Social Econ Blog

Description/Hypothesis:

A college’s matriculation rate, otherwise known as the yield rate, measures the proportion of students who accept its offer of admission. These rates are of great interest to admissions offices all over the country for a number of reasons. First, the matriculation rate is used to rank colleges. If more students accept a school’s offer, then that school is deemed to be more desirable, and it will receive a higher ranking from such magazines as U.S. News and World Report. This past year, Harvard boasted one of the highest matriculation rates in the country with 78.5% of admits accepting its offer. In the same year, Yale’s rate was 72% and Princeton’s was 67.2%. The second reason that the matriculation rate is so important is diversity recruitment. Diversity initiatives in the admissions office would be useless if large portions of particular demographics choose not to enroll. This scenario is best exemplified at Amherst, who saw only a dozen African American students out of 140 accept its offer.

This paper will focus on the risk preferences of students who live far away from the school to which they matriculate. The general question that this paper will try to answer is: “Why do students choose to enroll in a College that is far away?” This insight would be a great help to admissions officers who want to increase their matriculation rates. While many variables can influence a student’s decision, distance is obviously an important factor. Being able to discern which students will enroll despite the distance would be a great help to admissions officers as they attempt to maintain regional diversity and keep their matriculation rates as high as possible.

Greater risk aversion should lead to a higher likelihood of staying in the same region. For all students, the costs of attending a school that is farther away should be greater than the cost of attending a school that is closer. In addition, these costs should be fairly clear to the student when he or she makes the choice. The benefits, however, are less clear. There is a safe choice (stay in one’s region) and there is a more risky choice (go to a school that is farther away). All else equal, if a student is to choose the more risky option, then he or she should be less risk averse.

Data/Empirical Strategy

I will study Californians that chose to remain in California (preferably Stanford or UC Berkeley) and Californians that now go to school at Harvard. All participants should have had the choice to attend schools on both coasts. My goal is to get enough data just from my friends here from California and their high school friends who remained in California. This should be as close to “all else equal” as I can achieve. To survey for risk aversion, I will use the following setup from an experiment by Holt and Laury:

http://www.jstor.org.ezp2.harvard.edu/view/00028282/sp030006/03x0202t/1?searchUrl=http%3a//www.jstor.org/search/BasicResults%3fhp%3d25%26si%3d1%26Query%3drisk%2baversion%2bexperiment&frame=noframe¤tResult=00028282%2bsp030006%2b03x0202t%2b0%2cFF1F&userID=80673cc8@harvard.edu/01cc99333c25da210b03577a9c&dpi=3&config=jstor

There should be a point where the survey taker “crosses over” from choice set A to choice set B. I will use the different cross over points to place the population into risk aversion categories. I will then observe the correlation of risk aversion to the choice to attend an east coast school or not.

Problems

I would like to find a way to measure risk aversion without having to use questions involving. Let’s assume that our person is risk averse with his or her money. Then that person might want to come to Harvard, assuming that he or she believes that the Harvard advantage card can guarantee her future income. On the other hand, I am not particularly concerned with this issue because Californians that go to Harvard assure me that they believe the Stanford advantage card to hold just as much weight. I believe that this is a misconception believed by all Californians.

Risk aversion has been seen to increase as the stakes increase. There are perhaps few decisions more important than the choice of a college. However, I believe if person A is more risk averse than person B in a high stakes game, person A will be more risk averse than person B in a low stakes game as well. The evidence from Holt and Laury supports this claim.

There is little I can do to insure that participants would make the same choice in real life as they say they would in the questionnaire. Other experiments get around this problem by actually offering money. I will most likely not offer money.

Ideally, I would like to have participants who very closely resembled each other (i.e. students who visited the schools the same number of times, spoke to the same people, went to the same high school, etc.). There will be a lot of omitted variables. Perhaps students that stay in California did not visit the school on the east coast. Visiting the school might lower the riskiness of choosing to go there. I will do my best to include questions in the survey that address certain lurking variables and control for them. I will ask questions pertaining to family income, familial responsibilities, school visiting, and friends’ decisions. Given the sample size that I will probably be working with, though, the effect of lurking variables could be large.

// posted by Anonymous @ 5:49 AM