Beyond income: Exploring the role of household wealth for subjective well-being in Germany

Jantsch, Antje; Le Blanc, Julia; Schmidt, Tobias Article — Published Version Beyond income: Exploring the role of household wealth for subjective well-being in Germany Journal of Happiness Studies Provided in Cooperation with: Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale) Suggested Citation: Jantsch, Antje; Le Blanc, Julia; Schmidt, Tobias (2024) : Beyond income: Exploring the role of household wealth for subjective well-being in Germany, Journal of Happiness Studies, ISSN 1573-7780, Springer, Dordrecht [u.a.], Vol. 25, Iss. 7, https://doi.org/10.1007/s10902-024-00811-1 , https://link.springer.com/article/10.1007/s10902-024-00811-1 This Version is available at: https://hdl.handle.net/10419/303024 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0 Vol.:(0123456789) Journal of Happiness Studies (2024) 25:101 https://doi.org/10.1007/s10902-024-00811-1 RESEARCH PAPER Beyond Income: Exploring theRole ofHousehold Wealth forSubjective Well‑Being inGermany AntjeJantsch1 · JuliaLeBlanc2· TobiasSchmidt3 Accepted: 3 September 2024 © The Author(s) 2024 Abstract An individual’s financial situation positively impacts her subjective well-being (SWB) according to the literature. However, most existing studies focus solely on income, neglecting other aspects of an individual’s financial situation such as wealth. In this paper, we empirically examine the relationship between SWB, income, household wealth, and its components. Additionally, we explore the significance of one’s wealth relative to others’ for SWB. Our contribution expands the limited literature on absolute and relative wealth and SWB by utilizing unique microdata from a German wealth survey, the German Panel on Household Finances (PHF). Our findings indicate that both assets and debts, alongside income, are associated with an individual’s SWB. In particular, a similar relative increase in financial assets is associated with a greater increase in SWB than the same percentage increase in real assets, and SWB decreases as the level of unsecured debt increases. Furthermore, individuals tend to experience decreased SWB when comparing themselves to others with more assets or less debt. Interestingly, we observe divergent effects of relative wealth on SWB among younger and older individuals. These results underscore the significance of considering wealth, in addition to income, when analyzing determinants of SWB. Keywords Relative wealth· Debt· Assets· Subjective well-being· Relative deprivation· Tunnel effect JEL Classification I31· D19· D31 Disclaimer: The views expressed are those of the authors and do not necessarily reflect the views of the Deutsche Bundesbank or its staff. * Antje Jantsch [email protected] 1 Leibniz Institute ofAgricultural Development inTransition Economies (IAMO), Theodor-Lieser-Str. 2, 06120Halle(Saale), Germany 2 Joint Research Centre oftheEuropean Commission, Ispra, Italy 3 Deutsche Bundesbank, Frankfurt, Germany A.Jantsch et al. 101 Page 2 of 33 1 Introduction Whether money can buy happiness is a question addressed by several authors in empirical studies on subjective well-being, SWB (see, e.g. Diener & Biswas-Diener, 2002; Headey etal., 2004; Kahneman & Deaton, 2010; Killingsworth etal., 2023). A common finding of most of these studies is that an individual’s financial situation has a positive impact on their SWB.1 Most studies focus on only one aspect of an individual’s financial situation, i.e., income (Weinzierl, 2005). The link between SWB and wealth (components) has mostly been neglected in the existing literature, not least because of a lack of suitable microdata on households’ wealth. Most of the studies, which include wealth, are limited either to one measure of total net wealth or to a single wealth component, such as homeownership or savings.2 Relying exclusively on income and ignoring wealth may lead to wrong conclusions regarding the relationship between SWB and an individual’s financial situation (Clark etal., 2008). Classic microeconomic theory can be used to explain why SWB should be influenced by wealth and debt holdings: an individual derives utility from consuming goods, which can be purchased using current income, saved or accumulated income (wealth), or new debt. Thus, higher levels of income and wealth should lead—through increased consumption opportunities—to higher utility or SWB levels. Apart from providing consumption opportunities, wealth has some additional features making it prone to positively influence SWB: it can be used to smooth consumption over an individual’s life cycle, it provides security against income shocks, it serves as collateral for debt, and it generates income itself. Given these functions of wealth, it is not surprising that several recent studies have found a positive relationship between SWB and wealth holdings (for example, Brown & Gray, 2016; D’Ambrosio etal., 2020; Foye etal., 2018; Hagerty & Veenhoven, 2003; Headey & Wooden, 2004; Office for National Statistics, 2015). Going beyond the classic absolute utility theory that focuses on the levels of income, wealth or consumption, the levels of these measures relative to those of others also seem to affect SWB according to relative utility theory (Kuhn etal., 2011; Pollak, 1976). Here again, the empirical studies have mainly focused on income.3,4 Only recently, some studies confirmed the relevance of interpersonal comparisons based on wealth for SWB (see e.g., Brown & Gray, 2016; D’Ambrosio etal., 2020); however, the direction of the effect is unclear. On the one hand, wealthy people may cause negative externalities (Frank, 1989; Layard, 1980) because they make their peers feel relatively deprived (Runciman, 1966). 1 In this paper, we focus mainly on the correlation between income and wealth and subjective well-being through the lens of economics. Related disciplines go beyond the economic discussion on income and wealth effects and study psychological, unemployment or social class outcomes and their impact on life satisfaction (see e.g. Firebaugh & Schroeder, 2009; Prechsl & Wolbring, 2023; Eberl etal., 2023; Kaiser & Tinh, 2021). 2 See Jantsch and Veenhoven (2019) for a comprehensive review. 3 Social comparisons have long been known to be relevant for well-being, as shown for example by Clark (2003) regarding employment status and Piper (2015) regarding education. 