The Relative Importance of Personality, Financial Satisfaction, and Autonomy for Different Subjective Well-Being Facets

Abstract

Using a nationally representative sample (N = 507) from Singapore, this study examined whether personality, financial satisfaction, and autonomy were important to subjective well-being (SWB), and how the importance of these predictors varied across different SWB facets—life satisfaction, happiness, positive feelings, and negative feelings. The findings indicated that neuroticism, financial satisfaction, and autonomy, were important predictors of happiness. Personality was most important for affective well-being (i.e., positive and negative feelings), whereas financial satisfaction was most important for life satisfaction. Specifically, neuroticism accounted for substantial variance in positive and negative feelings, and was the strongest correlate among the Big Five traits. In contrast, financial satisfaction explained most of the variance in life satisfaction. This highlights that the importance of well-being predictors depended on the facet of well-being examined. The findings suggest that residents in an affluent nation like Singapore do not emphasize only postmaterialist values (e.g., autonomy) and disregard materialist concerns (e.g., financial satisfaction). Though certain SWB facets (positive and negative affect) are largely influenced by dispositional factors, other facets (life satisfaction and happiness) are closely related to factors (e.g., financial satisfaction, autonomy) that may be affected by social policies. Policymakers can thus target those aspects to enhance people’s SWB.

Keywords:

• Autonomy
• Big Five
• financial satisfaction
• personality
• subjective well-being

Disclosure Statement

The authors declare that they do not have any conflicts of interest that might be interpreted as influencing the research. This research was conducted in accordance with the APA ethical standards and institutional review board guidelines. Informed consent was obtained from all participants, and participants were debriefed.

Data Availability Statement

Data available on request from the authors. The data that support the findings of this study are not publicly available. Parts of the dataset may be available from the corresponding author [W, Ng], upon reasonable request.

Notes

1 Data from the Department of Statistics, Singapore, confirmed that the sample was representative of the Singaporean population. The resident population (i.e., Singapore citizens and permanent residents) in Singapore in 2015 (the year that this survey was conducted) comprised 50.9% females and 49.1% males. 59.4% of the residents were married, and 40.6% were not married (single/widowed/separated/divorced). The ethnic composition was 74.3% Chinese, 13.3% Malay, 9.1% Indian, and 3.2% Others. These percentages closely matched our sample demographics.

2 To ensure a broad measure that included both high and low activation emotions, the emotions assessed in this study were drawn from the PANAS, and other published emotion lists or affect circumplex (e.g., Diener, Smith, & Fujita, 1995; Scale of Positive and Negative Emotion Experience [SPANE]). This is because certain feelings (e.g., happy, contented) cannot be captured by items in the PANAS, which focus only on high arousal feelings. To avoid making the survey too lengthy, we selected only the items that were essential to cover both high and low arousal emotions, and the basic emotion categories (e.g., Diener et al., 1995). Our final selection consisted of 12 items (6 items each for positive and negative feelings). This is a briefer measure than the PANAS which consists of 20 items (10 items each for PA and NA).

3 The item assessing respect used the time frame of “previous day” because it was the same measure used in the GWP. In contrast, the items used to measure autonomy and social support utilized global indicators. This is because these same measures were used in other large-scale surveys (GWP: respect and social support; WVS: autonomy), which allows us to make comparisons with previous published findings.

4 The preliminary regressions with all the covariates showed the same patterns of results as the final analyses (without age and education).

5 Numerous studies using the GWP and WVS datasets had operationalized the well-being and psychological needs variables (e.g., respect, social support, autonomy, financial satisfaction, life satisfaction) using these single-item measures. The findings have been reported in published papers and shown to be consistent and robust (e.g., Delhey, 2010; Diener et al., 2010; Inglehart et al., 2008; Ng & Diener, 2014; Welzel & Inglehart, 2010).

Additional information

Funding

This study was funded by a grant from the Center for Applied Research, Singapore University of Social Sciences (Grant Number RF15SAS01).

This study was funded by a grant from the Center for Applied Research, Singapore University of Social Sciences (Grant Number RF15SAS01).

Notes on contributors

Weiting Ng

Weiting Ng is an associate professor in the School of Humanities & Behavioural Sciences, Singapore University of Social Sciences. She studies how various facets of well-being relate differentially to factors such as income and psychological needs, and how the impact of well-being predictors varies across countries.

Wui Sing Russell Kua

Wui Sing Russell Kua has just completed his candidature in Master of Applied Research in Social Sciences, at the Singapore University of Social Sciences. He has a Master in Community Leadership and Social Development, and had previously worked on social programmes related to family well-being. His research deals with social capital, well-being, and social inequality.

Soon-Hock Kang

Soon-Hock Kang is an associate professor in the School of Humanities & Behavioural Sciences, Singapore University of Social Sciences. His current research focus covers the areas of employability, health and well-being of the older adult population in Singapore.