Europeans’ Happiness from an Egalitarian Perspective: More Equal Overall, but Often More Polarized Between Rich and Poor

Delhey, Jan; Gercke, Marcus Article — Published Version Europeans’ Happiness from an Egalitarian Perspective: More Equal Overall, but Often More Polarized Between Rich and Poor Social Indicators Research Provided in Cooperation with: Springer Nature Suggested Citation: Delhey, Jan; Gercke, Marcus (2025) : Europeans’ Happiness from an Egalitarian Perspective: More Equal Overall, but Often More Polarized Between Rich and Poor, Social Indicators Research, ISSN 1573-0921, Springer Netherlands, Dordrecht, Vol. 179, Iss. 1, pp. 441-462, https://doi.org/10.1007/s11205-025-03619-5 This Version is available at: https://hdl.handle.net/10419/330772 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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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) Social Indicators Research (2025) 179:441–462 https://doi.org/10.1007/s11205-025-03619-5 ORIGINAL RESEARCH Europeans’ Happiness fromanEgalitarian Perspective: More Equal Overall, butOften More Polarized Between Rich andPoor JanDelhey1 · MarcusGercke1 Accepted: 29 April 2025 / Published online: 17 May 2025 © The Author(s) 2025, corrected publication 2025 Abstract European countries have become more prosperous since 2000, but social and economic development has also become more crisis-prone and, in particular, characterized by growing economic inequality. From an egalitarian perspective, the question arises as to how this ambivalent situation has affected the distribution of subjective well-being and, in particular, the gap between rich and poor. Based on life satisfaction data for 27 countries from 10 waves of the European Social Survey (2002–2024), this paper examines whether well-being within nations has become more unequal, both in the populations as a whole (overall dispersion) and between income groups specifically (group polarization). For the total population, our results suggest that there is growing equality in life satisfaction almost everywhere, which is mainly driven by falling unemployment and increases in national prosperity. In about half of the countries, however, we find an increasing polarization of life satisfaction between rich and poor, fueled by rising national prosperity and increasing social protection expenditures. From an egalitarian point of view, the last two decades have thus brought both progress and regression. Keywords Life satisfaction· Well-being· Happiness inequality· Polarization· Income groups· Trend analysis 1 Introduction Economic inequality has increased in many Western and European countries since the 1990s (Alderson et al., 2005; Makhlouf, 2023). Prominent social scientists have long warned of the far-reaching consequences of a wide—and widening—gap between rich and poor, such as declining social mobility, greater health and social problems, and dwindling support for democracy (Grusky & Maclean, 2016; Stiglitz, 2012; Wilkinson & * Jan Delhey [email protected] Marcus Gercke [email protected] 1 Otto-von-Guericke University Magdeburg, Faculty ofHumanities andSocial Sciences, Institute ofSocial Sciences, Zschokkestr. 32, 39106Magdeburg, Germany 442 J.Delhey, M.Gercke Pickett, 2010). But is people’s subjective well-being also affected? Has well-being inequality increased along with economic inequality? Previous studies based on data up to early 2000 have suggested that this fear did not materialize in Western Europe (Clark etal., 2016; Veenhoven, 2005), mainly as a result of income growth. But has this progressive trend continued, and, if so, has it continued throughout Europe? Economic inequality has continued to rise in many countries and socioeconomic development has become more crisis-prone overall, which has led to economic insecurity, especially among low-income and other vulnerable groups (Hacker, 2006; Ranci etal., 2021). A study that extended the Eurobarometer time series to the mid-2010s reports rising inequality in life satisfaction in the countries most affected by the euro zone crisis (Jorda etal., 2019). Against this background, the present article examines changes in the well-being distribution over more than two decades (2002–2024) with populationrepresentative data from the European Social Survey (ESS) for a large number of European countries. Our paper makes three contributions. First, we update the above-mentioned research on the evolution of well-being inequality in the total population, using the most recent data. Second, we examine changes in the extent of well-being polarization between the top and bottom income groups. When it comes to the