Identity as Dependent Variable: How Americans Shift Their Identities to Align with Their Politics. Patrick J. Egan. American Journal of Political Science, December 20 2019. https://doi.org/10.1111/ajps.12496
Abstract: Political science generally treats identities such as ethnicity, religion, and sexuality as “unmoved movers” in the chain of causality. I hypothesize that the growing salience of partisanship and ideology as social identities in the United States, combined with the increasing demographic distinctiveness of the nation's two political coalitions, is leading some Americans to engage in a self‐categorization and depersonalization process in which they shift their identities toward the demographic prototypes of their political groups. Analyses of a representative panel data set that tracks identities and political affiliations over a 4‐year span confirm that small but significant shares of Americans engage in identity switching regarding ethnicity, religion, sexual orientation, and class that is predicted by partisanship and ideology in their pasts, bringing their identities into alignment with their politics. These findings enrich and complicate our understanding of the relationship between identity and politics and suggest caution in treating identities as unchanging phenomena.
---
From the September 10, 2018 version:
Conclusion
These findings yield new insight on the nature of politically salient American identities
and how they can be shaped by the liberal-conservative, Democrat-Republican divide.
Inter-temporal stability varies highly among identities, running from relatively high (for
race, Latino origin and most religions) to moderate (for party identification and some national origins) to low (for most national origins, sexual orientation, and class). Many of the
identities commonly understood to be highly stable can in fact shift over time, and those
who have switched in or will soon switch out of identities make up very large shares of
those identifying as sexual minorities, religious “nones,” and any economic class.
These analyses permit us to see for the first time the extent to which over-time instability in identification is associated with politics, with liberalism and Democratic party
identification predicting shifts toward identification as Latino, lesbian, gay, or bisexual, as
nonreligious, lower class, and claiming national origin associated with being non-white;
and conservatism and Republican party ID yielding movement toward identification as being a member of Protestant faith, and having had an experience as a born-again Christian.
This is no small discovery: many of these identities are at the center of important American
policy debates, and those who claim these identities are key blocs of voters, party activists
and political donors. The data show us how in our era, which is so polarized that political
affiliations become identities in themselves, politics can create and reinforce identities even
thought to be as fixed as racial and ethnic categories. They thus reveal that “social sorting,”
while predominantly the result of individuals changing their politics to align with
their identities, is also due in some part to people shifting their identities to better align
with their politics.
Nearly sixty years ago, the “Michigan school” authors of The American Voter noted that the influence of group membership on political behavior might be overstated, as members of many identity groups often “come to identify with the group on the basis of preexisting beliefs and sympathies.” (Campbell et al 1960, 323). The findings presented here join mounting evidence that this concern was well-placed, and that more rich discoveries await those who continue to make use of powerful tools and data to understand the origins of important identities in American politics.
Bipartisan Alliance, a Society for the Study of the US Constitution, and of Human Nature, where Republicans and Democrats meet.
Saturday, December 21, 2019
Income inequality is indeed strongly & consistently related to social ills, but so is economic prosperity; & rising prosperity effectively reduces the amount of social ills, at least in Europe
Social Ills in Rich Countries: New Evidence on Levels, Causes, and Mediators. Jan Delhey, Leonie C. Steckermeier. Social Indicators Research, December 21 2019. https://link.springer.com/article/10.1007/s11205-019-02244-3
Abstract: The income inequality hypothesis claims that in rich societies inequality causes a range of health and social problems (henceforth: social ills), e.g. because economic inequality induces feelings of status anxiety and corrodes social cohesion. This paper provides an encompassing test of the income inequality hypothesis by exploring levels and breeding conditions of social ills in 40 affluent countries worldwide, as well as pathways for a subsample of wealthy European countries. Our aggregate-level research is based on a revised and updated Index of Social Ills inspired by Wilkinson and Pickett’s book The Spirit Level, which we compile for both more countries (40) and more years (2000–2015) and combine with survey information about experienced quality-of-life as potential mediators. We get three major results: First, cross-sectionally income inequality is indeed strongly and consistently related to social ills, but so is economic prosperity. Second, while longitudinally changes in inequality do not result in changing levels of social ills, rising prosperity effectively reduces the amount of social ills, at least in Europe. Finally, whereas the cross-sectional analysis indicates that aspects of social cohesion most consistently mediate between economic conditions and social ills, the longitudinal mediation analyses could not ultimately clarify through which pathway rising prosperity reduces social ills. Overall we conclude that the income inequality hypothesis is, at best, too narrow to fully understand health and social problems in rich countries.
