Peer social capital and academic achievement: evidence from a randomly assigned natural experiment
【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;
(Translated by LI Mengling)
. ① See the third part of this paper for the difficulties and processing strategies of this paper. [^Back]
. ① According to the interviews for official staff and students, about 98% of students prefer to live on campus with their original roommates. [^Back]
. ② See the third part of this paper for the details. [^Back]
. ① See the third part of this paper for a more detailed introduction. [^Back]
. ① See McPherson et al. (2001) for an overview of network homogeneity. [^Back]
. 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]
. ① See the Nature Experiments in the Social Sciences (Dunning, 2012) for more details. [^Back]
. 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]
. 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]
. 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]
. 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]
. 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]
. ① These students are generally short-term exchange students, which are also not eligible for scholarships. [^Back]
. 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]
. 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]
. ① Limited by space, the results of the robustness test are not presented in this paper and can be obtained from the author. [^Back]
Bian, Y., Zhang, W. & Cheng, C. Society (社会), (3) (2012).
Chen, Y. & Fan, X. Sociological Studies (社会学研究), (1) (2011).
Cheng, C. Youth Studies (青年研究), (4) (2012).
Cheng, C. Youth Studies (青年研究), (2) (2015).
Cheng, C. & Bian, Y. Society (社会), (4) (2014).
Cheng, C., Wang, Y. & Bian, Y. Population Research (人口研究), (2) (2015).
Guo, S. & Frasher, M. Propensity Score Analysis: Statistical Methods and Applications. Guo, Z. & Wu, X. (trans.) Chongqing: Chongqing University Press, (2012).
Liang, Y. Sociological Studies (社会学研究), (5) (2010).
Smith, A. The Theory of Moral Sentiments. Jiang, Z., Qin, B., Zhu, Z. et al. (trans.) Beijing: Commercial Press, (1997/1759).
Zhao, Y. & Hong, Y. Sociological Studies (社会学研究), (5) (2012).
Becker, Gary S. 1962, “Investment in Human Capital: A Theoretical Analysis.” The Journal of Political Economy 70 (5).
Bian, Yanjie 1997, “Bringing Strong Ties Back In: Indirect Ties, Network Bridges, and Job Searches in China.” American Sociological Review 62 (3).
Bian, Yanjie, Xianbi Huang & Lei Zhang 2015, “Information and Favoritism: The Network Effect on Wage Income in China.” Social Networks 40.
Blau, Peter M. & Otis Dudley Duncan 1967, The American Occupational Structure. New York: Wiley.
Brand, Jennie E. & Yu Xie 2010, “Who Benefits Most from College? Evidence for Negative Selection in Heterogeneous Economic Returns to Higher Education.” American Sociological Review 75 (2).
Brunello, G., M. De Paola & V. Scoppa 2010, “Peer Effects in Higher Education: Does the Field of Study Matter?” Economic Inquiry 48 (3).
Buchmann, Claudia & Ben Dalton 2002, “Interpersonal Influences and Educational Aspirations in12 Countries.” Sociology of Education 75 (2).
Burt, R.S.2001, “Structural Holes versus Network Closure as Social Capital.” In N. Lin, K. Cook & R. S. Burt (eds.), Social Capital: Theory and Research. New York: Aldine De Gruyter.
Burt, R. S. & K. Burzynska 2017, “Chinese Entrepreneurs, Social Networks, and Guanxi.” Management and Organization Review 13 (2).
Carbonaro, William J. 1999, “Opening the Debate on Closure and Schooling Outcomes: Comment on Morgan and Srensen.” American Sociological Review 64 (5).
Chen, Y. S. & B. Volker 2016, “Social Capital and Homophily Both Matter for Labor Market Outcomes: Evidence from Replication and Extension.” Social Networks 45.
Christakis, Nicholas A. & James H. Fowler 2013, “Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior.” Statistics in Medicine 32 (4).
Coleman, J. S. 1961, The Adolescent Society. New York: Free Press of Glencoe.
Coleman, J. S. 1988, “Social Capital in the Creation of Human Capital.” American Journal of Sociology 94.
Davies, Mark & Denise B. Kandel 1981, “Parental and Peer Influences on Adolescents’ Educational Plans.” American Journal of Sociology 87 (2).
DiMaggio, P. & F. Garip 2012, “Network Effects and Social Inequality.” Annual Review of Sociology 38.
Duncan, Otis Dudley, Archibald O. Haller & Alejandro Portes 1968, “Peer Influences on Aspirations: A Reinterpretation.” American Journal of Sociology 74 (2).
Dunning, Thad 2012, Natural Experiments in the Social Sciences: A Design-Based Approach. New York: Cambridge University Press.
Foster, G. 2006, “It’s not Your Peers, and It’s not Your Friends.” Journal of Public Economics 90 (8–9).