effects of widening economic disparities, we believe it is essential to compare the happiness with life of richer and poorer people directly. To our knowledge, evidence of changing between-group happiness inequality only exists so far for individual countries, such as the USA (Stevenson & Wolfers, 2008), Germany, and Switzerland (Lipps & Oesch, 2018), and—surprisingly—not for income groups. Finally, we provide evidence of which changes in fundamental socioeconomic conditions have driven changes in well-being inequality. There are mainly cross-sectional studies on this topic (e.g., Berg & Veenhoven, 2010; Delhey & Kohler, 2011; Kalmijn & Veenhoven, 2005), and longitudinal studies (Graafland & Lous, 2019) are rare exceptions. Longitudinal studies have so far mainly focused on the macro determinants of happiness levels rather than disparities (Bartolini etal., 2017; Evans etal., 2019; Schröder, 2018). The remainder of this paper is organized as follows. First, we clarify our main concepts and outline what expectations are plausible for trends in well-being inequality, based on the sequence model of life evaluation (Veenhoven, 2012) and existing research. We then introduce our data set and the measures we used to quantify well-being inequality within nations. We move on to the results of our analysis, place them in the context of the current state of research, and, finally, discuss their broader implications. 2 Conceptual Clarifications, Expectations, andState ofResearch 2.1 Life Satisfaction andits Inequality Recent decades have seen a growing interest in subjective life outcomes—that is, how people perceive and evaluate their quality of life, also known as happiness or (subjective) wellbeing. Individuals’ life satisfaction has been suggested as a means to capture well-being as comprehensively as possible; this can be defined as the “degree to which an individual judges the overall quality of his/her own life-as-a-whole favorably” (Veenhoven, 1984, p. 22, italics in the original). This key expression of evaluative well-being is considered to be less volatile and more cognitively based than measures of emotional well-being (Diener etal., 2003; Nettle, 2005). 443 Europeans’ Happiness fromanEgalitarian Perspective: More… According to Veenhoven’s (2012) sequence model, happiness with life in the sense of life satisfaction is the outcome of a stepwise assessment process. The model’s starting point is a person’s life chances, which result from individual life skills (e.g., intelligence), personal resources (e.g., economic capital), and larger societal conditions (e.g., national wealth and income distribution). These—differentially favorable—life chances generate a stream of positive or negative events that a person encounters in daily life, which in turn is reflected in a corresponding stream of pleasant or unpleasant experiences of both a cognitive and emotional nature that form the basis for the individual’s general assessment of life, which ultimately also factors in social and other comparisons (Michalos, 1985). Looking at life satisfaction from an egalitarian perspective means taking a primary interest in its distribution (Veenhoven & Kalmijn, 2005). Because the central input variables of the sequence model are unequally distributed between individuals (e.g., some have better life abilities, others worse; some have more personal resources, others fewer), there is also a certain inequality in life satisfaction: nowhere is everyone equally happy (or unhappy). Even though it is obvious that happiness cannot simply be “redistributed” like other goods, political bodies have adopted the idea of aiming for the highest possible well-being for all citizens, which implies a low level of inequality. The Council of Europe (2008, p. 14) has explicitly committed itself to the goal of cohesive well-being and defined cohesion as “the capacity of a society to ensure the well-being of all its members, minimising disparities and avoiding marginalisation.” Two main approaches can be distinguished in how happiness inequality is conceptualized (Quick, 2015). The first and most widespread approach considers the subjective well-being of all members of society and expresses the resulting distribution in one number, be it the standard deviation (e.g., Berg & Veenhoven, 2010), the percent-maximum standard deviation (e.g., Delhey & Kohler, 2011), the Gini index (e.g., Gandelman & Porzecanski, 2013), or various ordinal inequality measures (e.g., Bérenger & Silver, 2022; Grimes etal., 2023); no gold standard has yet been established. Comparatively equal distributions of well-being are typically found in Europe and English-speaking New World