4 See Killingsworth etal (2023) for a recent discussion in the psychology literature on the effects of social comparisons and income on subjective well-being. This research indicates that while happiness tends to increase with income, the relationship is not linear for everyone. The findings suggest that emotional wellbeing rises with income up to a certain point, after which additional income does not significantly enhance happiness. This phenomenon is often referred to as "income satiation," where individuals experience diminishing returns on happiness as their income increases beyond a certain threshold (around75,000 to 90,000 US dollar). Beyond Income: Exploring theRole ofHousehold Wealth for… Page 3 of 33 101 On the other hand, wealthy people may cause positive externalities because their wealth and income levels serve as information for their peers’ potential income and wealth in the future. The prospect of reaching these income and wealth levels in the future may positively affect SWB now. This information effect is also called tunnel effect (Hirschman & Rothschild, 1973). We contribute to the literature by empricially analyzing the link between SWB and different types of households’ wealth as well as debt components. Using panel microdata on household wealth in Germany from the Panel on Household Finances (PHF) 2010 and 2014, we first consider wealth and its different components, such as real assets, financial assets, secured and unsecured debt, in addition to income, and investigate how these are associated with our measure of SWB, i.e., life satisfaction. Second, we discuss whether considering wealth alters the relationship between SWB and income. Third, we investigate the importance of one’s own wealth relative to the wealth of other households for SWB. Specifically, we analyze whether and how the wealth of an individual’s reference group matters for SWB. Our comprehensive empirical analysis of various types of financial assets and their relationship with subjective well-being (SWB) shows that wealth (and its different components) and debt indeed play a role for the SWB of an individual, in addition to income. Financial assets play a significant role regarding the positive effect of total assets on life satisfaction, while the evidence on real asssets is less clear. Analyzing different types of debt, we find that unsecured debt, typically associated with non-durable consumption, has the most pronounced negative association with life satisfaction. The ’burden’ of servicing unsecured debt appears to outweigh the average increase in life satisfaction derived from consumption financed by such debt. These insights underscore the importance of considering specific components within wealth and debt when exploring their associations with individual life satisfaction. Not only the absolute levels of wealth and debt seem to matter, but also wealth and debt levels in comparison to those of the reference group While we find a negative correlation between holding less assets compared to the peer group on SWB for younger inividuals, the SWB of older people seems to increase with the raising assets of their reference group, suggesting a tunnel effect. Notably, reference debt is positively associated with life satisfaction for both age groups, with a stronger association observed among younger individuals. In summary, we show that a broader concept, going beyond income, is important when analysing the relationship between SWB and the financial situation of a household or individual. This paper is structured as follows. In the next section, we review the literature on life satisfaction, income, and wealth. The data set and some descriptive statistics are presented in section three. Our methodology is described in section four, and section five contains the results. Conclusions are drawn in section six. A.Jantsch et al. 101 Page 4 of 33 2 Literature Review: Subjective Well‑Being, Wealth andSocial Comparisons 2.1 Empirical Evidence onSWB and(Relative) Wealth The empirical literature on wealth and SWB is relatively scarce. However, there have been several contributions utilizing Australian survey data. Headey and Wooden (2004), for example, estimate the combined effects of disposable income and net wealth on SWB using cross-sectional data from the Household, Income and Labour Dynamics Survey in Australia (HILDA). The results indicate that income and net wealth promote SWB and relieve ill-being almost in the same way. In another study, Headey etal. (2004) empirically investigate the combined effects of net wealth, disposable income, and consumption on overall life satisfaction as an indicator of SWB. Using data from five national household panels (Australia, Britain, Germany, Hungary, and the Netherlands), they find a stronger correlation between life satisfaction and net wealth compared to the correlation between life satisfaction and income. Furthermore, it has been found that the relationship between SWB and net wealth is relatively weak in wealthy Western societies compared to their non-Western counterparts (Diener etal., 1999; Howell etal., 2006; Schyns, 2002). Using data from the Survey of Health, Aging, and Retirement in Europe (SHARE), Hochman and Skopek (2013) compare the effects of wealth on SWB across three welfare-state regimes: conservative (Germany), liberal (Israel), and social-democratic (Sweden). Their results indicate that income and wealth explain a greater part of the variance in SWB when taken together and that the welfare state has an important impact on the wealth-SWB relation. Two studies by the Office for National Statistics (2015) and Brown and Gray (2016) extend the analysis of the effects of wealth on SWB by distinguishing between assets and debt. They show that assets and debts can have opposite effects on SWB and that different types of assets in households’ portfolios can have differential effects. Empirical evidence, for example from the housing literature, suggests that homeowners are, on average, more satisfied with their lives (Zumbro, 2014) and have a better mental health status (Manturuk, 2012) than renters. In contrast, a study published by the British Office for National Statistics (2015) shows that property ownership (and private pension wealth) is not statistically significantly related to life satisfaction. Instead, they find a positive relationship between net financial wealth and life satisfaction. D’Ambrosio etal. (2020) show a positive effect of net real estate, financial and business assets on life satisfaction in Germany. Regarding different types of debt, Brown, Taylor, and Wheatley Price (2005) explore the role of unsecured and secured debt for psychological well-being. Using the British Household Panel Survey (BHPS), they find that unsecured—opposed to secured debt— has a detrimental effect on psychological well-being. One possible reason for this negative effect could be that the additional “pleasure” of goods paid for by credit card, for example, is weaker and of shorter duration than the “pain” experienced when in debt (Jantsch & Veenhoven, 2019). According to Tay etal. (2017), secured debt, such as mortgage debt, does not necessarily lower SWB. Hochman etal. (2019) and Müller etal. (2021) study the role of debt in shaping the negative relationship between negative life events and general life satisfaction and overall find that debt does not change the relationship between experiencing a negative life event and general life satisfaction. Beyond Income: Exploring theRole ofHousehold Wealth for… Page 5 of 33 101 2.2 SWB andSocial Comparisons Richard Easterlin uses data from repeated surveys carried out in the United States to compare self-reported happiness of U.S. citizens over time (Easterlin, 1974). He finds no associated rise in reported happiness even though the average levels of U.S. incomes had risen remarkably over time—the Easterlin-Paradox (see also Easterlin, 1995, p.35).5 Easterlin’s findings raise the question of whether the assumption that greater levels of income lead to greater utility is adequate. Indeed, the Easterlin-Paradox has been mainly explained by social comparison; i.e., people compare their current income to the incomes of their peer or reference groups (Clark etal., 2008). Social comparisons typically involve comparing one’s consumption opportunities with that of a reference group. James Duesenberry (1949, Chapter2) notes, for example, that individuals frequently prioritize maintaining or enhancing their relative social standing over solely pursuing absolute gains in income. There are two types: upward comparisons and downward comparisons (Wheeler, 1991) and some studies show asymmetrical effects, with upward comparisons having a greater negative impact on SWB (Ferrer-i-Carbonell, 2005; Holländer, 2001; Vendrik & Woltjer, 2007). Yet, there is evidence that positive feelings from downward comparisons dominate negative feelings from upward ones (McBride, 2001). Regardless of the direction, social comparisons affect SWB (cf. Smith, 2000, p. 175 for a comprehensive literature overview). Positive effects can be attributed to the (I) tunnel effect, where upward comparisons generate hope and optimism for future consumption opportunities. The phenomenon was first studied by Hirschman and Rothschild (1973), who assumed that people perceive their comparatively low income as only temporary and, at the same time, use others’ higher incomes as information regarding their own (potential) future income. In some cases, this positive effect of an increase in peers’ income may dominate the negative effect on SWB from a relatively worse position in the income distribution (Senik, 2004, 2101). Additionally, downward comparisons create a sense of pride and relief as individuals realize they are better off or not as worse off as others. This (II) relative gratification effect refers to the positive feelings individuals experience when they perceive themselves as doing relatively better compared to others (Grofman & Muller, 1973; Guimond & Dambrun, 2002; Leach etal., 2002; Jantsch, 2020, 33). With regard to the negative effects of social comparisons, Easterlin (1995, 35) argues that a respective increase in the income of others offsets the positive effect of an increase in own income on SWB. This negative effect is also known as the (III) relative deprivation effect, leading to envy and resentment when the individual feels worse off (Runciman, 1966). This literature indicates that individuals take their own objective status and that of their peers into account when assessing their level of SWB (Easterlin, 1995, 36).6 Thus, for a given income, a higher average income of others implies a lower position in the income distribution. This means that an individual may end up relatively worse-off compared to 5 Clark, Frijters, and Shields (2008) echo this finding for the United States using data from the General Social Survey (GSS) over the period 1973–2004. A similar pattern has been observed for Japan where incomes of Japanese citizens rose substantially between 1958 and 1987 (by a factor of five)—the average level of happiness remained constant (Di Tella & MacCulloch, 2006, p. 26). 6 Some recent literature (for example Hagerty & Veenhoven, 2003) contests Easterlin’s view on the basis of new and longer time series data on SWB and claims that absolute levels of income and wealth increase SWB and find little evidence for social comparisons in the U.S. and across nations. A.Jantsch et al. 101 Page 6 of 33 the rest of society even if the level of her own disposable income has not changed. Downward comparisons, on the other hand, can cause (IV) fear of social decline, where individuals worry about being as worse off as others in the future, using others’ performance as an indicator of their own future performance (Jantsch, 2020, 33). Effects on SWB resulting from downward and upward comparisons are summarized in Table1. To date, there is a large body of empirical evidence in the economics, psychological and social science literature that points to the importance of relative income rather than absolute income for SWB (see, for example, Clark & Oswald, 1996; Senik, 2004; Ferrer-iCarbonell, 2005; Luttmer, 2005; Wunder, 2009; Layard etal., 2010). As already mentioned, an increase in reference group income is not necessarily associated with lower levels of SWB. Instead, empirical evidence suggests that comparisons with the respective reference group that is relatively better off could also have a positive effect on SWB (Firebaugh & Schroeder, 2009; FitzRoy etal., 2014; Knies, 2012; Senik, 2004, 2008). For example, Firebaugh and Schroeder (2009) find that the relative income hypothesis does not hold at the neighborhood level. Net of the effects of their own income, Americans tend to be happier when their nearby neighbors are rich, but at the same time when their income is higher than thatthe one of more distant neighbors. In other words, the overall effect of residential income on individual happiness reverses from positive to negative as geographic scaleincreases. Reference effects can also go beyond income. Looking at