Grouping Individual Investment Preferences in Retirement Savings: A Cluster Analysis of a USS Members Risk Attitude Survey
Blake, D. ORCID: 0000-0002-2453-2090, Duffield, M., Tonks, I. , Haig, A., Blower, D. & MacPhee, L. (2020). Grouping Individual Investment Preferences in Retirement Savings: A Cluster Analysis of a USS Members Risk Attitude Survey (PI-2003). London, UK: Pensions Institute.
Abstract
Cluster analysis is used to identify homogeneous groups of members of USS in terms of risk attitudes. There are two distinct clusters of members in their 40s and 50s. One had previously ‘engaged’ with USS by making additional voluntary contributions. It typically had higher pay, longer tenure, less interest in ethical investing, lower risk capacity, a higher percentage of males, and a higher percentage of academics than members of the ‘disengaged’ cluster. Conditioning only on the attitude to risk responses, there are 18 clusters, with similar but not identical membership, depending on which clustering method is used. The differences in risk aversion across the 18 clusters could be explained largely by differences in the percentage of females and the percentage of couples. Risk aversion increases as the percentage of females in the cluster increases, while it reduces as the percentage of couples increases because of greater risk sharing within the household. Characteristics that other studies have found important determinants of risk attitudes, such as age, income and (pension) wealth, do not turn out to be as significant for USS members. Further, despite being on average more highly educated than the general population, USS members are marginally more risk averse than the general population, controlling for salary, although the difference is not significant.
Publication Type: | Monograph (Discussion Paper) |
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Publisher Keywords: | investment choices, cluster analysis, risk attitudes, risk capacity, defined contribution pension schemes |
Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HG Finance |
Departments: | Bayes Business School > Finance |
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