countries, more unequal ones in the Middle East and North Africa, in Latin America, and, especially, sub-Saharan Africa (Berg & Veenhoven, 2010; Delhey & Kohler, 2011; Helliwell etal., 2022). Country characteristics that are associated with low happiness inequality cross-nationally include economic prosperity, egalitarian income distribution, low levels of corruption, and a climate of social trust (Delhey & Kohler, 2011; Ovaska & Takashima, 2010; Salahodjaev, 2021; Veenhoven & Kalmijn, 2005), conditions that are also conducive to high levels of happiness (Ott, 2005; Veenhoven, 2012). The second approach focuses on the inequality in well-being between predefined groups. This can involve the comparison of demographic groups such as urbanites and country-dwellers (Burger et al., 2020), or of socioeconomic groups differentiated by income, education, or social class. Typically, higher-status people enjoy a higher level of subjective well-being, which gives rise, for example, to a gap between the rich and the poor (Caporale etal., 2009; Delhey & Steckermeier, 2016; Schyns, 2002). However, these gaps are not the same size everywhere. In Europe in the early 2000 s, differences in life satisfaction between top and bottom groups according to income, education, or class were small in Nordic countries and much greater in post-socialist countries (Delhey, 2004). 2.2 Expectations fortheDevelopment ofLife Satisfaction Inequality In this article, we seek to determine whether well-being inequality has changed during the past two decades. The fact that European countries have become even wealthier in the new 444 J.Delhey, M.Gercke millennium could certainly mean a continuation of the positive trend toward a more equal well-being that was identified for the three decades up to the early 2000s (Clark etal., 2016; Veenhoven, 2005). Yet other developments could suggest a break in the trend, first and foremost the widening economic gaps between rich and poor in many countries. These distributive shifts themselves are fueled by precarious working conditions (Standing, 2011), a growing low-wage sector, and the transition to an activating welfare state. According to Nachtwey (2018), we are living in a new era of regressive modernization, which works like the escalators in a department store: for some it is still going up, but for others it is going down. Empirically, economic capital is associated with happiness and life satisfaction (see above); so, if economic resources are more unequally distributed today, this should—all other things being equal—lead to more unequal flows of life events, experiences, and therefore emotions and cognitions, thus making greater satisfaction inequality likely. Widening income disparities also mean that those with low incomes fare even worse in social comparisons (Layard etal., 2010), which could further increase happiness inequality. The succession of social and economic crises could also suggest a break in the positive trend toward more even distribution of happiness. The global financial crisis in 2008/9 plunged the majority of European countries into a recession, while the eurozone debt crisis in the period 2010–2014 primarily affected countries in Southern Europe, plus Ireland. For several years, unemployment rose across Europe, but most dramatically in southern Europe (Boeri & Jimeno, 2016; Heidenreich, 2016). There, and in Europe’s liberal welfare states, the rate of people with severe material deprivation increased (Heidenreich, 2016). Cuts in welfare state benefits disproportionately affected the vulnerable and especially low-income groups (Matos, 2022). The strong influx of migrants in 2015/16, and again in 2022 as a result of Russia’s war of aggression against Ukraine also had the strongest impact on the lives of the lower classes, as many migrants compete with them for similar jobs (Jetten, 2019) and social benefits (Cordero etal., 2023). Due to the war, the supply of energy has become more difficult and therefore more expensive, and in combination with the supply shortages caused by the coronavirus pandemic, consumer prices rose sharply in 2022 and 2023. Typically, low-income earners are the ones who feel inflation the most. The general argument we want to put forward is that periods of economic malaise and social turbulence hit the already disadvantaged groups hardest—which could have resulted in widening gaps in subjective well-being overall and between richer and poorer people in particular. What is known from the existing studies? Two studies, roughly covering the period 1970–2000, concluded that inequality in life satisfaction has narrowed in most Western European countries (Clark etal., 