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What is a rich personality?

The prototypical personality profile of the rich is marked by higher Risk tolerance, Openness, Extraversion, and Conscientiousness, and lower Neuroticism.

nature.com - The personality traits of self-made and inherited millionaires - Nature

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The data used in this study met four central requirements to meaningfully address the questions of how and why rich individuals differ from the general population: (1) both samples use well-validated survey instruments and the same measures for the general population and the rich sample, (2) data on personality and wealth portfolios are collected at the individual level, (3) the number of rich people is substantially higher than in previous studies, and (4) the samples are population representative and come from surveys randomly drawn within their respective populations.

Data sources

The sample of rich individuals used in this study is largely comprised of a new top-wealth subsample (SOEP-P) in the German Socio-Economic Panel (SOEP). The SOEP measures not only personality but also wealth at the individual level; basically, all other surveys collect wealth data only at the household level. The SOEP-P, which was first surveyed in 2019 (Schröder et al., 2020), is thus unique in fulfilling the data requirements mentioned above. The SOEP study began in 1984 and now surveys about 15,000 households and about 30,000 individuals every year (Giesselmann et al., 2019; Goebel et al., 2019). The target population is Germany’s resident population. New samples have been added over time to compensate for panel attrition, to maintain cross-sectional representativeness in the presence of influx to the underlying target population, and to oversample subpopulations like the wealthy (Kroh et al., 2018). Direct comparisons between different subsamples are possible thanks to the use of identical questionnaires and data-preparation procedures in the SOEP. The SOEP scientific data infrastructure undertakes comprehensive measures to ensure data quality and consistency. Beyond the usual test routines to check data plausibility and consistency after data collection, the SOEP has put in place institutional safeguards to ensure data quality include monitoring mechanisms to verify the correct work of the interviewers, generation of user-friendly variables (including inter-temporal harmonization and statistical imputation), and external validations of SOEP statistics with external data sources (Schröder et al., 2020).

Population of interest

Our population of interest consists of adult individuals living in Germany. We distinguish these individuals according to whether or not they are rich, as measured by individual net wealth. In order to make the two groups sufficiently distinct from one another, we exclude individuals with individual net wealth levels between 800,000 and 1 million euros. Observations in this range of wealth are likely to contaminate salient differences between the general non-rich population and our sample of rich individuals. We label the individuals with lower individual wealth “non-rich” and those with higher wealth “rich”. The working sample contains 23,721 individuals. Of these, 1125 individuals have individual net wealth of at least 1 million euros, 190 of at least 5 million euros, and 61 of at least 10 million euros. The richest five respondents have net wealth between 100 and 131 million euros. Figure 1 shows the distribution of net wealth for the regular SOEP and SOEP-P samples, with the shaded area indicating the rich population (N = 1125), as well as the fraction of the relevant millionaire subpopulations: rich self-mades (millionaires for whom entrepreneurship and self-employment had the prime influence on their wealth, N = 517), and rich inheritors (N = 136, millionaires for whom gifts, inheritances, or marriage had the prime influence on their wealth). See Table S2 for percentiles of wealth for the combined sample and the rich sample. The data provide sufficient statistical power to analyse the personality traits of millionaires in Germany. Note that our data also overlap with the 2019 Manager Magazin “rich list” of the wealthiest 1000 individuals in Germany (according to expert estimates), who made up the top 0.00144 percent of the adult population in Germany in 2019 (Federal Statistical Office of Germany, n.d.). Last place (number 1000) in the Manager Magazin rich list is held by an individual with 90 million euros. The richest individual surveyed in our study comes in at number 821 in the Manager Magazin list. Note, however, that rich lists are prone to overestimating net wealth: as Raub et al. (2010) document, net wealth from inheritance tax records is on average about 50 percent of what is recorded in the Forbes 400 list. Fig. 1: Composition of the data. On the left is a kernel density plot of net wealth for SOEP and SOEP-P and on the right is the composition of the rich population with respect to both relevant subgroups of millionaires (inheritors and self-mades) as well as a remaining group of rich individuals with mixed or unspecified factors influencing their wealth (mixed/unspecified). Data based on SOEP v36 (10.5684/soep-core.v36eu). Full size image

Focal variables

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Our analyses require information on individual’s net wealth, personality traits (specifically the Big Five and risk-taking), and basic socio-demographic variables. An overview of all variables used in this study can be found in Table S3.

