Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Economics

Supervisor

Conley, Timothy

2nd Supervisor

Rivers, David

3rd Supervisor

Stinebrickner, Todd

Abstract

In this dissertation, I explore peer effects and social networks among MBA students in a Canadian business school. The unique feature of the data collected for this research is that the students are administratively assigned to small groups, providing plausibly exogenous variation that allows me to identify causal peer effects. Chapter 1, “Peer Effects in an MBA class”, establishes the existence and magnitude of the effects of peer characteristics on academic outcomes of MBA students. It shows that peer effects are heterogeneous across courses and student characteristics. Chapter 2, “Testing team allocation rules”, uses these results to find the allocations of students across peers that produce the highest grades for the Managerial Finance course. I find that separating students by their admission GPA (a proxy for academic ability) may result in the best grades in Managerial Finance class. I discuss the role of the business school and posit that academic achievement may not be the only outcome that is important for business school graduates. Finally, in Chapter 3, “Comparison of the Two Methods of Social Network Data Collection”, I compare two methods of social network data collection: a recollection and a recognition method. First, I present descriptive results of the data collected by these two methods. Then I use the approach described in Comola and Fafchamps (2017) to estimate the true proportion of links by using the information from the discordant answers. I conclude by commenting on the appropriate uses of the two methods of social network data collection.

Summary for Lay Audience

In this dissertation, I explore peer effects and social networks among MBA students in a Canadian business school. The unique feature of the data collected for this research is that the students are administratively assigned to small groups, which allows me to avoid a common problem of students selecting their own peer groups. Chapter 1, Peer Effects in an MBA class, establishes the existence and magnitude of the effects of peer characteristics on academic outcomes of MBA students. It shows that students may affect each other differently in different courses. It also shows that various types of students may be influenced by their peers in different ways. Chapter 2, Testing team allocation rules, uses these results to find the allocations of students across groups that produce the highest grades for the Managerial Finance course. I find that separating students by their admission GPA (a proxy for academic ability) may result in the best grades in Managerial Finance class. I discuss the role of the business school and posit that academic achievement may not be the only outcome that is important for business school graduates. Finally, in Chapter 3, Comparison of the Two Methods of Social Network Data Collection, I compare two methods of social network data collection: a recollection method, where we ask respondents to name their friends, and a recognition method, where we ask them to pick friends from a given list. First, I present descriptive results of the data collected by these two methods. Then I use the approach described in Comola and Fafchamps (2017) to estimate the true proportion of links by using the information from the data where respondents disagree on whether or not they are connected. I conclude by commenting on the appropriate uses of the two methods of social network data collection.

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