Students' university choice

Abstract

This thesis addresses UK students’ university choice using discrete choice methods and micro-data obtained from Higher Education Statistical Agency for graduates between 2006 and 2010. The thesis consists of three chapters with each addressing a different aspect of students’ choice. The studies are intended to provide policy-makers and other decision-makers with valuable information that will help them to implement strategies and policies for better higher education. Some work in the literature has been dedicated to students’ university choice. This thesis explores this body of work and builds on it, extends it and improves what is previously known in the literature. The aim of the first chapter is to investigate what affects students’ university choice. It contributes to the literature by establishing the best method to do so. Two models are used: the standard conditional logit and conditional logit with, what is called in this paper, alternative specific constants. Conditional logit with alternative specific constants improves on conditional logit twofold: it deals with unobserved university characteristics and improves the model fit. The results show that the probability of attending a university decreases with an increase in tuition fees and distance between students’ home and the university, and decreases in students’ socio-economic status. The second chapter further investigates the importance of distance on students’ university choice and it contributes to the literature by calculating the willingness to pay of students for distance to university. The chosen models are estimated for different socio-economic group of students separately. This methodology allows for meaningful comparison between socio-economic groups and produces more reliable estimates due to the fact that it accommodates for different unobserved characteristics of universities for different groups of students. The results show that students with the highest socio-economic status are not affected or have a positive utility of distance. The willingness to pay of other socio-economic groups are mixed and depend on the university characteristics used in the model. The third chapter focuses on students’ attitudes towards costs and benefits of university degree by calculating the discount rate of future income using marginal utility of graduate income and tuition fees. In addition, the chapter shows how use of consideration sets of universities for each student improves the model fit. The results show that students have a normal discount rate around 1% without consideration sets. The discount rate becomes negative in all models apart from one, when consideration sets are used.