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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Peer Effects: Evidence from the Students in Taiwan

Wu, Shin-Yi, WU 02 November 2017 (has links)
No description available.
2

Adolescent friendship network and college enrollment : a longitudinal network analysis of selection and influence processes

Wu, Zebing 01 July 2015 (has links)
Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), I investigate the influence of adolescent friendship network on the likelihood of college enrollment, and whether and how this influence is affected by stratification factors (e.g., gender, race/ethnicity, and socioeconomic status). However, there is a challenge in evaluating this influence process since adolescents usually non-randomly select their friends. A selection process needs to be taken into consideration simultaneously with the influence process of adolescents’ friendship network on their likelihood of college enrollment. Previous research on peer effects has methodological issues and limitations. Traditional methods (e.g., multivariate regression, multilevel modeling, or propensity score matching) using limited data (e.g., cross-sectional) and measures of friendship network (e.g., one best friend) could not solve the problem of integrating selection process and influence process in one model. In addition, the dyadic and triadic (or even higher level) dependency among friends in the network makes it more difficult to estimate selection and influence processes using traditional methods. To address these concerns, I employ longitudinal network analysis with stochastic actor-based models (SABMs) to account for the influence of friendship network on adolescent college enrollment when simultaneously considering the selection of friendship. The co-evolution model of network dynamics (selection) and behavioral dynamics (influence) also addresses the problem of endogeneity between network change and behavioral change. However, the co-evolution model requires network data and behavioral data measured in multiple time points, so in the first stage of this research, I generate the predicted probability of college enrollment at three time points of Add Health using traditional logistic regression. Then in the second stage of this research, I use the transformed likelihood of college enrollment, a statistical artifact, as the behavior variable in the co-evolution model to examine how the likelihood of college enrollment affect the friendship selection and in turn friend’s average likelihood of college enrollment in the network influences an adolescent’s own likelihood of college enrollment. In the first stage, I find that there are some levels of gender, race/ethnicity, and SES inequalities in the college enrollment, even after controlling for previous academic achievement, other individual characteristics, family backgrounds, and school level variables. In the second stage, the results of dynamic network analysis indicate significant selection (partial deselection) and influence effects of adolescent friendship networks on the likelihood of college enrollment. In the selection process, adolescents have high tendency to select friends who are similar to them in the likelihood of college enrollment, or terminate friendships with other students of dissimilar likelihood of college enrollment. In the influence process, the average alter effect is found consistently significant and positive across all models and schools, which indicates that there is strong social influence of friendship network on adolescents’ likelihood of college enrollment. The higher the average friends’ likelihood of college enrollment, the more likely the adolescent will increase own likelihood of college enrollment. I also discuss the significance of results and many important policy and practical implications.

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