it spurred the search for equilibrium concepts in even more general settings.
So yesterday I offered some pointers to the neighborhood effects literature, which is relevant to the new research on social mobility that is receiving extensive coverage in the NYT and elsewhere. Commenter Robert Park (it’s good to know that earthly departure does not preclude keeping up with orgtheory) mentioned additional work worth highlighting (links added by me):
On the efficacy of residential mobility programs, I’d note the work of Rosenbaum and Rubinowitz “Crossing the Class and Color Lines” which studies the Gautreaux program, on which MTO was based, and more recently, “Climbing Mt. Laurel” by Doug Massey and colleagues and the work of Stefanie Deluca.
I know I have not mentioned many significant scholars, which I hope will be read not as a slight but as a reflection of how deep and rich this literature is in sociology.
But today I want to add a few comments on the question of why Chetty and Hendren’s work is getting so much attention when related work in sociology has not.
The New York Times posted a big feature yesterday on a couple of new papers by Harvard economists Raj Chetty, Nathaniel Hendren, and Lawrence Katz. The papers, like much of Chetty’s other work, use deidentified individual-level tax data to get at factors affecting income over time. In this case, they are interested in getting at neighborhood effects—in one paper, county-level effects on intergenerational income change, and in the other, the effects of the Moving to Opportunity experiment, which in the 1990s provided housing vouchers through a lottery system, on the same.
The big findings are that moving to a better neighborhood improves children’s income as adults, with the effects being cumulative. The experimental MTO data shows that each additional year of residence in the new neighborhood contributes linearly to an increase in adult income. However, the effects of a move zero out around age 13, after which they may be negative. The quasi-experimental data on non-MTO moves, which cleverly compares different-age siblings to get at length of exposure to the new neighborhood, points to substantial variation in mobility across counties for children at various income levels. The NYT visualization of this latter data, which is personalized by your location, is really terrific.
It’s some impressive work. But sociologists, of course, have been studying neighborhood effects for a long time. And while there is a lot of interest in the study, there is also a not-totally-unjustified sense of annoyance:
Big News: Economists discover a thing sociologists have been studying in detail for about a century. https://t.co/AxVkIfqsyw
— Mervyn Horgan (@simmelian) May 4, 2015
I’m fascinated both by the studies, sociologists’ reaction to them, and how the research is picked up and interpreted by the media. I tried to put all those things into one post, but it was getting way too long. So I’m going to break my reactions into a couple of chunks. Today, I’ll highlight some of the excellent existing work by sociologists in this area. Tomorrow, I’ll comment on why Chetty and Hendren’s work is getting so much more attention than related work in sociology. And later this week I’ll address how this kind of research gets covered in the media and is likely to be translated into policy conversations.
So for starters, some pointers to the sociology literature.
Yesterday, I described a paper written by Kirby Schroeder and my self on infection networks. Yesterday’s post addresses the professional lessons I learned. Today, I want to talk about the impact of the paper on current work. For a long time, the paper, literally, got zero citations in peer reviewed journals. Then, the citations increased around 2010, with people in economics, health, and biology discussing the paper.
Economics: The main commentary among economists is that this is a model of interaction, which can then be used to assess the impact of policy. For example, a paper in the American Law and Economics Review notes that the paper models risky behavior but does not model the law. Other economists are attracted to our prediction about infection knowledge and epidemic plateaus (once the disease becomes common knowledge, people shift behavior and transmission stalls).
Health: The Archives of Sexual Behavior has an article that discusses our article in the context of trying to expand models of disease transmission. For example, we critique the health belief model for ignoring interaction. We criticize sexual scripting theory for ignoring risk and strategic action.
Biology: Perhaps the most interesting impact of the paper is the impact on mathematical biology. In The Journal of Theoretical Biology, a team of mathematicians use the model to address group formation. In a model derived from our Risky Sex Game model, they show that the population, under certain conditions, will separate into specific groups based on HIV status.
Bottom line: People sure hated the paper when I wrote it, but its children are a joy to behold.
When people look at PhD programs, they usually base their judgment on the fame of its scholars or the placement of graduates. Fair enough, but any seasoned social scientist will tell you that is a very imperfect way to judge an institution. Why? Performance is often related to resources. In other words, you should expect the wealthiest universities to hire away the best scholars and provide the best environment for training.
Thus, we have a null model for judging PhD program (nothing correlates with success) and a reasonable baseline model (success correlates with money). According to the baseline, PhD program ranks should roughly follow measures of financial resources, like endowments. Thus, the top Ivy League schools should all have elite (top 5) programs in any field in which they choose to compete, anything less is severe under performance. Similarly, for a research school with a modest endowment to have a top program (say Rutgers in philosophy) is wild over performance.
According to this wiki on university endowments, the top ten wealthiest institutions are Harvard, Texas (whole system), Yale, Stanford, MIT, Texas A&M (whole system), Northwestern, Michigan, and Penn. This matches roughly with what you’d expect, except that Texas and Texas A&M are top flight engineering and medicine but much weaker in arts and sciences (compared to their endowment rank). This is why I remain impressed with my colleagues at Indiana sociology. Our system wide endowment is ranked #46 but our soc programs hovers in that 10-15 range. We’re pulling our weight.