social class and social mobility, Kaiser and Trinh (2021) find thatone’s own social mobility generally improves life satisfaction while higher reference mobility leads to a decrease in life satisfaction. FitzRoy etal. (2014) study relative income effects over the life cycle and show that the negative effect of income comparisons dominates later in life, while the positive effect appears to be more important in early life. Brown etal. (2016) confirm these results by analysing the relationship between SWB and relative wealth using HILDA data. In their recently published study, D’Ambrosio etal. (2020) show a positive effect on individual’s life satisfaction and permanent wealth of the reference group using data from the German Socio-Economic Panel. Some recent studies analyse the relationship between relative wealth and life satisfaction for some selected types of wealth. Foye etal. (2018) argue that home ownership is a positional good and show empirically for the UK that the life satisfaction of homeowners decreases if the homeownership rate of the reference group increases. Odermatt and Stutzer (2022) find that homebuyers systematically overestimate their future life satisfaction just before as well as just after having relocated to their acquired dwelling. Brown etal. (2017) use data from the US to examine the importance of the relative rank within a social comparison group for life satisfaction. Among other indicators, they look at mortgage debt and financial assets. They show that the relative position in the distribution and not the absolute level of mortgage debt and financial asset holdings affect life satisfaction. 3 Data andDescriptive Statistics 3.1 Data: The Panel onHousehold Finances For our analysis we use data from the 2010 and 2014 waves of the “Panel on Household Finances” (PHF). The survey is based on a random stratified sample of private households Beyond Income: Exploring theRole ofHousehold Wealth for… Page 7 of 33 101 in Germany, with oversampling of wealthy areas.7 The PHF net samples comprised 3565 households in 2010 and 4661 households in 2014. To account for attrition and to ensure cross-sectional representativeness, a refresher sample was drawn for the 2014 survey. Attrition rates were low for a survey with a three-year frequency. About 68% of the households in the 2010 wave also participated in the 2014 wave. The survey thus has a large panel component, which we use in our analysis. More than two thousand households (2191 incl. 40 split off households) participated in both 2010 and 2014. The survey is well suited for our analysis as it contains detailed information on monthly household income and household wealth. It provides information on real assets (properties, self-employed businesses, vehicles, and valuables) and financial assets (current accounts, savings accounts, stocks, bonds and other securities, pension contracts, managed accounts, non-self-employed business wealth) as well as liabilities (mortgages/secured debt, consumer loans, private loans, overdue bills). To deal with missing values, the wealth and income variables of the PHF are multiply imputed using Rubin’s (1987) method.8 Except for gross income and pension assets, all the financial information is collected at the household level. In our analysis, we use total assets calculated as the sum of all real and financial assets as well as total debt, the amount of outstanding secured debt and unsecured debt. Net income is taken from a single question on total monthly net household income. The scientific use file contains paradata from the sampling stage, i.e., the stratification of the sample by wealth. Municipalities with less than 100,000 inhabitants were assigned to two strata, labelled “wealthy small municipality” and “other small municipality”, based on the share of taxpayers with high income. In large cities, wealthy street sections were identified based on micro-geographic characteristics, such as housing structure. This information allows us to investigate whether the relationship between life satisfaction and income or wealth is affected by the “wealth” in the area the person lives in.9 We use life satisfaction as an indicator of SWB. It is taken from a question using a classic 11-point Likert scale: “In general, how satisfied are you currently with your life as a whole?” which respondents answer by ticking one option on a list running from 0 “completely dissatisfied with life” to 10 “completely satisfied with life”. This question, like all the other questions on beliefs, expectations and evaluations, was only answered by one person in the household, the “financially knowledgeable person (FKP)” which is the person who knows best about the household’s finances.10,11 We concentrate our analysis on the balanced panel. Of the 2250 panel households that could potentially be linked across the two waves we use 2,114 for our analysis. We delete four observations with missing information on life satisfaction in either one of the two survey waves. We also exclude 61 households in which the financially knowledgeable person 7 The PHF survey was conducted in 2010 (September 2010 to June 2011) and 2014 (April to November 2014). Interviewers collect detailed data on households’ assets and liabilities in face-to-face CAPI interviews, which last, on average, about 1 h. The German surveys are part of a larger effort to collect harmonized wealth data in the euro area, the “Household Finance and Consumption Survey” (HFCS). Unfortunately, information on life satisfaction is not part of the “core questionnaire” for all countries. For more information on the survey, see Kalckreuth etal. (2012), and Altmann etal. (2020) or visit the website of the Deutsche Bundesbank/PHF. 8 A detailed description of the imputation method is available in Zhu and Eisele (2013). Altmann etal. (2020) describes the basic features. 9 See Altmann etal. (2020) for more details. 10 Since wealth and income are measured at the household level and life satisfaction is measured at the individual level, we have to assume that all persons in a household participate equally in the resources of the household. 