2016; Veenhoven, 2005). For the period 2006–2021, the World Happiness Report (Helliwell etal., 2022) echoes this conclusion for European countries on average; however, averaging could conceal diverging trends in individual countries. Notably, a recent research paper points to a growing disparity in life satisfaction in countries severely affected by the eurozone debt crisis (Jorda etal., 2019). For post-communist countries, first an increase, then a decrease in life satisfaction inequality has been reported since the 1990 s (Arslan, 2023), largely parallel to the initially difficult and then consolidating transformation process. Looking beyond Europe, there is evidence of declining happiness inequality for single countries like the USA (Dutta & Foster, 2013; Stevenson & Wolfers, 2008), Japan (Araki, 2023), and South Africa (Kollamparambil, 2020), as well as globally (Veenhoven, 2005). Interestingly, and confusingly, the World Happiness Report identifies widening disparities in well-being as a global trend, except for Europe (as mentioned above). There is only scarce evidence on how between-group well-being inequality has evolved. In the USA, differences in life satisfaction according to gender, race, marital 445 Europeans’ Happiness fromanEgalitarian Perspective: More… status, and age have narrowed, while differences by education have widened (Stevenson & Wolfers, 2008). The happiness gap between rich and poor has also widened in the USA (Okulicz-Kozaryn & Mazelis, 2017). For Germany, a recent study points to widening gaps between social classes (Lipps & Oesch, 2018). For the most part, these trend studies tend to be descriptive, so the question of what drives happiness inequality can be considered to be under-researched. A comparative study on Western Europe pointed to the crucial role of changes in national prosperity (Clark etal., 2016), while a comparison of OECD countries highlighted changes in income inequality (Graafland & Lous, 2019). Another research paper focusing on one country case, Germany, confirmed the positive role of increases in average income in reducing happiness inequality, whereas growing unemployment has the opposite effect (Becchetti etal., 2014). The present study aims to expand knowledge on the following research questions: RQ1: Has the trend toward greater well-being equality in European countries continued over the past two decades, or has this trend reversed? RQ2: What changes in socioeconomic conditions influence well-being inequality over time, either increasing or decreasing it? We use life satisfaction as an indicator of well-being and analyze its distribution from two distinct perspectives on polarization. The first perspective examines the distribution of satisfaction within the population as a whole and uses a measure designed for ordinal variables. In light of the ongoing debate regarding the cardinal (Kalmijn & Arends, 2010; Kalmijn & Veenhoven, 2005) versus ordinal measurement of life satisfaction inequality (Cowell & Flachaire, 2017; Jenkins, 2020), we have adopted an approach that accounts for the ordinal nature of the data. The second perspective compares the overlap between distributions of life satisfaction in two pre-defined subpopulations, richer and poorer people. To clearly distinguish these two perspectives, we refer to general polarization as overall dispersion and to the polarization between income groups as (income) group polarization. As for the potential drivers, we closely follow our storyline (see above) and focus on socio-economic factors. First, we consider economic inequality, which we measure using various indicators. We also take into account macroeconomic factors, including national prosperity, unemployment, inflation, and social spending. Changes in these parameters critical to well-being reflect the increased volatility—if not the susceptibility to crises— of European societies over the past two decades. Finally, we consider social trust as a key indicator of social cohesion (Larsen, 2013) about which many people are deeply concerned today. The chosen explanatory variables are repeatedly used in comparative quality-of-life research to explain happiness levels (e.g., Bjornskov, 2003; Welsch & Bonn, 2008), happiness inequality (e.g., Delhey & Kohler, 2011; Veenhoven & Kalmijn, 2005), and inequality-adjusted happiness levels (Veenhoven & Kalmijn, 2005). 3 Data andMethods To describe and explain trends in well-being inequality, this study employs individual-level survey data that are aggregated at the country level and supplemented by country-level social indicators. 