Keywords: Prosperity Income inequality hypothesis Social ills Health Social cohesion Spirit level theory Status anxiety Two-way fixed effects
Abstract: The income inequality hypothesis claims that in rich societies inequality causes a range of health and social problems (henceforth: social ills), e.g. because economic inequality induces feelings of status anxiety and corrodes social cohesion. This paper provides an encompassing test of the income inequality hypothesis by exploring levels and breeding conditions of social ills in 40 affluent countries worldwide, as well as pathways for a subsample of wealthy European countries. Our aggregate-level research is based on a revised and updated Index of Social Ills inspired by Wilkinson and Pickett’s book The Spirit Level, which we compile for both more countries (40) and more years (2000–2015) and combine with survey information about experienced quality-of-life as potential mediators. We get three major results: First, cross-sectionally income inequality is indeed strongly and consistently related to social ills, but so is economic prosperity. Second, while longitudinally changes in inequality do not result in changing levels of social ills, rising prosperity effectively reduces the amount of social ills, at least in Europe. Finally, whereas the cross-sectional analysis indicates that aspects of social cohesion most consistently mediate between economic conditions and social ills, the longitudinal mediation analyses could not ultimately clarify through which pathway rising prosperity reduces social ills. Overall we conclude that the income inequality hypothesis is, at best, too narrow to fully understand health and social problems in rich countries.
Keywords: Prosperity Income inequality hypothesis Social ills Health Social cohesion Spirit level theory Status anxiety Two-way fixed effects
6 Discussion and Conclusion
By examining the impact of economic conditions on a broad range of social ills for 40 rich countries for the period 2000–2015, this study represents the most up-to-date and comprehensive examination of the famous inequality hypothesis. To our knowledge, this is also the first aggregate-level study in which a larger number of potential mediators between economic conditions and social ills has been put to an empirical test. Descriptively, while the ranking of countries according to their number of social ills largely matches that presented in The Spirit Level, our finding that social ills have decreased over time in all but two countries is a genuinely new finding that contradicts the widely accepted diagnose of social malaise in the developed world (Eckersley 2012; Elchardus and De Keere 2013). While some of our results provide partial support for the inequality hypothesis, others contradict it. We begin our discussion with the supporting evidence, which stems exclusively from the cross-sectional analysis.
The first confirmatory finding is that cross-sectionally the scale of income inequality is positively associated—year by year—with social ills, an association that holds when economic prosperity is considered at the same time (confirming H1). This association is found in our two sets of rich countries, the global (full) sample, which is culturally more diverse, and the subset of European countries (confirming H3). There thus seems to be no need to confine the inequality hypothesis to the Western world. In light of the criticism that Wilkinson and Pickett especially received for disregarding cultural peculiarities (Saunders and Evans 2010; Snowdon 2010), this is a most relevant finding.
A second and at least partly theory-confirming finding concerns potential mediators. Our cross-sectional results lend some support, first of all, to the idea that status anxiety mediates between economic conditions and social ills. Two qualifications, however, are essential. While average levels of status anxiety are systematically higher in less affluent countries, they are not higher in more unequal ones, as The Spirit Level presumes. Secondly, our cross-sectional finding that the characteristics of social cohesion perform better as mediators suggests that it is the erosion of social life more generally which evokes health and social problems, not status anxiety specifically. Interestingly, this conclusion resonates well with the thrust of Wilkinson’s (1996, 1999) older works.
As regards the findings that challenge the inequality hypothesis and the spirit level theory, most importantly, changing income inequality does not cause changes in the number of social ills (disconfirming H4). Our study thus joins those that find a link between inequality and social ills cross-sectionally, but not longitudinally (e.g. Beckfield 2004; Leigh and Jencks 2007; Avendano 2012; Hu et al. 2015). Our results further indicate that economic prosperity is related to lower social ills—cross-sectionally in both subsets of rich nations, and longitudinally in Europe, in both cases while simultaneously considering the income distribution. This questions the exclusive focus on inequality that many scholars advocate. The positive impact of prosperity on societies is already observable at the beginning of the 2000s according to our data; and so it was not a new phenomenon that appeared after The Spirit Level was published. Seen in conjunction with the mounting evidence that individual quality of life is also better in richer countries (e.g., Hagerty and Veenhoven 2003; Deaton 2008; Delhey and Steckermeier 2016), it appears premature to declare economic resources ineffective for making lives and societies better, and even more so, as in the study at hand increases in economic prosperity over time decrease social ills, at least in Europe. In our data, the causal effect on social ills is actually exerted by economic prosperity, not by changes in the income distribution. Still, we do not want to gloss over the finding that in the European sub-sample the cross-sectional association between economic prosperity and social ills became weaker in later years of the period studied. This might mean that some rich societies are experiencing diminishing returns from economic resources, but still have positive returns—in particular in Europe—so “wealthier is healthier” (Biggs et al. 2010) is still a valid slogan for contemporary rich societies.