11 See, for example, Cherchye etal. (2017). A.Jantsch et al. 101 Page 8 of 33 has changed across waves to avoid comparing life satisfaction measures of different people across time, and 52 households are excluded because there are no households to link them to in wave 1. The 52 households include 40 split-off households and 12 households where the structure changed so substantially between waves 1 and 2 that they could no longer be considered the same households. Finally, we had to drop 19 individuals because we could not assign them an ISCED education status.12 3.2 Descriptive Statistics We find that the respondents in the balanced panel have, on average, a fairly high level of life satisfaction. Average life satisfaction is almost identical in both waves: 7.32 in 2010 and 7.33 in 2014, with a standard deviation of 1.9 in each of the two years. Both the mean and the distribution are very similar across the two years, as Fig.1 shows. The mode in both years was at eight (8) and the mid-point of the scale (value 5) had a higher frequency than the next highest increment (value 6). With respect to wealth and income, the mean (median) annual net household income is €38,491 (32,400) in 2010 and €40,594 (35,316) in 2014. Mean (median) total gross wealth is at €432,003 (227,000) in 2010 and at €475,533 (256,888) in 2014 (Tables7 and 10 in the Appendix).13 There are substantial changes at the microlevel in our two main explanatory variables of interest,14 total gross wealth (total assets) and total debt (see Tables8 and 9 in the Appendix). We find that about half of the panel households change the decile of their total assets between 2010 and 2014: 30% move to a higher decile and 22% to a lower decile, approximately 48% stay in the same decile. For total debt only about one third of households (34%) stay in the same decile, 27% move up one or more decile and 38% down by at least one decile. Table 1 Effects resulting from downward and upward comparisons Source: Jantsch (2020) Upward comparison Downward comparison Positive effects (1) Tunnel effect Indication of economic chances from upward comparison (2) Relative gratification Positive feelings from downward comparison Negative effects (3) Relative deprivation Negative feeling from upward social comparison (4) Fear if social decline Indication of economic threats from downward comparison 12 Those individuals had only provided “other education” as an answer to the questions on their educational background. 13 Median and mean values for wealth components are presented in Table7 in the Appendix. Descriptive statistics for control variables included in the regression analysis are presented in Table10 inthe Appendix. Both total net household income and total household wealth are substantially higher than the weighted averages for the total population, reflecting the oversampling of the wealthy. 14 Please note that we do show the transitions within the wealth and debt distributions without considering where the households are in the life satisfaction distribution. It is not possible to infer from these tables how changes in wealth and debt are linked to changes in life satisfaction. This is the main topic of our multivariate analysis presented below. Beyond Income: Exploring theRole ofHousehold Wealth for… Page 15 of 33 101 Here, the negative difference, Diff-, represents an upward comparison, wherein one’s own income and total assets are below that of the reference group. According to Eq.(5), a negative sign of the estimated coefficients of DiffYand DiffAcorrespond to the tunnel effect, whereas a positive sign of the estimated coefficients of DiffYand DiffAcorrespond to the relative deprivation effect (see Table1 in subsection2.2 for an overview of the effects). However, this interpretation of the signs does not hold for the coefficients of relative debt; it is the other way around. Here, DiffDcorresponds to downward comparison as the reference group is worse off due to holding more debt. Hence, a negative sign of the estimated coefficient of DiffD-corresponds to the relative gratification effect because as the total debt of the reference group decreases, so too does the distance between one’s own and the reference debt decrease. A positive sign of the estimated coefficient of DiffDcorresponds to a fear and worry of social decline. The logic here is that as the debt of the reference group decreases, life satisfaction is expected to decrease also as fear and worry of future social decline set in. The positive difference, Diff+, represents a downward comparison, wherein one’s own income and total assets are above that of the reference group. Looking at Diffy+ and DiffA+, a negative sign corresponds to a sense of fear and worry about one’s own social decline, whilst a positive sign of the estimated coefficient is associated with the effect of relative gratification. Here, too, these interpretations do not hold for the relative debt indicators. The term DiffD+ represents an upward comparison, as it implies that one’s own total debt is larger than the median in the reference group. A negative sign of the estimated coefficient of DiffD+ corresponds to the relative deprivation effect because with decreasing reference total debt, and therefore an increasing DiffD+, a lower level of life satisfaction would be expected. It follows that if the sign of the coefficient for DiffD+ is positive, a higher life satisfaction is expected when reference total debt decreases and DiffD+ gets larger. In this case, therefore, (positively assessed) information is derived so that the household can also Table 2 Life satisfaction, net income, total assets, and total debt in Germany—coefficients from fixed effects panelregressionsa Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, persons in panel households only. The models are based on Eq.1. Multiple imputation taken into account in the calculation of SEs ***p < 1%, **p < 5%, *p < 10% a These results are robust to excluding households with change in their composition (see Supplemental Table1 in the online Appendix) Variables (1) (2) (3) ln(total assets) 0.097*** 0.103*** [0.035] [0.036] ln(total debt) −0.016* [0.009] ln(hh-income) 0.370*** 0.329*** 0.334*** [0.115] [0.113] [0.113] Controls Yes Yes Yes Constant 9.565 9.500 9.509 [2.954] [2.956] [2.961] Model test F statistic 3.82 3.14 3.14 MI model test p-value < 0.001 < 0.001 < 0.001 Observations 4108 4108 4108 Number of individuals 2054 2054 2054 A.Jantsch et al. 101 Page 16 of 33 achieve the low debt level of the reference group in the future. Hence, a positive sign of the estimated coefficient of DiffD+ corresponds to the tunnel effect. According to the size of the point estimates in column (2) of Table5, the comparison effect of income is symmetric as the coefficients are of similar size. With this finding of the upward comparison not dominating the downward comparison, we do not corroborate previous