In this study, we used the High Potential Trait Indicator (HPTI), which was constructed to predict workplace behaviour and has good psychometric properties. For instance, each of the six factors has an alpha between .72 and .80, a good fit, convergent validity with the established NEO-PI-R, and predictive validity with management level ( MacRae & Furnham, 2020 ).

The HPTI was developed to measure personality at work, and has some overlap with the Big Five (Five Factor Model, FFM) on three traits ( Cuppello et al., 2023a, 2023b ) and includes three additional traits, shown to relate to success in a variety of jobs ( Teodorescu et al., 2017 ). The first overlapping trait is Conscientiousness, characterised by self-discipline, organisation, educational and business success and the ability to moderate one’s impulses ( Barrick et al., 2001 ). The second is Adjustment (low Neuroticism), characterised by emotional resilience to stressors, positive affect, and mood stability and regulation. The third is Curiosity (Openness), which is characterised by an interest in new ideas, experiences and situations. It involves new ways of completing tasks, new ideas, and an interest in colleagues with different opinions.

A number of papers have used the HPTI ( Cuppello et al., 2023a, 2023b ; Furnham & Treglown, 2018 ; Furnham & Impellizzeri, 2021 ; Treglown et al., 2020a, 2020b ). The psychometric properties of the measure have been reported ( MacRae & Furnham, 2020 ), of which the most relevant report is the study by Teodorescu et al. (2017) . Their results indicated that the HPTI personality traits relate to subjective and objective measures of success, with Conscientiousness being the strongest predictor.

In this study, we are interested in three sets of economic behaviour correlates: demography, ideology, and personality. We had three criterion variables: subjective ratings of wealth and financial literacy and the number of credit cards they possessed. The essential question was, which set of variables predicted the outcome variable, and how much variance could we account for?

From our review of the above literature, we predict that males more than females (H1); older more than younger (H2); graduates rather than non-graduates (H3); those with higher scores on Conscientiousness (H4), Ambiguity Acceptance (H5), Competitiveness (H6) and Curiosity (H7) would rate their wealth and financial literacy higher and have more credit cards.

Table 1 and Table 2 reports Pearson correlations, with means and standard deviations on the diagonal.

Table 1 indicates that sex and religious beliefs were largely unrelated to the three ratings, whereas the traits Risk Approach and Ambiguity Acceptance demonstrated stronger associations. Notably, Self-esteem emerged as one of the stronger correlates of the criterion variables, all of which, according to Cohen (1988) , were small effect sizes.

A series of regressions were then conducted with Personal Wealth, Financial Literacy, and Number of Credit Cards as dependent variables. A standard multiple linear regression was utilised for Personal Wealth, as it did not considerably violate the assumptions of linear regression ( Tabachnick & Fiddel, 2013 ). However, alternative regressions were used for Financial Literacy and Number of Credit Cards due to the nature of the responses for these questions.

Financial Literacy is a single-item question anchored at 1 (Not at all), to 9

Note. *p < 0.05, **p < 0.01, ***p < 0.001. 0 = Male, 1 = Female. 0 = Degree not obtained, 1 = Degree obtained.

Note. *p < 0.05, ** p < 0.01, *** p < 0.001. 0 = Male, 1 = Female. 0 = Degree not obtained, 1 = Degree obtained.

(Very), deeming the responses to be ordinal. The distribution of responses was also negatively skewed (skewness = −0.715, W = 0.919, p < 0.001, M = 6.91, SD = 1.45). Accordingly, an ordinal logistic regression was conducted using the proportional odds model ( Ananth & Kleinbaum, 1997 ). The analysis was performed in Jamovi ( The Jamovi Project, 2025 ), which utilizes the MASS package ( Ripley et al., 2023 ) in the statistical programme, R ( R Core Team, 2024 ).

The Number of Credit Cards responses is count data by nature, and therefore require a more suitable regression approach. Poisson and negative binomial regressions were considered, with the latter being preferred as the data exhibit overdispersion, which violates a key assumption of Poisson regression ( Fávero et al., 2021 ; Gardner et al., 1995 ). The distribution of reported credit cards was positively skewed and overdispersed (skewness = 1.763; W = 0.833, p < 0.001; M = 1.73, SD = 1.42). Consequently, a negative binomial regression was employed to examine the relationship between the number of credit cards and the independent variables. Multicollinearity was not a concern, as the highest variance inflation factor (VIF) observed was 2.259, well below the commonly used threshold of 5 ( O’Brien, 2007 ).

Table 3 shows that for the regression of personal wealth, in all, six variables were significant and accounted for around 13% of the variance. Individuals with higher levels of education, higher Self-esteem, higher Conscientiousness, more willingness to take risks, and lower curiosity, tended to rate their personal wealth higher. Interestingly, age was not significant, as it is expected that older individuals would accumulate more wealth over time.