The mediation analysis could only be performed for Europe. Here, a genuinely new finding is that the same mechanisms that mediate in cross-sectional analysis between inequality and social ills also mediate between economic prosperity and social ills, namely satisfaction with social life and experienced social exclusion (largely in support of the cross-sectional part of H6); and further, that the mechanism prominently proposed by the spirit level theory—feelings of inferiority—only mediates the attenuating effect of economic prosperity. This suggests that prosperity exerts its positive effect on social ills by improving the social climate within societies (cf. Welzel 2013; Delhey and Dragolov 2016). Nevertheless, the longitudinal mediation analysis could not ultimately clarify the experienced quality-of-life mechanism through which economic prosperity has an effect on social ills. Future research, ideally based on larger case numbers, might yield more conclusive results on this issue.
Our results for economic prosperity raise the important question of why we unearthed a robust prosperity-social ills nexus when Wilkinson and Pickett did not. Re-running our analysis for the set of 21 countries from The Spirit Level, we find two explanations: country selection and methods. Indeed, there is no significant correlation between economic prosperity and our ISI index for the 21 countries in any of the years 2000–2015. In other words, it is Wilkinson and Pickett’s—disputable—compilation of countries which produces a non-correlation. Furthermore, when estimating pooled OLS regressions of ISI on inequality and prosperity for their 21 countries over the full period of 16 years, there is a robust social ills attenuating effect of prosperity, entirely in line with our results, but contrary to Wilkinson and Pickett. This demonstrates how unadvisable it is to draw conclusions based on zero-order correlations alone.
A limitation of our study is that the mediation analysis could only be performed for Europe. European societies are in the vanguard of value change toward self-expression values (Inglehart and Welzel 2005; Welzel 2013). Provided this peculiarity rubs off on the social production functions of these societies, we cannot rule out that the focus on Europe in the mediation analysis overemphasizes the role of social mediators and underemphasizes the role of material ones, such as economic strain. Moreover, a multi-level framework could be applied to the best-performing mechanisms from our analysis to determine whether they imply contextual effects of inequality and prosperity, or rather composition effects (for status anxiety, see, for example, Whelan and Layte 2014). Further research is also needed to explore potential cultural conditions that breed or prevent social ills. Although we have established that the impact of income inequality is not weaker in the culturally diverse global sample, it is still conceivable that cultural forces play their part in the generation of health and social problems.
In conclusion, while from a cross-sectional perspective the inequality hypothesis seems accurate but one-sided, in a longitudinal perspective it appears to be wrong. This news might be hard to digest for those who assume that creating a ‘better’ society is, definitely and primarily, a matter of income redistribution. For policymakers, our study instead suggests that economic prosperity should be prioritized over income redistribution as an instrument to achieving a less problem-ridden society. Naturally, tackling inequalities might still be of paramount importance for achieving other valuable goals, such as to enhance social justice.