Individual net wealth

The SOEP survey includes a wealth module to collect data on owner-occupied housing, rental property, financial assets, building loan contracts, life and private pension insurance, tangible assets, vehicles, and privately owned businesses (market value). In case an asset is owned by multiple individuals such as spouses or business partners, respondents are asked to state how many shares they personally own. SOEP also collects information on individual liabilities: mortgages on owner-occupied housing, mortgages on rental property, consumer debt, and student loans. Individual net assets, used here to distinguish rich and non-rich individuals, is the sum of the eight asset components minus the four liability components. Measurement of wealth at the individual level is a special feature of the SOEP survey and essential for our analyses, since the use of household wealth would not take into account how many people in the household share the wealth in what proportions.

Personality

The Big Five personality traits are derived from SOEP’s short Big Five inventory (BFI-S), measuring each of the five traits with three items. Participants are asked to rate their agreement with statements starting with “I am …” on a scale from 1 (strongly disagree) to 7 (strongly agree). An example for the dimension of Conscientiousness would be “I am a thorough worker.” The BFI-S generally showed acceptable levels of: (1) internal consistency, (2) stability over a period of 18 months, (3) convergent validity in relation to the NEO-PI-R measuring the Big Five with 240 items and in relation to the BFI measuring the Big Five with 44 items, and (4) discriminant validity (Ackerman et al., 2016; Hahn et al., 2012). Evidence for the validity of this short version is provided by Gerlitz and Schupp (2005). A factor analysis clearly revealed the expected five-factor structure. Internal consistency was comparable to other short scales in which heterogeneous items are selected to maximize validity, ranging from 0.49 (Agreeableness) to 0.69 (Extraversion). For an overview of the correlation between the personality traits, see Table S4. We use risk-taking as an additional personality trait for several reasons. Risk-taking is an important explanatory variable for entrepreneurship (Cagetti and De Nardi, 2006, 2008; De Nardi and Fella, 2017) and an important factor in wealth creation (Quadrini, 1999), investing (Mata et al., 2018), and company performance (Sanders and Hambrick, 2007). SOEP respondents are asked to rate their willingness to take risks on a scale from 0 to 10, where 0 means “not at all willing to take risks” and 10 means “very willing to take risks.” A comparison of this self-rated risk measure with an alternative measure of risk-taking from an incentivized lottery experiment in the field shows that the self-rating predicts actual risk-taking behaviour very well (Dohmen et al., 2011), and the self-rated risk measure has even outperformed incentivized lottery experiments in predicting real-world risk-taking across different domains (Hertwig et al., 2019). Recently, Arslan et al. (2020), analysed the self-perceptions behind stated Risk tolerance. They showed that people recount diagnostic behaviours and experiences, focusing on voluntary, consequential acts and experiences when inferring their risk preference.

Socio-demographic variables

The SOEP collects a wide range of sociodemographic information. In this study we used gender (0 = female, 1 = male) as well as the self-created variables age category (1 = younger than 40, 2 = between 40 and 60, 3 = older than 60) and high education (1 = 12 or more years of schooling; 0 = else) as control variables for our analyses.