446 J.Delhey, M.Gercke Life Satisfaction Data on life satisfaction were taken from 10 rounds of the European Social Survey Cumulative File (ESS 1–11, 2024). The ESS has been conducted biannually since 2002 (Round 1), with the 2024 survey (Round 11) being the most recent one. Round 10 from 2020 was excluded due to an interim change in survey mode during the coronavirus pandemic. The subsequent analyses cover 27 countries; we excluded countries that had participated in fewer than three ESS rounds (seven countries)1 or had missing data on key explanatory variables, including variables used for robustness checks (three countries).2 The ESS contains the following established item to measure life satisfaction: “All things considered, how satisfied are you with your life as a whole nowadays? Please answer using this card, where 0 means extremely dissatisfied and 10 means extremely satisfied” (European Social Survey European Research Infrastructure Consortium [ESS ERIC], 2024). Table1 presents the descriptive statistics for the interand extrapolated sample. The median life satisfaction for the entire sample is 7. The lowest country median is 5, and the highest is 9. The overall standard deviation (SD) of the sample is just under one scale point (0.95); the within-country SD is considerably lower at 0.41 (see Table1). The overall SD represents the standard deviation for the entire sample across all countries and years, whereas the within-country standard deviation (within-country SD) represents the standard deviation within each country over the time period covered. Missing values of aggregated data between available data points were linearly interpolated, while missing information beyond the available data was replaced with the last observed data point. Detailed information on the availability of country-year data is provided in the appendix (Table1). Table 1 Descriptive information for the country sample, period 2002–2024 LIFESAT-OD = Overall dispersion of life satisfaction; LIFESAT-GP = Income group polarization of life satisfaction. Explanatory variables are lagged by one year (t − 1) except for trust. Country data are interand extrapolated across ESS rounds; see Appendix 1 Variable Countries ESS Rounds Mean (*Median) Overall SD Within SD Min Max LIFESAT 27 10 7* 0.95 0.41 5 9 Trust 27 10 5* 1.10 0.36 3 7 LIFESAT-OD 27 10 24.54 6.51 2.23 13.20 38.70 LIFESAT-GP 27 10 26.64 7.50 4.53 7.60 46.40 GDPpct−1 27 10 36,275.12 16,593.05 12,052.38 6961.08 127,873.20 log. GDPpct−1 27 10 10.40 0.46 0.31 8.85 11.76 Ginit−1 27 10 29.03 3.34 1.11 22.30 38.10 Unemploymentt−1 27 10 8.25 4.45 3.15 1.87 27.69 Social protectiont−1 27 10 16.62 4.28 1.62 7.50 26.40 Inflationt−1 27 10 2.61 2.60 2.36 –4.45 17.13 Age structuret−1 27 10 25.43 4.91 3.09 14.70 38.35 1 These countries are Albania, Kosovo, Montenegro, North Macedonia, Romania, Serbia, and Turkey. 2 These countries are Israel, Russia, and Ukraine. 447 Europeans’ Happiness fromanEgalitarian Perspective: More… Overall Dispersion of Life Satisfaction To quantify the well-being inequality in the total population, we calculated Van der Eijk’s (2001) Agreement A, inverted it, and scaled it from 0 to 100, with higher values indicating greater inequality and polarization. Agreement A, designed specifically for ordinal rating scales, is based on the principle that consensus is highest when responses cluster in a single category (a homogenous, unimodal distribution) and lowest when they are evenly split between two categories (a polarized, bimodal distribution). Mathematically, Van der Eijk’s method decomposes the response distribution into semi-uniform layers, where each layer consists of contiguous non-empty categories. The original range of Agreement A is from –1 (perfect bimodality) to + 1 (perfect unimodality). To derive a measure of disagreement, we first rescaled Agreement A to a range of 0 to 1, then inverted it and multiplied by 100. The resulting Disagreement Index is defined as: (1 – Arescaled) × 100. A value of 0 occurs when all respondents select the same category (greatest possible homogeneity); a value of 100 occurs when respondents are evenly split between just two categories—that is, half of respondents are very dissatisfied, the other half very satisfied (greatest possible polarization). A value of 50 indicates a uniform distribution of respondents across all categories. Please note that the index does not indicate the level of satisfaction at which the (dis)agreement occurs. According to the Disagreement Index, the mean overall dispersion of life satisfaction in the sample is 24.54, with an overall SD of 6.51 and a within-country SD of 2.23. The empirical values range from 13.2 to 38.7 (see Table1). Figure1 illustrates this approach with ESS data for Cyprus. In 