Lower drinking frequencies among asexual individuals
Understanding Alcohol and Tobacco Consumption in Asexual Samples: A Mixed-Methods Approach. Caroline Bauer, Sasha L. Kaye, Lori A. Brotto. Archives of Sexual Behavior, December 20 2019. https://link.springer.com/article/10.1007/s10508-019-01570-4
Abstract: Existing research suggests significant differences in alcohol and tobacco consumption trends according to one’s sexual orientation. However, asexual people have not yet been included in these comparisons. In this mixed-methods, two-part study, we sought to compare group differences in alcohol and tobacco consumption among sexual orientations, focusing on asexual people, sexual people, and those in the “gray” area between asexual and sexual (i.e., “gray-asexual”). Data for Study 1 came from four British studies: National Surveys of Sexual Attitude and Lifestyles I, II, and III in 1990, 2000, and 2010 (NATSAL I, II, III) and Towards Better Sexual Health (TBSH) in 2000. Sample sizes for each study by gender are: NATSAL I—M: 1923 F: 3511; NATSAL II—M: 4604 F: 6031; NATSAL III—M: 6122 F: 7966; TBSH—M: 347 F: 552. Notably, asexual and gray-asexual respondents were found to consume significantly less alcohol and were more likely to abstain from drinking alcohol altogether, compared to allosexual respondents. Differences in tobacco consumption were only statistically significant for asexual respondents in two of three studies that included tobacco consumption. Each of the four studies also found that asexual and gray-asexual respondents were more likely to be non-drinkers (40.0–77.8%, asexual and 28.1–50.1% gray-asexual, non-drinkers, respectively) than allosexual respondents (10.2–27.2%, non-drinkers). Interviews conducted in Study 2 identified somatic, social, and psychological experiences and motivations that may shed light on the reasons for lower drinking frequencies among asexual individuals. Variability in alcohol consumption levels among asexual, lesbian, gay, and bisexual respondents, and the general population raises new questions about the motivations for why people consume alcohol.
Keywords: Asexuality Alcohol Tobacco LGBT Gray-asexuality Sexual attraction
Abstract: Existing research suggests significant differences in alcohol and tobacco consumption trends according to one’s sexual orientation. However, asexual people have not yet been included in these comparisons. In this mixed-methods, two-part study, we sought to compare group differences in alcohol and tobacco consumption among sexual orientations, focusing on asexual people, sexual people, and those in the “gray” area between asexual and sexual (i.e., “gray-asexual”). Data for Study 1 came from four British studies: National Surveys of Sexual Attitude and Lifestyles I, II, and III in 1990, 2000, and 2010 (NATSAL I, II, III) and Towards Better Sexual Health (TBSH) in 2000. Sample sizes for each study by gender are: NATSAL I—M: 1923 F: 3511; NATSAL II—M: 4604 F: 6031; NATSAL III—M: 6122 F: 7966; TBSH—M: 347 F: 552. Notably, asexual and gray-asexual respondents were found to consume significantly less alcohol and were more likely to abstain from drinking alcohol altogether, compared to allosexual respondents. Differences in tobacco consumption were only statistically significant for asexual respondents in two of three studies that included tobacco consumption. Each of the four studies also found that asexual and gray-asexual respondents were more likely to be non-drinkers (40.0–77.8%, asexual and 28.1–50.1% gray-asexual, non-drinkers, respectively) than allosexual respondents (10.2–27.2%, non-drinkers). Interviews conducted in Study 2 identified somatic, social, and psychological experiences and motivations that may shed light on the reasons for lower drinking frequencies among asexual individuals. Variability in alcohol consumption levels among asexual, lesbian, gay, and bisexual respondents, and the general population raises new questions about the motivations for why people consume alcohol.
Keywords: Asexuality Alcohol Tobacco LGBT Gray-asexuality Sexual attraction
Sweden: Approx 75pct of the top 1 men have a partner with income below the 90th percentile; for top 1 women, three-quarters of them have a partner with income above the 90th percentile, and about 30% have a partner who is also in the top 1pct
Women in top incomes – Evidence from Sweden 1971–2017. Anne Boschini, Kristin Gunnarsson, Jesper Roine. Journal of Public Economics, Volume 181, January 2020, 104115, https://doi.org/10.1016/j.jpubeco.2019.104115
Highlights
• Women have increased their presence in the top of the total income distribution.
• Women are still a minority (and more so higher up in the distribution).
• Top women have gained in labour incomes, while top men have gained in capital.
• Top men and women have converged in a number of dimensions.
• Family circumstances remain different for top men and women.
Abstract: Using yearly register data on the full population of Sweden we study gender differences in top incomes, down to the top 0.01 percentile group, over the period 1971–2017. We find that, while women are still a minority of the top decile, and typically make up a smaller share the higher up in the distribution we move, their presence has steadily increased in all top groups over the past half-century. At the beginning of the period, top income women relied more on capital incomes, but the rise in the share of top women is not due to the growing importance of capital. Instead, women have increased their presence in the top by gains in the top of labour incomes, while top income men have captured most of the growth in capital incomes. Studying gender differences in observable characteristics we find small gender differences in some respects, convergence in others, but also some important remaining differences. Overall, our results suggest that many findings in the top income literature have a clear gender component and that understanding gender equality in the top of the distribution requires studying not only earnings and labour market outcomes but also incomes from other sources, as well as family circumstances.
