期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2017
卷号：114
期号：48
页码：E10291-E10300
DOI：10.1073/pnas.1705451114
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：We measure the social preferences of a sample of US medical students and compare their preferences with those of the general population sampled in the American Life Panel (ALP). We also compare the medical students with a subsample of highly educated, wealthy ALP subjects as well as elite law school students and undergraduate students. We further associate the heterogeneity in social preferences within medical students to the tier ranking of their medical schools and their expected specialty choice. Our experimental design allows us to rigorously distinguish altruism from preferences regarding equality–efficiency tradeoffs and accurately measure both at the individual level rather than pooling data or assuming homogeneity across subjects. This is particularly informative, because the subjects in our sample display widely heterogeneous social preferences in terms of both their altruism and equality–efficiency tradeoffs. We find that medical students are substantially less altruistic and more efficiency focused than the average American. Furthermore, medical students attending the top-ranked medical schools are less altruistic than those attending lower-ranked schools. We further show that the social preferences of those attending top-ranked medical schools are statistically indistinguishable from the preferences of a sample of elite law school students. The key limitation of this study is that our experimental measures of social preferences have not yet been externally validated against actual physician practice behaviors. Pending this future research, we probed the predictive validity of our experimental measures of social preferences by showing that the medical students choosing higher-paying medical specialties are less altruistic than those choosing lower-paying specialties.