2002, responses were concentrated in categories 7, 8, and 9, resulting in a low score of the Disagreement Index (19.7). In 2024, categories 7, 8, and 9 are less strongly filled, while categories 0, 2, 3, 4, and 5 are somewhat more strongly filled. Respondents are more spread out across the satisfaction scale, which is reflected in the higher Disagreement Index (30.8). Polarization of Life Satisfaction Between Income Groups (Group Polarization) As a preparatory step, we first harmonized the ESS income data, as income categories changed from Round 3 onward. To obtain a continuous income variable, we assigned each respondent the mean value of their reported monthly income category (e.g., €75 for the category “0 to €150”). To account for differences in household size, we applied the square root equivalence scale, a method commonly used in the Luxembourg Income Study (Buhmann etal., 1988) and by researchers working with OECD data (Thewissen etal., 2018). Specifically, we adjusted disposable household income by dividing it by the square root of the number of household members before forming income quintiles. To assess the polarization of life satisfaction between income groups, we compared how (dis)similar the distributions of life satisfaction of the poorest and richest quintiles are. Our starting point was the extent to which the two distributions overlap, using the overlapping coefficient (OVL; see Lelkes, 2016). The simple idea is that the similarity between two distributions increases as their area of overlap grows. Mathematically, the overlapping area is determined by the integral of their probability density functions and can be approximated using their standard normal cumulative distribution functions (for details, see Goldstein, 1995; Inman & Bradley, 1989). The overlapping coefficient ranges from 0 (no overlap, complete dissimilarity) to 1 (complete overlap, complete similarity). To obtain a measure of dissimilarity, we simply invert the overlap coefficient and rescale it from 0 to 100. This Dissimilarity Index is thus defined as: (1 − OVL) × 100. Higher index values 448 J.Delhey, M.Gercke Fig. 1 Overall dispersion of life satisfaction in Cyprus, 2002 versus 2024 455 Europeans’ Happiness fromanEgalitarian Perspective: More… and Spain, there was no change. Correlation of the pooled time series data confirms an upward trend of group polarization over time (r(270) = 0.123, p < 0.05). For some countries, the trend between rich and poor contrasts with the trend for overall dispersion shown above; this is also reflected in the relatively weak, yet still positive, association between the two measures (r(270) = 0.225, p < 0.001). According to the multiple TWFE models (Table3), within-country changes in life satisfaction polarization between income groups are less well explained by our set of predictors than changes in overall dispersion (R2 = 13.5 max.). Standardized effect sizes suggest that national prosperity and social protection expenditure—both with small positive effects—exceed the threshold for a small effect and thus qualify as the main drivers. As national prosperity rises, life satisfaction becomes somewhat more polarized between rich and poor (M3: β = 0.349, M4: β = 0.322). The same applies when governments increase their expenditures on social protection (M3: β = 0.207, M4: β = 0.214), which may sound counter-intuitive. However, increasing social protection expenditure may indicate an increase in the number of people who depend on it – a dependence that might widen rather than narrow the well-being gap between Fig. 4 Changes in group polarization in relation to life satisfaction (highest vs. lowest income quintile), 2002–2024. Note: Polarization measure: Dissimilarity Index [0;100]; 0 = no polarization (complete overlap of the two distributions); 100 = absolute polarization (no overlap of the two distributions). Correlation over time: r(270) = 0.123, p < 0.05 456 J.Delhey, M.Gercke rich and poor. Changes in the other socioeconomic conditions have standardized effects below the threshold for a weak effect and are therefore substantively negligible. Robustness checks (see Appendix A6 to A9) indicate that the effect of social protection expenditure falls below the threshold for a small effect when income inequality is measured using the S80/S20 ratio or the at-risk-of-poverty rate. In contrast, the effect of national prosperity remains robust. Changes in income inequality remain negligible regardless of its concrete measurement. The results from M3 and M4 are also robust to changes in civil liberties and political rights. 