Keywords: Income inequalityWealth inequalityIncome distributionGender inequalityTop incomesCapital incomesRealized capital gains
7. Concluding discussion
This paper arrives at several conclusions about the evolution of women in the top of the income distribution in Sweden over the past fifty years. First, and most obviously, it shows that the presence of women in top incomes has increased significantly. There are still fewer women than men in top groups, and typically fewer the higher up we move in the distribution, but there has been a relatively steady rise over the whole period; from 12 to just below 30% in the top decile, from around 6 to 19% in the top 1 group, from 5 to 15 in the top 0.1 percentile group.
Even when focusing on the top 1 group (where capital incomes become important), this change has overwhelmingly been driven by women increasing their share of total labour income, while, on average, losing shares in the capital income distribution. This highlights the importance of studying the joint distribution of labour and capital to understand the changes in total income, especially in the very top.
When looking at the characteristics of top income women compared to men, they are not very different in terms of age and education (though women are, on average, more educated), and both groups become more and more similar over time. In terms of marital status, however, differences are large, especially at the beginning of the period. Around 1970 more than 90% of top 1 men were married, while this was the case for less than 50% of top 1 women. At that time more than 20% of women were widows (in the top 0.1 group almost 40%), while the share of widowers in the top 1 was close to zero. Over time the share of married men has gone down, the share of married women has increased, and today the marital status of top men and women are much more similar.
The largest remaining difference, however, seems to be in terms of “partner type”, especially concerning partner income. While the education levels of the top earners' partners, men and women alike, are similar – around 65% have tertiary education, 30% have secondary education, and only 5% have primary education – approximately three quarters of the top 1 men have a partner with income below the 90th percentile. For top 1 women, the opposite is true, three-quarters of them have a partner with income above the 90th percentile, and about 30% have a partner who is also in the top 1.
Trying to take all of these developments together, gives a picture of top income men and women being much more different in the 1970s than today. The typical top 1 woman had much higher capital incomes, and also owned more wealth in relation to the average top 1 man, but in return, she had significantly lower labour income. Over time capital has become more important in total incomes in general and also for top income men. For top income women, however, capital incomes have become relatively less important, both in relation to the population average and especially to the average top income man. In short, concerning income composition and wealth, top income men and women have become increasingly similar.
Why have women gained ground in terms of labour income? The short answer to the first part of this question is simply that more women have gradually risen to higher and higher-paying jobs. Exactly how this has happened requires further detailed study, but it seems to happen with a lag to women's education levels, since already well before the 1990s, when the increase really takes off, more women than men were graduating from Swedish universities. Also, one should recall that education, while certainly being important, is not everything when it comes to explaining top incomes. More than a third of top 1 earners, and about half of the top 10 earners do not have a tertiary education still today. The increasing share of women executives and senior managers, both in the private and public sector, is notable in the last decade or two. Moreover, tireless pro-active policy for gender equality in wages since the 1970s might finally have been fruitful. Despite these positive trends and also more men taking out parental leave after the introduction of so called “daddy quotas” (especially in high-educated high-income couples) and more women CEOs in listed companies than ever, there is also less positive evidence of both increasing gender wage gaps among executive managers after having their first child (see Keloharju et al., 2019, and more generally Kleven et al., 2019) and an increase in the divorce rate of particularly successful women managers and politicians (see Folke and Rickne, 2019). These findings are undoubtedly related to the partner choices of top men and top women. While the partners of top men and top women are increasingly similar in many dimensions, the large majority of top men's partners are still not pursuing a career of their own, as opposed to the majority of top women's partners.
