Financial well-being as a research topic has drawn interests not only for financial planners, economists, sociologists, and policy makers, but also for psychologists. The different disciplines emphasise different factors that lead to financial status in adulthood. This study aims to investigate a set of socio-demographic factors (parental social status, education and occupation) as well as psychological factors (intelligence, self-esteem, locus of control, malaise) that influence adult financial well-being indicated by weekly net income, house ownership status, and living space (number of rooms). The study had a large, nationally representative sample in the UK, and had a particular focus on psychological factors (intelligence, locus of control, malaise) and the extent to which they independently predict adult financial well-being.
Previous studies have established findings on the links between family background, childhood intelligence and later educational and occupational outcomes [1
], between childhood cognitive development and adulthood socioeconomic status and mental health [13
] using a large American sample showed that each IQ test point raises income by between $
234 and $
616 per year after holding numerous other factors constant.
However, few studies have examined the effects of locus of control, intelligence, and mental health on adult financial well-being. Many studies have demonstrated the predictive power of locus of control with respect to many life outcome variables including health and financial well-being [15
] showed locus of control, measured at age 10 years predicted social class at age 30 years. Locus of control has been linked to attitudes and behaviour with respect to money [18
]. Those with internal locus of control tend to be more strongly motivated to exercise plan and take responsibility for their actions.
There is also a literature on personality and occupational and financial success which suggests particular personality variables, namely Conscientiousness positively and Neuroticism negatively are related to career success [20
]. In this study we examine the effect of early adult Malaise (a strong correlate of Neuroticism) on mid adult financial success. Longitudinal studies have shown that early indicators of instability/malaise are negatively linked to educational and occupational outcomes [17
]. We also examined self-esteem measured at aged 10 which has been shown to be related to a number of variables like external locus of control and educational attainment.
The current study has three strengths: it examined a set of inter-correlated social and psychological factors together determining to what extent each factor influenced the outcome variable; it used a large, nationally representative longitudinal dataset; and it used a set of financial well-being measures (earnings, house ownership status, living space), thus covering more than one components of the concept of financial well-being.
Gender pay gap is well documented [22
], though explanations vary. Women in almost every social sectors have less earnings than men. However, the discrepancy of pay between men and women seems to decrease in some developed countries. For example, in the UK, when full-time work is taken in isolation, women earn 10 per cent less than men in 2013. It means the gap between men and women’s full-time earnings has now almost halved since records began in 1997 [22
There have been numerous studies on the possible causes of the established gender difference in pay which include gender differences in education, hours worked, occupational prestige, employment sector and years in the labour market [23
]. Semykina and Linz (2007) [26
] found gender differences in personality traits which explained 8% of the gender wage gap. They also found women’s earnings are strongly affected by personality while the effect of personality on men’s earnings was small and often not significant. Ashby and Schoon (2010) [27
] found teenage career aspirations and ambition predicted adult social status and earnings but that the effect was slightly different between the sexes. This study considers the effects of cognitive and non-cognitive individual difference factors separately for males and females. It uses an archived data set that has been used to explore how early childhood factors predict socioeconomic outcomes in adulthood.
This study explored the effects of a set of socio-economic and psychological factors in childhood and adulthood on adult financial well-being, using structural equation modelling and drawing on data collected from a large representative population sample in the UK. Its primary aim was to examine the relative power of individual difference factors measured before adolescence particularly intelligence, over social class, in predicting adult financial success. Specifically it was hypothesised that (H1) Parental social status would be a significant predictors of adult financial well-being; (H2) Childhood intelligence would be a significant predictor of adult financial well-being; (H3) Locus of control would be a significant predictor of adult financial well-being; (H4) Malaise would be a significant predictor of the outcome variable; (H5) Educational achievement and occupational prestige would be significant predictors of the outcome variable.
The results of the current study showed that all of the independent variables measures at different points in time (gender, parental social class and education, intelligence, self-esteem, locus of control, malaise, educational level and occupational status) were all significantly correlated with the financial well-being measure at the item and total score level. Although there were significant differences in total income between the sexes, the pattern of results were strikingly similar.
The results from all the analyses show the extent to which two inter-correlated factors, namely childhood intelligence and parental social class predict financial well-being in mid-life. Whilst this is neither a surprising nor new finding what is interesting is the amount of variance accounted for by these two factors.
and Figure 2
show the results of exploring the possibility of moderator variables. They also show that the direct effect of intelligence is stronger than that of parental social class in predicting adult financial well-being. There are four important points resulting from that analysis. First, that almost a third of the variance could be accounted for by these four factors alone, all of which were measured at least 20 years before mid-life adult well-being. Second, that the pattern for men and women was almost identical. Third, that intelligence and social class both influence self-esteem, but that it is only intelligence that influences locus of control which is directly related to the outcome variable. Fourth, that the strongest relation was between intelligence and locus of control, suggesting that more intelligent children (aged 10) have a more instrumentalist, internal locus of control at age 16 which is a significant predictor of educational success.
Sociologists tend to focus on social class, educational and occupational correlates of financial well-being arguing, as our data indicated, that social class affects educational outcomes and then occupational choices which have a direct influence on financial variables of different kinds. Psychologists on the other hand tend to focus on individual difference correlates and determinants of wealth, showing that personality and intelligence influence educational outcomes which in turn influences financial well-being. There is agreement that education, occupation and financial well-being are highly inter-correlated but more disagreement on the determinants of those variables.
The final results shown in Figure 3
and Figure 4
are interesting for many reasons. The results show that both social class and intelligence predict education which predicts financial well-being. First, the seven variables account for around half the variance for both males and females. Next, for both sexes it is the moderating effect of education that is stronger than parental social class on financial well-being though both are related. Third, for females the role of parental social class is much reduced, compared to males and its effect on financial well-being is moderated by self-esteem, locus of control and education. Fourth, the effect of malaise was weak but in the predicted direction.
It is not difficult to construct a causal theory from these results. High social class parents have higher intelligence which their children partly inherit. Parental socialisation along with school success leads these children to have high self-esteem, an internal locus of control, and a reduced sense of malaise. Intelligence is strongly related to educational outcomes which opens greater and better job opportunities both of which lead to higher salaries.
All studies have their limitations and this is no exception. The sample with complete data had a slight under-representation of lower/manual occupational classes which may provide a small bias in these results. It would have been desirable to have more measures of financial well-being, as well as other psychological (i.e., personality traits) measures to get a more nuanced result. Further, the loadings of the latent outcome variables were relatively low. Therefore results of the current study are not conclusive. Future studies with better psychological properties or more sophisticated identifications of different type of indicators (effect/causal/composite indicators, etc.) and treatment [39
] are required to confirm or refute the findings.
The present study confirms the strong and direct effects of parental social class and intelligence on education, occupational and financial well-being in middle age. Current occupation is the strongest predictor of financial well-being, followed by educational achievement, and childhood intelligence is the best predictor of educational attainment. There is a continuous and persistent effect of parental social class on adult financial well-being yet intelligence and locus of control shared a substantial amount of the variance.