6 Discussion andConclusions The starting point of our investigation was the coincidence of a (further) rise in income inequality in many European countries and a succession of economic crises since 2000. This, and the inconclusiveness of previous research, motivated two research questions: (a) Has there been a trend toward growing inequality of subjective life outcomes—measured as life satisfaction—in European countries over the past two decades? (b) What changes in socioeconomic conditions have worked to increase or decrease it? For 27 ESS countries, we examined the well-being distribution in a longitudinal design through two lenses of Table 3 Within models for group polarization in life satisfaction (highest vs. lowest income quintile), 2002–2024 *** p < 0.001, ** p < 0.01, * p < 0.05, † p < 0.1. Standardized effect (β) size of b: small (0.2 < β < 0.5); medium (0.5 < β < 0.8); large (β > 0.8). β = bX × within SDX/within SDY (M3) (M4) VARIABLES LIFESAT-GP LIFESAT-GP log. GDPpct−1 5.108 4.710 Ginit−1 0.575†0.598† Unemploymentt−1 0.098 0.096 Social protectiont−1 0.579*0.599* Inflationt−1 –0.258†–0.246† Age structuret−1 0.130 0.051 Trust 1.191 Round –0.183 –0.154 Standardized effect sizes β log. GDPpct−1 0.349 0.322 Ginit−1 0.141 0.147 Unemploymentt−1 0.068 0.067 Social protectiont−1 0.207 0.214 Inflationt−1 –0.134 –0.128 Age structuret−1 0.089 0.035 Trust 0.095 Observations 270 270 Countries 27 27 ESS Rounds 10 10 F-Stat 4.584 3.706 R-squared within 0.128 0.135 457 Europeans’ Happiness fromanEgalitarian Perspective: More… polarization—across all members of society (overall dispersion) and between the upperand lower-income groups specifically (group polarization). A first important result is that the overall dispersion and group polarization are only weakly related, evolved in different directions in quite a number of countries, and have different socioeconomic drivers. This may sound contradictory, but it is not. The measures used are, first, based on different sets of people—here the population as a whole, there the rich and the poor as specific subgroups—and are therefore not derived from the same distribution. Second, the population as a whole is a composite of many groups, and the development of polarization between rich and poor can be “representative” for the total population, but it does not have to be. In some countries the rich and poor have become more dissimilar in terms of life satisfaction, but at the same time the overall dispersion has narrowed, so it stands to reason that other groups must have converged. To gain a more complete picture, it is therefore necessary to examine group polarization in addition to the overall dispersion. For the total population, we can renew Veenhoven’s (2005) well-known verdict: there has been no return of inequality in well-being. This general progressive trend puts popular portrayals of contemporary Western societies as social failures that are racked by inequality (Wilkinson & Pickett, 2010) in perspective. The evolution of the overall dispersion of satisfaction over time has primarily been influenced by changes in national prosperity (a homogenizing effect), unemployment (a polarizing effect), and the aging of societies (again a homogenizing effect). If policymakers want to enable as many people as possible to achieve the same level of happiness, then securing economic prosperity and combating unemployment are promising starting points. Seen in conjunction with results from previous research, increasing prosperity thus seems to improve both the level of well-being (Hagerty & Veenhoven, 2003; Veenhoven & Hagerty, 2006), and its overall distribution, by making it more homogenous. Our finding regarding the role of unemployment rates is consistent with studies on well-being inequality in Germany (Becchetti etal., 2014) and on various public health outcomes across the European Union (Stuckler etal., 2009). The polarization of life satisfaction between rich and poor presents a mixed picture. Seen through this lens, there has been a return of inequality in well-being in quite a number of countries. This at least qualifies Veenhoven’s (2005) verdict—and it also indicates policy failure, as the Council of Europe (2008, p. 14) has set the goal of minimizing inequalities in the well-being of the rich and the poor specifically. Not only southern European countries fail to meet this target (Jorda etal., 2019); countries from all parts of Europe, including the Nordic countries of Denmark, Sweden, and Finland, fail to do so. As a result, the evidenced lead of the “old” European member states in terms of well-being equality (Delhey, 2004) has become smaller. The strongest driver of polarization between income groups is, somewhat surprisingly, rising national