It takes two shining lights to brighten the room: peer effects with random roommate assignments

ABSTRACT

We used housing assignment data from a college in China to investigate peer effects on college grades. Study results provided some evidence for peer effects in college housing units. First, peer effects through means occurred during both fall and spring semester of the first year in college, with estimated effect much larger than that in previous studies. Second, students are also influenced by the mix of roommates. Finally, having more than one roommate in the top quartile has large and significant effects for female students; however, this positive effect is not statistically significant for male students.

KEYWORDS:

• College
• peer effects
• academic performance

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Though the students are not assigned based on revealed living habits, they are assigned to their registration type, time, and available building upon their registration. We control all these conditions to avoid possible hidden similarities between students sharing similar registration pattern. In addition, our data collection and field work suggested that in some cases our random assignment process is not entirely clear-cut. For example, friends may compromise the random assignment process by registering—intentionally or unintentionally—at approximately the same time. We remedy this by deleting possible self-selected roommates which are identified through detailed students' background information and registration process information.

2. Studies have also examined peer effects of roommates on social outcomes including drinking, smoking, and joining fraternity (Eisenberg, Golberstein, and Whitlock 2013; Sacerdote 2001; Wilson 2007).

3. We use a students’ College Entrance Exam score as a measurement of academic ability. The College Entrance Exam is a standard test for high school seniors before they enter college. A detailed description is provided in the data session.

4. In China’s higher education system, over 2100 colleges and universities are broadly grouped into four tiers based on academic reputation and admission selectivity. The first tier, located at the top of the higher education hierarchy, consists of approximately 120 key national colleges and universities. These institutions attract top students nationally. The next tier consists of well-known regional colleges and universities, who also attract students from other provinces. The third tier becomes more regional focused. And the last group consists of a large number of sub-baccalaureate institutions.

5. High school students select between Science and Humanity tracks in their 11th grade. They are tested on different subjects in the College Entrance Exam.

6. In our analysis, we use students' dormitory room at the end of their first year. As only few students changed their dormitory rooms, students’ initial (in the beginning of their first year) and final (in the end of their first year) dormitory rooms are identical for the vast majority of students.

7. Once we repeated the simulation over 100 times, the distribution for number of rooms with roommates from the same high school was very stable.

8. Before estimating these final models, we used the exact specifications in Table 6 to predict student own CEE scores (without this variable in the right-hand side of the equation). This additional exercise further confirmed our previous analyses in Table 2, that is, student quality or pre-treatment conditions are not related to roommates.