Group definitions

We subdivided the general and the rich population into “inheritors,” “self-mades,” and individuals who cannot be assigned to the two other groups, i.e., the “mixed/unspecified group.” The latter group served as a benchmark for the personalities of the two former groups, as it consists of individuals who can be considered a convex combination of inheritors and self-mades. For this grouping, we relied on a battery of questions that ask respondents about the factors that have reduced, not influenced, or increased the amount of wealth they currently hold as individuals. These factors are: (1) entrepreneurship or self-employment, (2) dependent employment, (3) earnings from financial transactions, (4) real estate, (5) gifts, (6) inheritances, (7) marriage, and (8) lottery winnings. Respondents rated each of these factors on an 11-point Likert scale from –5 (reduced assets significantly) to 5 (increased assets significantly). Inheritors fulfilled the following criteria: (1) They rated the importance of either gifts or inheritances or marriage in increasing their individual wealth higher than 3. (2) They rated the importance of entrepreneurship and self-employment in increasing their individual wealth 3 or lower. Self-mades fulfilled the following criteria: (1) They rated the importance of entrepreneurship and self-employment in increasing their individual wealth higher than 3. (2) They rated the importance of either gifts and inheritance and marriage in increasing their individual wealth 3 or lower.Footnote 1 The groups based on self-ratings stratify well across many objective measures. The Supplementary Materials (Tables S11 and S12) show that the self-made scored high on objective measures of self-made economic success (such as self-employment and business wealth) and low on measures of being born into wealth (such as inheritances and the ratio of capitalized inheritances to current net wealth), while for inheritors the inverse is true.Footnote 2 The choice of the cut-offs ensures selectivity of the group while securing a reasonable size of the group, as can be seen from Table 1. Note that the share of rich self-mades is large (45%), which is congruent with evidence in Scheuer and Slemrod (2020) for the United States. Means and standard deviations for several socio-demographic variables as well as the personality items for each group among the rich and non-rich are shown in Table S5. Figure S2 in the Supplementary Materials shows histograms for each of the factors split across the rich and non-rich, while Fig. S3 shows these histograms for self-mades and inheritors, and Table S6 shows rank correlations of the influence factors.

Table 1 Sample size overview. Full size table

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Construction of a prototypical personality profile of the rich

The construction of the prototypical personality profile of the rich regarding the Big Five and risk-taking was informed by previous research that found wealthy individuals to score higher on Extraversion, Conscientiousness, Openness, and Narcissism, as well as scoring lower on Neuroticism and Agreeableness (Leckelt et al., 2019). There also exists initial indirect evidence that risk-taking is related to wealth (Cass and Stiglitz, 1972; Iglesias et al., 2004; King, 1974; Paravisini et al., 2017) and household income (Barsky et al., 1997; Dohmen et al., 2011). Moreover, narcissism, one of the traits that is somewhat more pronounced in wealthy individuals is linked to increased risk-taking (Buyl et al., 2019; Wales et al., 2013). Finally, a substantial number of wealthy individuals own businesses (Leckelt et al., 2019; Smeets et al., 2015) and entrepreneurship has been linked to a personality profile consisting of high values “[…] in extraversion, conscientiousness, and openness” and low levels of “[…] agreeableness and neuroticism” (Obschonka et al., 2013, p. 107). Thus, the prototypical profile of rich individuals can reasonably be assumed to consist of (limiting on the personality characteristics assessed in the present study): the highest possible values in Extraversion, Openness, Conscientiousness, and risk-taking as well as the lowest possible values in Neuroticism and Agreeableness. Following previous studies that have successfully used a personality profile approach, linking personality profiles to entrepreneurial activity (Obschonka et al., 2013), to investigate personality types in adolescents (Asendorpf and van Aken, 1999; Robins et al., 1996), or person-environment-fit (Götz et al., 2018), we calculated a difference score to the prototypical profile of the rich for each person in the samples based on (Cronbach and Gleser, 1953) as follows:

$$mathop {sum}limits_{j = 1}^k {left( {x_{j1} - x_{j2}} ight)^2}$$

Subscript j indicates a specific personality trait and the indices 1 and 2 represent a prototypical and a person’s actual score on trait j, respectively. Thus, the larger this difference, the more dissimilar is a person’s personality profile from the prototypical profile of the rich.

nature.com - The personality traits of self-made and inherited millionaires - Nature

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