Why have top income women gained less than top income men from the increased role of capital in the top? Again, answering the question in detail requires further study and is likely a complex web of connected developments. But our results give some important clues. First, as far as we can tell using tax data, the wealth difference between the average top income women and man has been shrinking over time. In 2007 – the last year when wealth was taxed – top income women had on average 1.5–2 times more wealth than the average corresponding man, down from more than 3 in the 1970s. At the same time, seen over the whole period, women have not lost ground in the top of the wealth distribution. The number of women in the top 1 of the wealth distribution has been between 30 and 40% over the whole period. This suggests that as the share of women has increased in the top, the composition of the average type of women has shifted in the direction of one with more labour income and less wealth. Furthermore, there are gender differences beyond wealth levels. In particular, our analysis of realized capital gains shows that top men, much more than top women, top-up their incomes with capital gains, and also that these are mainly based on financial assets. This suggests that top income men have more financial wealth than top income women (in line with what numerous government commissions and other studies find for gender differences in wealth holdings in general). These assets generate, not only an income when sold but also a flow of income in the form of dividends, which in turn have grown in importance in relation to other types of income. If top men have more financial assets than top income women, this has a relatively larger impact on their income growth. Finally, while capital incomes, in general, were adversely treated relative to labour before the great tax reform in 1991, the situation today is reversed. This has led to several different ways in which one can suspect that activities that, in a different tax system, would be taxed as labour are now categorized as capital. However, in this respect incentives are similar for men and women alike and to the extent that men would profit more than women from this requires further study.
Overall, the results in this paper suggest that to understand the gender dynamics of top incomes, we need to analyse the joint evolution of both labour and capital incomes, as well as family circumstances.
Highlights
• Women have increased their presence in the top of the total income distribution.
• Women are still a minority (and more so higher up in the distribution).
• Top women have gained in labour incomes, while top men have gained in capital.
• Top men and women have converged in a number of dimensions.
• Family circumstances remain different for top men and women.
Abstract: Using yearly register data on the full population of Sweden we study gender differences in top incomes, down to the top 0.01 percentile group, over the period 1971–2017. We find that, while women are still a minority of the top decile, and typically make up a smaller share the higher up in the distribution we move, their presence has steadily increased in all top groups over the past half-century. At the beginning of the period, top income women relied more on capital incomes, but the rise in the share of top women is not due to the growing importance of capital. Instead, women have increased their presence in the top by gains in the top of labour incomes, while top income men have captured most of the growth in capital incomes. Studying gender differences in observable characteristics we find small gender differences in some respects, convergence in others, but also some important remaining differences. Overall, our results suggest that many findings in the top income literature have a clear gender component and that understanding gender equality in the top of the distribution requires studying not only earnings and labour market outcomes but also incomes from other sources, as well as family circumstances.
Keywords: Income inequalityWealth inequalityIncome distributionGender inequalityTop incomesCapital incomesRealized capital gains
7. Concluding discussion
This paper arrives at several conclusions about the evolution of women in the top of the income distribution in Sweden over the past fifty years. First, and most obviously, it shows that the presence of women in top incomes has increased significantly. There are still fewer women than men in top groups, and typically fewer the higher up we move in the distribution, but there has been a relatively steady rise over the whole period; from 12 to just below 30% in the top decile, from around 6 to 19% in the top 1 group, from 5 to 15 in the top 0.1 percentile group.
Even when focusing on the top 1 group (where capital incomes become important), this change has overwhelmingly been driven by women increasing their share of total labour income, while, on average, losing shares in the capital income distribution. This highlights the importance of studying the joint distribution of labour and capital to understand the changes in total income, especially in the very top.
When looking at the characteristics of top income women compared to men, they are not very different in terms of age and education (though women are, on average, more educated), and both groups become more and more similar over time. In terms of marital status, however, differences are large, especially at the beginning of the period. Around 1970 more than 90% of top 1 men were married, while this was the case for less than 50% of top 1 women. At that time more than 20% of women were widows (in the top 0.1 group almost 40%), while the share of widowers in the top 1 was close to zero. Over time the share of married men has gone down, the share of married women has increased, and today the marital status of top men and women are much more similar.
The largest remaining difference, however, seems to be in terms of “partner type”, especially concerning partner income. While the education levels of the top earners' partners, men and women alike, are similar – around 65% have tertiary education, 30% have secondary education, and only 5% have primary education – approximately three quarters of the top 1 men have a partner with income below the 90th percentile. For top 1 women, the opposite is true, three-quarters of them have a partner with income above the 90th percentile, and about 30% have a partner who is also in the top 1.
Trying to take all of these developments together, gives a picture of top income men and women being much more different in the 1970s than today. The typical top 1 woman had much higher capital incomes, and also owned more wealth in relation to the average top 1 man, but in return, she had significantly lower labour income. Over time capital has become more important in total incomes in general and also for top income men. For top income women, however, capital incomes have become relatively less important, both in relation to the population average and especially to the average top income man. In short, concerning income composition and wealth, top income men and women have become increasingly similar.