Four variables were significant for the rating of financial literacy, which, in total, accounted for about 5% of the variance. More Conscientious and Ambiguity

Note *p < 0.05, **p < 0.01, ***p < 0.001, 1 = Female, 2 = Male, 1 = Degree not obtained, 2 = Degree obtained.

Tolerant people with higher Self-esteem, and tending to be politically conservative, rated their financial literacy more highly.

The regression onto the number of credit cards a person owned showed that older people, individuals who have obtained a degree, more Competitive, and those with higher Self-esteem, but less Conscientious people had more credit cards.

The results showed that Self-esteem and Conscientiousness were related to all three criterion measures. A few of the variables were not significant predictors in any of the regressions: sex, religious beliefs, and Adjustment. Overall, all three regressions accounted for between 5 and 12% of the variance.

The regression onto perceived wealth showed that degree status, political beliefs, Self-esteem, and three of the six personality traits were significant. It is well-accepted that people are not well-informed about the wealth of others and that this measure is essentially comparative and, thus, open to variability over time. Perhaps most surprising is that age is not associated with this estimate. As people become older, their wealth usually increases, but their comparative judgements may stay the same. Interestingly, as so frequently observed political beliefs were related to perceived wealth, showing that individuals who perceived themselves as being wealthy tended to be politically more conservative. Our results showed that Conscientiousness was related to self-perceived wealth. We know that this trait is most consistently and systematically related to success at work, which, in part, is rewarded monetarily ( Furnham, 2018 ). Equally, wise risk-taking is often rewarded financially. While we only have correlational data, given the findings on the stability of personality in adulthood, this data suggests that personality does effect wealth accumulation. A particularly shocking result was the negative relationship with Curiosity (Openness). This may reflect the “creative” nature of more open people, who are less interested in wealth accumulation than quality of life and “having fun”.

However, what is most clear is the role of Self-esteem. It is possible that Self-esteem is a part cause and consequence of a person’s wealth. Assuming more competent people on a range of skills have higher Self-esteem, it seems likely they would achieve better jobs and make better financial decisions and hence achieve greater wealth. Similarly, being financially successful would no doubt lead to an increase in Self-esteem. Another possible interpretation is that individuals with high Self-esteem tend to respond more positively on self-report surveys, either due to Self-enhancing tendencies ( Baumeister et al., 2003 ) or because of a favourable response style associated with high Self-esteem ( Ohide, 1979 ). Alternatively, they may genuinely believe they are better off—including in domains like personal wealth—regardless of their objective circumstances ( Taylor & Brown, 1988 ; Sedikides & Gregg, 2008 ).

Our results showed that more politically conservative, Conscientious, and Ambiguity-tolerant people who had higher Self-esteem believed that they were more financially literate. There is a sizable literature on the correlates of financial literacy, which indicates that Conscientiousness is a major predictor ( Fenton-O'Creevy & Furnham, 2020a ; von Stumm et al., 2013 ). It could be argued that an interest in financial affairs is related to seeking wealth accumulation, which is related to more conservative politics. It is fascinating that tolerance for ambiguity is related to Self-assessed financial literacy, which may be due to the uncertainty and randomness of many markets and financial affairs; one has to be able to tolerate this to pursue financial knowledge and, thence, literacy. However it no surprise that Self-esteem is related to beliefs about financial literacy, though once again it not clear how the process works: do people with high Self-esteem make more attempts to become financially literate; or does financial literacy boost Self-esteem? However it should be acknowledged that people might not be able to accurately estimate their degree of financial literacy and that the correlation reflects poor insight into personal skills and talents.

Finally, the correlates of credit card ownership showed that older people with a degree held more. Once again, Self-esteem was a correlate suggesting that those with more cards had higher Self-esteem though it is not clear as to the causal relationship. The personality results were particularly intriguing; less Conscientious and more Competitive people had more cards. Credit card ownership is related to many factors, which may change as a function of the decrease in cash. For some, credit card ownership and use could be related to careless and compulsive spending ( Khandelwal et al., 2022 ), while for others, credit cards might be used to signal power and success ( Furnham, 2015 ). It is noteworthy that Conscientious people had fewer cards while Competitive people had more. The former may be more selective in the cards to choose and use; in contrast, the latter may like to display their wealth by the number of cards they have.

Like all others, this study had limitations. We had a reasonably sized population, but they were essentially middle-aged professionals, which concomitantly restricted range. It would have been desirable to have actual objective economic data on each individual’s wealth, earnings, credit and debit card ownership, as well as a test measure of their actual financial literacy. Finally, many of our measures were based on single items, which may be less robust and reliable than multiple-item measures. However, a recent review noted that “most research published on single-item measures shows that they are often as valid and reliable as their multi-item counterparts” ( Allen et al., 2022 , p. 4).

The data may be requested from the first author.

This paper was not pre-registered with the journal.

The study involved secondary analysis of anonymised data, collected from a non-vulnerable population with informed consent that allowed the use of the data by third party researchers.