Peer social capital and academic achievement: evidence from a randomly assigned natural experiment

CHENG Cheng1

(1.Department of Sociology and Institute for Empirical Social Science Research, Xi’an Jiaotong University)

【Abstract】This paper explores the effect of peer social capital on adolescents’ academic performance. It uses the official dataset from a university in Chinese mainland, takes the issue of endogeneity into account, and finds that the academic ability of peers has indeed influenced the accumulation of human capital for university students. This finding stands contrast to what has been found in other research contexts. First, it is through an indirect rather than a direct way that peer social capital affects adolescents’ academic performance, as the peer networks affect university students’ performance by having an influence on their academic attitudes and behaviors. Second, as time passes by, the effect of peer social capital on university students’ academic performance gets stronger, rather than attenuates. Such an increase can be attributed to the role played by peers from roughly the same social class background, whereas those coming from quite different social background exert a steady impact on university students’ academic performance. Moreover, there is no solid evident indicating that peer social capital has different impact on university students with different social class backgrounds.

【Keywords】 peer social capital; academic achievement; influencing mechanism; natural experiment; social class background;

【DOI】

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(Translated by LI Mengling)

    Footnote

    [1]. ① See the third part of this paper for the difficulties and processing strategies of this paper. [^Back]

    [2]. ① According to the interviews for official staff and students, about 98% of students prefer to live on campus with their original roommates. [^Back]

    [3]. ② See the third part of this paper for the details. [^Back]

    [4]. ① See the third part of this paper for a more detailed introduction. [^Back]

    [5]. ① See McPherson et al. (2001) for an overview of network homogeneity. [^Back]

    [6]. ② The characteristics that the natural experiments are consistent with the instrumental variables does not come by easily, but a large number of reforms and pilot projects initiated by local governments or departments in the transitional period of China objectively have also created a good experimental field for researchers and provided a rare opportunity for academic innovation. [^Back]

    [7]. ① See the Nature Experiments in the Social Sciences (Dunning, 2012) for more details. [^Back]

    [8]. ② Due to that each college has several dormitory buildings, all the dormitory buildings (20 buildings) are included in the analysis model as dummy variables for controlling the influence of the common environment, thus the college is no longer included in the model as a control variable. [^Back]

    [9]. ① In the report evaluating the relationship with the roommate for the first-year students in university C, 87% of the students evaluate it “(very) good” and only 0.4% of them evaluate it “(very) bad.” In addition, 76.2% of the students have one of their roommates in the list of their three friends. [^Back]

    [10]. ② The pre-test data is best collected before students met with their peers, such as the academic performance of their peers in high school. See the research of Manski (Manski, 1993) for a detailed explanation of reflection problem. [^Back]

    [11]. ① The academic performance of network members in their first year of may be affected by the reflection effect, thus leading to the overestimate on the network effect. According to the analysis later, the network effect is increasing over time, so the reflection effect should be very weak in the first year. [^Back]

    [12]. ② Students can not apply for the scholarship with the academic achievement in their fourth year (because they have graduated from school), so it is not included in this study. [^Back]

    [13]. ① These students are generally short-term exchange students, which are also not eligible for scholarships. [^Back]

    [14]. ② The differences above all have passed the significance test, and more detailed statistics (including variable description statistics) can be obtained from the author. [^Back]

    [15]. ① In the analysis for social network, in order to distinguish the influence of different network members (alters) on actors (ego), data structures based on attributes are often extended into data structures based on relationships; that is, wide table is changed to long table. It also means copying multiple egos, each of which corresponds to a different alters. At this point, one case is reused multiple times, and the independence assumption between cases is no longer valid. By convention, the standard errors are adjusted based on the logistic regression, and the option in Stata is cluster (Burt and Burzynska, 2017). [^Back]

    [16]. ① Limited by space, the results of the robustness test are not presented in this paper and can be obtained from the author. [^Back]

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This Article

ISSN:1002-5936

CN: 11-1100/C

Vol 32, No. 06, Pages 141-164+245

November 2017

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Article Outline

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Abstract

  • 1 Research background and issues
  • 2 Literature review and hypotheses
  • 3 Research strategy
  • 4 Empirical results
  • 5 Conclusion and discussion
  • Footnote

    References