empirical evidence that points to upward comparisons being more relevant to people with respect to income (Duesenberry, 1949; Ferrer-i-Carbonell, 2005; Holländer, 2001; Vendrik & Woltjer, 2007). Here, the relative deprivation effect with one’s own income being below and fear and worry of social decline with one’s own income being above that of the respective reference group’s income is at play. Results regarding social comparisons with respect to total assets indicate that there is, in accordance with expectations, dominance of the upward comparison over the downward Table 3 Life satisfaction and net wealth components: coefficients from fixed effects panelregressionsa Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, persons in panel households only. The models are based on Eq.2. Multiple imputation taken into account in the calculation of SEs ***p < 1%, **p < 5%, *p < 10% a A table with coefficient estimates for all variables including control variables is available in the Online Appendix Variables Indicators Values (1) (2) Has real assets −0.102 – [0.220] Has financial assets 0.684*** – [0.242] Has secured debt 0.010 – [0.096] Has unsecured debt −0.255*** – [0.085] ln(real assets) – 0.012 [0.021] ln(fin. assets) – 0.071*** [0.025] ln(secured debt) – 0.001 [0.009] ln(unsecured debt) – −0.031*** [0.010] ln(hh-income) 0.369*** 0.328*** [0.114] [0.114] Controls Yes yes Constant 9.281 9.758 [2.941] [2.948] Model test F statistic 3.150 3.256 MI model test p value < 0.001 < 0.001 Observations 4108 4108 Number of individuals 2054 2054 Beyond Income: Exploring theRole ofHousehold Wealth for… Page 17 of 33 101 comparison when comparing the size of the estimated coefficients. In the case of the upward comparison, life satisfaction is expected to increase the smaller the difference becomes between the total assets of one’s own and those of the respective reference group. This is an indication for the relative deprivation effect being at play. If the household’s total assets are above the level of the reference assets, life satisfaction is expected to slightly decrease the smaller the difference becomes between the total assets of one’s own and those of the respective reference group with the point estimate being close to zero though. Results regarding social comparisons with respect to total debt indicate that life satisfaction is expected to increase the larger the difference becomes between the total debt of one’s own and those of the respective reference group. This is regardless of whether the household’s total debt is above or below the level for the reference assets. Our results also indicate that there is dominance of the upward comparison and therefore the relative deprivation effect over the downward comparison when comparing the size of the estimated coefficients. The results presented above raise at least two questions: (1) who are the individuals whose own life satisfaction decreased due to the greater income and assets of others? Table 4 Life satisfaction and reference group median wealth, debt and net income: coefficients from fixed effects panel-regressionsa Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, persons in panel households only. The models are based on Eqs.1 (column 1) and 3 (columns 2–4). Multiple imputation taken into account in the calculation of SEs. *** p < 1%, ** p < 5%, * p < 10%. Standard errors clustered at reference group level. Reference income ln(Yr), assets ln(Ar) and debt ln(Dr) refer to the median income, assets and debt of the previously defined reference group r of each household a A table with coefficient estimates for all variables including control variables is available in the Online Appendix Variables Baseline +Ref income +Ref assets +Ref debt (1) (2) (3) (4) Total assets: ln(A) 0.103*** 0.104*** 0.103*** 0.103*** [0.031] [0.032] [0.031] [0.031] Total debt: ln(D) −0.016 −0.017 −0.017 −0.017 [0.011] [0.011] [0.011] [0.011] Net income: ln(Y) 0.334*** 0.329*** 0.328*** 0.330*** [0.110] [0.109] [0.109] [0.110] Reference income: ln(Yr) – 0.305 0.202 −0.000 [0.224] [0.257] [0.293] Reference assets: ln(Ar) – – 0.039 −0.031 [0.069] [0.096] Reference debt: ln(Dr) – – – 0.124 [0.082] Controls yes yes yes yes Constant 9.509 8.597 8.552 9.086 [2.961] [2.359] [2.792] [2.771] Model test F statistic 3.145 41.985 41.720 30.500 MI model test p value < 0.001 < 0.001 < 0.001 < 0.001 Observations 4108 4108 4108 4108 Number of individuals 2054 2054 2054 2054 A.Jantsch et al. 101 Page 18 of 33 Table 5 Life satisfaction and reference group wealth measures: coefficients from fixed effects panel-regressionsa Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, persons in panel households only. The models are based on Eqs. 4 and 5. Multiple imputation taken into account in the calculation of SEs. Standard errors clustered at reference group level. ***p < 1%, **p < 5%, *p < 10%. Reference income ln(Yr), assets ln(Ar) and debt ln(Dr) refer to the median income, assets and debt of the previously defined reference group r of each household. For the case of income and total assets, the negative difference Diff− represents an upward comparison with the own consumption opportunities being below that of the reference group. The positive difference Diff+ represents a downward comparison with the own consumption opportunities being above that of the reference group. For the case of debt, the opposite applies a The correlation between the different indicators, particularly median reference income and debt, is relatively high. Data from the PHF survey indicate that higher-income households tend to have higher levels of outstanding liabilities compared to lower-income households, likely due to their greater capacity to service mortgages or other forms of Variables (1) (2) Total assets: ln(A) 0.103*** 0.099 [0.031] [0.117] Total debt: ln(D) −0.017 0.121 [0.011] [0.083] Net income: ln(Y) 0.330*** 0.350 [0.110] [0.299] Reference income: ln(Yr) −0.000 – [0.293] Reference assets: ln(Ar) −0.031 – [0.096] Reference debt: ln(Dr) 0.124 – [0.082] DiffY −: ln(Y/Yr) – 0.136 [0.347] DiffY +: ln(Y/Yr) – −0.156 [0.267] DiffA −: ln(A/Ar) – 0.059 [0.092] DiffA +: ln(A/Ar) – −0.006 [0.121] DiffD −: ln(D/Dr) – −0.043 [0.105] DiffD +: ln(D/Dr) – −0.144* [0.084] Controls Yes Yes Constant 9.086 8.119 [2.771] [2.873] Model test F statistic 30.500 45.785 MI model test p value < 0.001 < 0.001 Observations 4108 4108 Number of individuals 2054 2054 Beyond Income: Exploring theRole ofHousehold Wealth for… Page 19 of 33 101 And (2), are there individuals