Why have women gained ground in terms of labour income? The short answer to the first part of this question is simply that more women have gradually risen to higher and higher-paying jobs. Exactly how this has happened requires further detailed study, but it seems to happen with a lag to women's education levels, since already well before the 1990s, when the increase really takes off, more women than men were graduating from Swedish universities. Also, one should recall that education, while certainly being important, is not everything when it comes to explaining top incomes. More than a third of top 1 earners, and about half of the top 10 earners do not have a tertiary education still today. The increasing share of women executives and senior managers, both in the private and public sector, is notable in the last decade or two. Moreover, tireless pro-active policy for gender equality in wages since the 1970s might finally have been fruitful. Despite these positive trends and also more men taking out parental leave after the introduction of so called “daddy quotas” (especially in high-educated high-income couples) and more women CEOs in listed companies than ever, there is also less positive evidence of both increasing gender wage gaps among executive managers after having their first child (see Keloharju et al., 2019, and more generally Kleven et al., 2019) and an increase in the divorce rate of particularly successful women managers and politicians (see Folke and Rickne, 2019). These findings are undoubtedly related to the partner choices of top men and top women. While the partners of top men and top women are increasingly similar in many dimensions, the large majority of top men's partners are still not pursuing a career of their own, as opposed to the majority of top women's partners.
Why have top income women gained less than top income men from the increased role of capital in the top? Again, answering the question in detail requires further study and is likely a complex web of connected developments. But our results give some important clues. First, as far as we can tell using tax data, the wealth difference between the average top income women and man has been shrinking over time. In 2007 – the last year when wealth was taxed – top income women had on average 1.5–2 times more wealth than the average corresponding man, down from more than 3 in the 1970s. At the same time, seen over the whole period, women have not lost ground in the top of the wealth distribution. The number of women in the top 1 of the wealth distribution has been between 30 and 40% over the whole period. This suggests that as the share of women has increased in the top, the composition of the average type of women has shifted in the direction of one with more labour income and less wealth. Furthermore, there are gender differences beyond wealth levels. In particular, our analysis of realized capital gains shows that top men, much more than top women, top-up their incomes with capital gains, and also that these are mainly based on financial assets. This suggests that top income men have more financial wealth than top income women (in line with what numerous government commissions and other studies find for gender differences in wealth holdings in general). These assets generate, not only an income when sold but also a flow of income in the form of dividends, which in turn have grown in importance in relation to other types of income. If top men have more financial assets than top income women, this has a relatively larger impact on their income growth. Finally, while capital incomes, in general, were adversely treated relative to labour before the great tax reform in 1991, the situation today is reversed. This has led to several different ways in which one can suspect that activities that, in a different tax system, would be taxed as labour are now categorized as capital. However, in this respect incentives are similar for men and women alike and to the extent that men would profit more than women from this requires further study.
Overall, the results in this paper suggest that to understand the gender dynamics of top incomes, we need to analyse the joint evolution of both labour and capital incomes, as well as family circumstances.
Liberals exhibit zero-sum thinking when issues are framed in terms of upholding current social structures, conservatives when they are framed in terms of changing the status quo
The politics of zero-sum thinking: The relationship between political ideology and the belief that life is a zero-sum game. Shai Davidai, Martino Ongis. Science Advances Dec 18 2019, Vol. 5, no. 12, eaay3761. DOI: 10.1126/sciadv.aay3761
Abstract: The tendency to see life as zero-sum exacerbates political conflicts. Six studies (N = 3223) examine the relationship between political ideology and zero-sum thinking: the belief that one party’s gains can only be obtained at the expense of another party’s losses. We find that both liberals and conservatives view life as zero-sum when it benefits them to do so. Whereas conservatives exhibit zero-sum thinking when the status quo is challenged, liberals do so when the status quo is being upheld. Consequently, conservatives view social inequalities—where the status quo is frequently challenged—as zero-sum, but liberals view economic inequalities—where the status quo has remained relatively unchallenged in past decades—as such. Overall, these findings suggest potentially important ideological differences in perceptions of conflict—differences that are likely to have implications for understanding political divides in the United States and the difficulty of reaching bipartisan legislation.
