Money matters - a comparative study of students' financial literacy and attitudes to debt in the UK, US and New Zealand
Project start: September 2013
Project end: December 2014
Project team: Dr Neil Harrison, Steve Agnew (University of Canterbury, New Zealand) and Dr Joyce Serido (University of Arizona, United States)
Funder: British Academy / Leverhulme Trust
The indebtedness of higher education students in the UK has become ubiquitous since the introduction of student loans in the early 1990s. However, this is not an isolated situation and most OECD countries now have systems that require many or most students to borrow to meet the costs of their education. Each is unique in history, scale, criteria and the meaning attached to debt by students and wider society.
The Money Matters project in an international comparative study contextualising the UK with the United States (US) and New Zealand (NZ), and involving data from around 600 individuals. The three systems of student finance vary in key ways, providing students with a different experience of indebtedness. It will use quantitative techniques to examine younger students within these systems, probing the ways in which the prevailing system impacts on their attitudes, understanding and behaviours. It uses a blend of theoretical concepts from the fields of economics, psychology and sociology, including financial literacy, personality theory and social class.
Specifically, the Money Matters project will address the following research questions:
- RQ1: To what extent are
students’ attitudes to debt explained by personality, financial
literacy and demographic variables?
- RQ2: To
what extent does national context play a role in determining
attitudes to debt, either directly or mediated by personality,
financial literacy and demographic variables?
- RQ3: If national context is important, what components of the student finance systems or wider societal values might be relevant?
Data have been collected from around 600 full-time first year undergraduates in social science and business from across the three countries via an online questionnaire. These data are being analysed through a mixture of statistical approaches, including factor analysis, structural equation modelling, regression analysis and ANOVA.