who use the higher level of income or total assets of others as information for their own potential level of income or total assets in the future? FitzRoy etal. (2014) have postulated that relative deprivation effects with respect to income dominates in later life, while the positive tunnel effect is more important early in life. We thus split the sample by age in a subsequent step and repeated the analysis, including relative income as well as relative wealth indicators for individuals younger than 45years and individuals 45years and older. The results for this split sample are shown in Table6. Interestingly, income, total assets and total debt do not seem to be associated with life satisfaction of younger individuals, as is indicated by the size of the estimated coefficients shown in column (1). Household income appears to have been more important for life satisfaction among the older population, which is indicated by the larger point estimate; the same applies to both total assets and total debt. Reference income and reference assets show opposite associations with life satisfaction for younger and older individuals. Whereas higher incomes and assets of the respective reference group are associated with, on average, lower levels of life satisfaction for the young, they slightly increase life satisfaction for the older individuals. With this finding we do not confirm FitzRoy etal. (2014) results with the tunnel effect being more important in early life. Looking at the association between life satisfaction and reference debt, the results in columns (1) and (3) show that for both younger and older people the reference debt was positively associated with life satisfaction. This means that life satisfaction is predicted to increase on average with an increase in reference group’s debt. Looking at the size of the estimated coefficients, this association was even stronger for the younger population. Coulum (2) in Table6 displays that the upward comparisons dominated with respect to relative income in the younger sample. The negative associations of the reference income can be interpreted as a relative deprivation effect. With this analysis, we do not observe similar results to FitzRoy etal. (2014) for relative income, as we found that the relative deprivation effect plays a role in both younger and later life. Furthermore, our results do not suggest there is a tunnel effect with respect to income. In the sample containing older individuals, downward comparisons seem to be more pronounced as seen in column (3). As the coefficient appears to be negative, we interpret this as fear and worries of social decline because an increase in reference income is associated with lower levels in life satisfaction. In terms of total assets, downward comparisons dominated in both the younger and the older sample. In the case of the younger sample, the positive coefficient of the downward comparison is associated relative gratification whereas in the older sample the negative coefficient is associated with fear and worries of social decline. Regarding the relationship between life satisfaction and total reference debt, the upward comparison, i.e., towards those with a lower level of total debt, dominated in both population groups. Thus, the feeling of relative deprivation also dominated among both population groups since the point estimate appears to be negative. debt. Additionally, the high correlation observed in our analysis may be partly attributable to the limited number of reference groups considered A table with coefficient estimates for all variables including control variables is available in the Online Appendix Table 5 (continued) A.Jantsch et al. 101 Page 20 of 33 6 Concluding Remarks Our study contributes to the ongoing debate on the relationship between individuals’ financial situation and subjective well-being (SWB). We show that a broader concept, going beyond income, is important when analysing the relationship between SWB and the financial situation of a household or individual. In line with the existing literature, we find the expected positive association between net income and individual life satisfaction. This relationship remains relatively stable even after accounting for wealth, suggesting that income and wealth exert separately identifiable associations with life satisfaction. While we observe a positive association between total assets and life satisfaction, total debt exhibits a negative relationship with life satisfaction. These associations hold true even after controlling for household income and other sociodemographic factors. Contrary to the existing literature, when examining the interplay between life satisfaction and the financial situation of one’s reference group, we find that reference income is positively associated with life satisfaction. The subsequent addition of reference debt suggests a marginal and economically small tunnel effect. In contrast, an increase in reference total assets correlates with a decrease in individual life satisfaction, indicative of a deprivation effect. Moreover, life satisfaction is positively related to the total debt of the reference group, reinforcing the deprivation effect. The impact of reference income and reference assets on life satisfaction varies between age groups, with higher incomes and assets reducing life satisfaction for the young but slightly increasing it for the older population. These findings challenge previous claims of a dominant tunnel effect in early life and a relative deprivation effect in later life. While our results are robust to different versions of the main regressions, our findings must be considered in the light of several limitations. While we take the change in income and wealth for SWB into account, we do not (fully) consider the source of the variation explicitly. Inheritances and gifts, but also life events like divorces or unemployment spells could easily influence the development of wealth and income as well as SWB directly. The SWB of a household that “lost” wealth because an investment going bad may be markedly different from the SWB of a household which just transferred the same amount of wealth to its children. However, in our approach the “loss” in wealth would be treated equally. A second limitation is that we only observe households every four years. The four-year gap between the two-panel waves may raise concerns about reverse causality, i.e., SWB not only being influenced but also influencing wealth or debt accumulation. While we