An Examination of Demographic Differences in Obtaining Investment and Financial Planning Information

Financial literacy and financial education are important components of modern life. The importance of financial literacy is increasing for financial consumers because of the weakening of both government and employer-based retirement systems. Unfortunately, empirical research shows that financial consumers are not fully informed and are not able to make proper choices even when appropriate information is available. More research is needed as to how financial consumers obtain investment and financial planning information. A primary data study was conducted to understand the differences between the demographic categories of gender, age, education-level, and income-level with the means of obtaining investment and financial planning information. In this research study, which selected a population from the LinkedIn platform, statistical differences between gender, age, education-level, and income-level were confirmed. These differences helped to confirm prior research in this field of study. Practical opportunities for commercial outreach to specific populations became evident through this type of research. Providers of investment and financial planning information can access their targeted audience more effectively by understanding the demographic profile of the audience, as well as the propensity of the demographic profile of the audience to respond. As this type of research is relatively easy to construct and administer, commercial outreach for providers of investment and financial planning information can be conducted in a cost-efficient and effective manner.

Using a stochastic economic scenario generator to analyse uncertain superannuation and retirement outcomes

The retirement systems in many developed countries have been increasingly moving from defined benefit towards defined contribution system. In defined contribution systems, financial and longevity risks are shifted from pension providers to retirees. In this paper, we use a probabilistic approach to analyse the uncertainty associated with superannuation accumulation and decumulation. We apply an economic scenario generator called the Simulation of Uncertainty for Pension Analysis (SUPA) model to project uncertain future financial and economic variables. This multi-factor stochastic investment model, based on the Monte Carlo method, allows us to obtain the probability distribution of possible outcomes regarding the superannuation accumulation and decumulation phases, such as relevant percentiles. We present two examples to demonstrate the implementation of the SUPA model for the uncertainties during both phases under the current superannuation and Age Pension policy, and test two superannuation policy reforms suggested by the Grattan Institute.

BEST RETIREMENT SYSTEMS IN FOREIGN COUNTRIES

The structures and characteristics of the best retirement systems of foreign countries are considered.

Learning in late career stages in Europe – gendered effects of retirement policies

Institutional contexts shape learning participation throughout the course of life. Combining micro-data on adult education from 26 European countries with country-level indicators on retirement systems in multi-level logistic regression models, the focus is on analysis of participation in non-formal learning among people aged 50–64 and its interactions with retirement policies. The analysis makes use of the largest sample of European countries used so far for exploring the issue. For the first time, gender differences in retirement policies are considered. The results imply that for all women and highly educated men, participation in non-formal training is higher when retirement age in the country is set at 65 years or higher. However, men with less education do not profit from a higher retirement age because their training participation remains unaffected by retirement policies. In the current analysis, training participation in older age groups remains unaffected by the generosity of pensions. The results outline gender differences in learning participation in older age groups. Also, after the age of 50, men with a low education are at particular risk of labour market exclusion and unemployment because the retirement age in European countries keeps rising and technological advancements make additional demands on workers’ skills.