prosperity. The reason could be that, as nations get richer, people in the upper income groups in particular become more and more homogenous in their—quite high—subjective wellbeing, so there are hardly any dissatisfied or unhappy people among the wealthy. Such a pattern along the income distribution characterizes the USA (Klein Teeselink & Zauberman, 2023), and it could also characterize Europe. The second driver is when states are spending a growing share of their GDP on social protection. The stigma attached to welfare recipients, or their self-stigmatization, could be the critical factor here (Baumberg, 2016); increased social spending would then alleviate material deprivation, while nevertheless leaving recipients with a satisfaction deficit. Furthermore, higher social protection expenditure may indicate an increase in the number of people who depend on it. If we assume that this dependence—especially among poorer individuals—reduces 458 J.Delhey, M.Gercke well-being, this could further explain the rise in life satisfaction inequality between rich and poor that we observed with ESS data. What about the “usual suspect”—income inequality—which is central to the famous “spirit level theory” (Wilkinson & Pickett, 2010) and the motivation for this article? In our study, economic inequality is less important than we thought: Widening income inequality leads, at most, to only a very small rise in life satisfaction inequality. Our conclusion of a very small longitudinally impact contrasts with the findings of Graafland and Lous (2019) for OECD countries but aligns with trend analyses on health and social problems (Delhey etal., 2023). Why does rising income inequality matter so little? One explanation could be that the scale of “objective” income inequality is not accurately represented in people’s subjective perceptions (Faggian etal., 2023). Another explanation could be that people today tend to rank their own position in the social hierarchy higher than people did in the past decades (Oesch & Vigna, 2022). Inequality could therefore be seen as a social problem rather than an individual one, with limited impact on life satisfaction inequality. Because our study is necessarily limited in scope, a number of follow-up questions arise for further research. We only considered subjective well-being from an egalitarian perspective; an additional examination of how levels of life satisfaction have developed would complete the picture and allow a conclusive assessment of welfare development from the perspective of social progress. It also remains to be explored whether the contrasting trends—overall a more homogeneous distribution, but quite often rising polarization between rich and poor—also apply to non-European countries. After all, it is well known that economic disparities have widened more sharply in other regions of the world (UNDP, 2019). Next, it would be worthwhile to systematically examine trends in group polarization between various sub-populations, such as those differentiated by age, gender, education, place of residence (rural–urban), ethnic background, relationship status, or political values—a research agenda that would have gone far beyond the scope of this paper. Another research desideratum is a systematic analysis of which population groups have become more homogeneous internally in terms of life satisfaction (for income groups in the USA, see Klein Teeselink & Zauberman, 2023). Withingroup homogenization may have contributed to a more even distribution of life satisfaction in the population as a whole. Whatever issues are taken up, continuing this type of research will provide valuable insights into where and why contemporary societies are moving closer to—or further away from—the goal of cohesive well-being. Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1120502503619-5. Authors’ Contributions Both authors have equally contributed according to the four criteria mentioned here: https:// www. icmje. org/ recom menda tions/ browse/ rolesandrespo nsibi lities/ defin ingtheroleofautho rsandcontr ibuto rs. html Funding Open Access funding enabled and organized by Projekt DEAL. The authors declare that they have no financial interests. Code Availability Stata Code is available on request, custom code. Declarations Ethical Approval The authors declare that the study complies with human research ethics. The authors declare that respondents gave informed consent to the survey. 459 Europeans’ Happiness fromanEgalitarian Perspective: More… Conflict of interest The authors declare no conflict of interest. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. 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