cannot completely rule this out, we think that given that wealth typically builds up and changes slowly, it does not call our analyses into question. However, given our setup, the point estimates should be interpreted as associations and not as causal effects. The slow accumulation of wealth may also limit the generalizability of our results. A longer-term perspective may be necessary to better assess the impact of wealth dynamics on SWB. Future research is needed to fully understand the mechanisms behind a change in different wealth components, in order to fully understand the relationship between wealth and SWB. In particular, it would be interesting to see how, to paraphrase Bentham (1789/2000, 31), intensity and duration of pleasure and pain look when someone consumes or acquires a good that is financed, for example, by unsecured debt. Questions that would be worth exploring in this context refer to the psychological burden of consumer debt relative to the benefits of consuming the debt-financed goods or reasons when the possession of real assets is associated with lower life satisfaction. Beyond Income: Exploring theRole ofHousehold Wealth for… Page 21 of 33 101 Table 6 Separate fixed-effects panel regressions of individuals’ life satisfaction on absolute wealth and relative wealth for Younger and Older peoplea Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, persons in panel households only. The models are based on Eqs.4 and 5. Results Multiple imputation taken into account in the calculation of SEs. Standard errors clustered at reference group level. *** p < 1%, ** p < 5%, * p < 10%. Reference income ln(Yr), assets ln(Ar) and debt ln(Dr) refer to the median income, assets and debt of the previously defined reference group r of each household. For the case of income and total assets, the negative difference Diff− represents an upward comparison with the own consumption opportunities being below that of the reference group. The positive difference Diff+ represents a downward comparison with the own consumption opportunities being above that of the reference group. For the case of debt, the opposite applies a A table with coefficient estimates for all variables including control variables is available in the Online Appendix Variables Younger (aged < 45) Older (aged ≥ 45) (1) (2) (3) (4) Total assets: ln(A) 0.064 −0.213 0.084** 0.212 [0.063] [0.206] [0.031] [0.152] Total debt: ln(D) 0.007 0.306** −0.021* 0.065 [0.022] [0.132] [0.011] [0.095] Net income: ln(Y) 0.048 0.053 0.352** 0.486 [0.299] [0.799] [0.128] [0.395] Reference income: ln(Yr) −0.142 – 0.098 – [1.075] [0.347] Reference assets: ln(Ar) −0.143 – 0.076 – [0.260] [0.126] Reference debt: ln(Dr) 0.210* – 0.076 – [0.115] [0.098] DiffY −: ln(Y/Yr) – 0.405 – −0.039 [1.152] [0.399] DiffY +: ln(Y/Yr) – −0.300 – −0.222 [0.858] – [0.318] DiffA −: ln(A/Ar) – 0.089 0.025 [0.267] – [0.112] DiffA +: ln(A/Ar) – 0.296 −0.147 [0.235] – [0.157] DiffD −: ln(D/Dr) – −0.091 0.027 [0.190] – [0.115] DiffD +: ln(D/Dr) – −0.315** −0.093 [0.125] – [0.097] Controls Yes Yes Yes Yes Constant 12.177 13.394 −1.453 −1.593 [9.397] [9.014] [12.604] [11.647] Model test F statistic 47.394 120.367 417.410 449,820 MI model test p value < 0.05 0.128 < 0.001 < 0.001 Observations 814 814 3,294 3,294 Number of individuals 407 407 1,647 1,647 A.Jantsch et al. 101 Page 22 of 33 Our findings have a number of practical implications for policymakers. Given the importance of relative aspects of wealth and income, policymakers should design policies that address not only absolute levels of material well-being, such as income and wealth but also relative ones. Policies aimed at wealth redistribution, progressive taxation, and social welfare programs can mitigate the negative effects of inequality. By enhancing social cohesion and reducing the gap between the rich and the poor, such policies can improve overall subjective well-being. Furthermore, these insights can guide public policy to focus on measures that consider both material and psychological components of well-being, ensuring a more holistic approach to improving quality of life. Some international policy institutions are indeed going in this direction: the OECDs Wellbeing framework (OECD, 2020) and the current work of the European Commission on Sustainable and Inclusive Wellbeing (Benczur etal., 2024) acknowledge the crucial importance of people’s economic conditions for well-being and for determining consumption possibilities but also recognise other factors that have wide-ranging consequences for other aspects of life, such as education and health. Appendix See Tables7 , 8, 9, 10, 11, 12, 13. Beyond Income: Exploring theRole ofHousehold Wealth for… Page 23 of 33 101 Table 7 Descriptive statistics for wealth variables included in the analysis Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, panel households only Participation rate (%) Conditional mean Conditional median Conditional SD 2010 Total gross wealth 100.0 432,003 227,000 923,634 Total net wealth 100.0 382,787 184,000 888,129 Total real assets 90.5 359,150 202,000 805,480 Total financial assets 99.6 101,247 37,000 306,659 Total outstanding balance of secured debt 30.4 128,673 88,000 164,889 Total outstanding balance of non-secured debt 31.9 12,430 4000 33,178 2014 Total gross wealth 100.0 475,533 256,888 841,092 Total net wealth 100.0 434,306 213,150 826,801 Total real assets 90.7 402,880 220,400 684,916 Total financial assets 99.8 114,310 39,200 351,505 Total outstanding balance of secured debt 29.2 143,289 90,000 226,249 Total outstanding balance of non-secured debt 29.0 11,876 4500 35,590 A.Jantsch et al. 101 Page 24 of 33 Table 8 Total assets quintiles in 2010 and 2014: transitions, (row percentages) Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, panel households only 2014 2010 < 20 20–39 40–59 60–79 80–100 Total < 20 63 27 8 1 1 100 20–39 17 50 25 5 3 100 40–59 5 16 49 22 8 100 60–79 2 2 14 52 30 100 80–100 0 0 2 10 88 100 Total 10 12 15 20 43 100 Table 9 Total debt quintiles in 2010 and 2014: transitions, (row percentages) Source/Notes: PHF 2010/11, PHF 2014–SUF Files, unweighted, panel households only 2014 2010 < 20 20–39 40–59 60–79 80–100 Total < 20 39 24 21 9 6 100 20–39 26 22 35 10 7 100 40–59 12 28 36 15 9 100 60–79 3 6 25 50 16 100 80–100 1 1 4 17 77 100 Total 10 12 21 23 34 100 Beyond Income: Exploring theRole ofHousehold Wealth for… Page 31 of 33 101 Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1090202400811-1. 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