This thesis is a collection of three essays. The first two study how ideas spread through a network of individuals, and how it an advertiser can exploit it. In the model I develop, users choose their sources of information based on the perceived usefulness of their sources of information. This contrasts with previous literature where there is no choice made by network users and thus, the information flow is fixed. I provide a complete theoretical characterization of the solution and define a natural measure of influence based on choices of users. I also present an algorithm to solve the model in polynomial time on any network, regardless of the scale or the topology. I also discuss the properties of a network technology from a public economic standpoint. In essence, a network allows the reproduction of ideas for free for the advertiser. If there is any free-riding problem, I show that coalitions of users on the network can solve such problem. I also discuss the social value of networks, a value that cannot be captured for profit. The third essay is completely distinct from the network paradigm and instead studies funding rules for public universities. I show that a funding rule that depends solely on enrolment leads to "competition by franchise" and that such behavior is sometimes inefficient. I suggest instead an alternate funding rule that allows government to increase welfare without increasing spending in universities. / Thesis (Ph.D, Economics) -- Queen's University, 2013-10-11 17:16:42.178

In 2008, state legislatures provided $6 billion in financial aid to 2 million low-income young adults. When low-income young adults receive state financial aid and do not complete college, states lose their investment because fewer people with degrees will contribute to the state's economy. Declining states' budgets have led to (a) the rising cost of higher education, (b) state merit-based aid that has targeted nonminority students from affluent backgrounds, and (c) state need-based aid that has targeted students further along in their college career. State need- and merit-based aid may contribute to the lack of college completion among low-income freshman students who rely on financial aid. The purpose of this study was to explore the differences between state need- and merit-based aid as enrollment factors of low college completion among low-income students in the U.S. This study was grounded on Tinto's model of social integration. Secondary data collected by the National Center for Education Statistics on 101,000 freshmen who attended 1,360 postsecondary institutions in 2003-04 and 2008-09 were used for this study. Logistic regression was used to test and compare two models. Logistic regression tested the relationship between the predictor variables of state need- and merit-based aid and degree completion. This study's results revealed that state merit-based aid had a greater predictive value than state need-based aid as enrollment factors of college completion among low-income young adults. This study contributes to positive social change by providing state policy makers with research results to evaluate and formulate state financial aid policies that will increase access to financial aid and college completion rates among low-income freshman students.

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