Galiani, S. & E. Schargrodsky 2010, “Property Rights for the Poor: Effects of Land Titling.” Journal of Public Economics 94 (9–10).
Giordano, Peggy C. 2003, “Relationships in Adolescence.” Annual Review of Sociology 29.
Griffith, A. L. & K. N. Rask 2014, “Peer Effects in Higher Education: A Look at Heterogeneous Impacts.” Economics of Education Review 39.
Guo, G., Y. Li, H. Y. Wang, T. J. Cai & G. J. Duncan 2015, “Peer Influence, Genetic Propensity, and Binge Drinking.” American Journal of Sociology 121 (3).
Haller, Archibald O. & Charles E. Butterworth 1960, “Peer Influences on Levels of Occupational and Educational Aspiration.” Social Forces 38 (4).
Harris, Judith Rich 2009, The Nurture Assumption: Why Children Turn Out the Way They Do. New York: Free Press.
Hasan, S. & S. Bagde 2013, “The Mechanics of Social Capital and Academic Performance in an Indian College.” American Sociological Review 78 (6).
Haynie, D. L. & D. W. Osgood 2005, “Reconsidering Peers and Delinquency: How Do Peers Matter?” Social Forces 84 (2).
Hout, Michael &William R. Morgan 1975, “Race and Sex Variations in the Causes of the Expected Attainments of High School Seniors.” American Journal of Sociology 81 (2).
Kremer, M. & D .Levy 2008, “Peer Effects and Alcohol Use among College Students.” Journal of Economic Perspectives 22 (3).
Lin, Nan 1999, “Social Networks and Status Attainment.” Annual Review of Sociology 25.
Lu, Yao, Danching Ruan & Gina Lai 2013, “Social Capital and Economic Integration of Migrants in Urban China.” Social Networks 35 (3).
Manski, C. F. 1993, “Identification of Endogenous Social Effects: The Reflection Problem.” Review of Economic Studies 60 (3).
McDill, Edward L. & James Coleman 1965, “Family and Peer Influences in College Plans of High School Students.” Sociology of Education 38 (2).
McPherson, M., L. Smith-Lovin & J. M. Cook 2001, “Birds of a Feather: Homophily in Social Networks.” Annual Review of Sociology 27.
Morgan, S. L. & A. B. Sorensen 1999, “Parental Networks, Social Closure, and Mathematics Learning.” American Sociological Review 64 (5).
Mouw, T. 2006, “Estimating the Causal Effect of Social Capital: A Review of Recent Research.” Annual Review of Sociology 32.
Petticrew, Mark, Steven Cummins, Catherine Ferrell, Anne Findlay, Cassie Higgins, Caroline Hoy, Adrian Kearns & Leigh Sparks 2005, “Natural Experiments: An Underused Tool for Public Health?” Public Health 119 (9).
Portes, Alejandro 1998, “Social Capital: Its Origins and Applications in Modern Sociology.” Annual Review of Sociology 24.
Ream, Robert K. & Russell W. Rumberger 2008, “Student Engagement, Peer Social Capital, and School Dropout among Mexican American and Non-Latino White Students.” Sociology of Education 81 (2).
Sacerdote, B. 2001, “Peer Effects with Random Assignment: Results for Dartmouth Roommates.” Quarterly Journal of Economics 116 (2).
Sacerdote, B. 2011, “Peer Effects in Education: How Might They Work, How Big Are They and How Much Do We Know Thus Far?” In Erik Hanushek, Stephen Machin & Ludger Woessmann (eds.), Handbook of the Economics of Education. Amsterdam: North Holland.
Sacerdote, B.2013, “Social Networks and the Identification of Peer Effects Comment.” Journal of Business and Economic Statistics 31 (3).
Sacerdote, B.2014, “Experimental and Quasi-Experimental Analysis of Peer Effects: Two Steps Forward?” Annual Review of Economics 6 (1).
Schultz, Theodore W.1961, “Investment in Human Capital.” American Economic Review 51 (1).
Sewell, William H., Archibald O. Haller & Alejandro Portes 1969, “The Educational and Early Occupational Attainment Process.” American Sociological Review 34 (1).
Smith, K. P. & N. A. Christakis 2008, “Social Networks and Health.” Annual Review of Sociology 34.
Spenner, Kenneth I. & David L. Featherman 1978, “Achievement Ambitions.” Annual Review of Sociology 4.
Stinebrickner, R. & T. R. Stinebrickner 2006, “What Can Be Learned about Peer Effects Using College Roommates?” Journal of Public Economics 90 (8–9).
Zimmerman, D. J. 2003, “Peer Effects in Academic Outcomes: Evidence from a Natural Experiment.” Review of Economics and Statistics 85 (1).