DISCUSSION
In six studies, we found that conservatives are more prone than liberals to view challenges to the status quo as zero-sum but that the opposite is true when the status quo is preserved. In addition, we found that the same issue can elicit zero-sum thinking among liberals and conservatives, depending on whether it is framed in terms of maintaining or challenging the status quo. Whereas liberals exhibit zero-sum thinking when issues are framed in terms of upholding current social structures, conservatives exhibit zero-sum thinking when they are framed in terms of changing the status quo.
These findings highlight the role of ideology in shaping people’s views of life as zero-sum. Rather than being a stable mindset associated with a specific ideology or worldview (14), we found that zero-sum thinking is exhibited across the political spectrum. When thinking about threats to the status quo, conservatives are susceptible to the same reasoning patterns for which they criticize liberals when the status quo is maintained, and vice-versa. As a result, political polarization can stem from liberals’ and conservatives’ diverging assumptions about interest incompatibility and the zero-sum nature of social and economic relationships.
This suggests that how an issue is talked about can predictably influence whether it would elicit zero-sum thinking. As shown in study 4, emphasizing how the distribution of wealth preserves the status quo decreases zero-sum thinking among conservatives while increasing such thinking among liberals. In contrast, emphasizing how the accumulation of wealth can challenge existing social structures achieves the opposite result. Similarly, studies 5A and 5B show that framing an issue in terms of challenges to the status quo increases zero-sum thinking among conservatives, whereas framing an issue in terms of maintaining existing social structures increases such thinking among liberals. Since many policies preserve some aspects of the status quo while challenging other aspects of it, politicians and policy-makers can (for better or for worse) strategically frame contentious policies in a manner that either increases or decreases zero-sum thinking among their constituents. For instance, many policies may be more likely to attain bipartisan support if framed in a manner that emphasizes the status quo when presented to conservative voters but in a manner that emphasizes the challenges to the status quo when presented to more liberal-leaning voters. Similarly, emphasizing how a proposed policy is not zero-sum (e.g., emphasizing how similar policies in the past had no effect on the majority group or may have even benefitted it) may help increase support for it.
This suggests that people may be motivated to view life as zero-sum both to preserve the integrity of their own beliefs and to convince others about them. By emphasizing how maintaining (or challenging) the status quo hurts many more people than one’s opponents allow, people may become more confident in their own views and may be better situated to convince others of their position. Of course, it is possible that some people may adopt zero-sum rhetoric as a tool to convince others without genuinely accepting it as true. Although the current research focused on examining how ideological motivations relate to zero-sum thinking in general, it did not distinguish between when it is used as a way for bolstering one’s own convictions versus as a tool for convincing others. Future research could examine whether people adopt zero-sum thinking as mere rhetoric without truly believing in it and the extent to which it is effective to do so.
It is important to note that despite the significant relationship between zero-sum thinking and people’s political leanings, the tendency to view life as zero-sum involves beliefs that go beyond people’s political ideology. Although we found a significant and systemic relationship between political ideology and zero-sum thinking, there was substantial variance among both conservatives and liberals in their tendency to view life as zero-sum. Whereas the majority (73.4%) of liberal participants exhibited zero-sum thinking consistent with their ideological stance (i.e., viewing the current status quo as zero-sum but challenges to the status quo as not zero-sum), a substantial minority of liberals (26.4%) did not do so. Similarly, whereas most conservative participants (56.9%) exhibited “ideologically consistent” zero-sum thinking patterns (i.e., viewing challenges to the status quo as zero-sum but the existing status quo as not zero-sum), many conservatives (43.1%) did not do so (see fig. S1 and table S2).
Zero-sum thinking also has a unique effect in its ability to predict people’s attitudes about important societal issues above and beyond their political ideology. In two additional studies (studies S1 and S2), we examined the extent to which zero-sum thinking predicts attitudes about economic inequality and anti-immigration policies. In the first study, we measured, in a counterbalanced order, participants’ tendency to view wealth as a zero-sum resource (14) and their attitudes regarding inequality using the Support for Economic Inequality Scale (32). As predicted, we found that zero-sum thinking was negatively related to the extent to which participants viewed economic inequality favorably [r(100) = −0.659, P < 0.0001]. The more participants believed that wealth was a zero-sum resource, the more they opposed inequality. A multiple regression analysis predicting attitudes toward inequality from political ideology and the tendency to view wealth as zero-sum found that zero-sum thinking remained a significant predictor of support for inequality beyond participants’ ideology [βzero-sum thinking = −0.531, t(98) = −6.69, P < 0.0001; βideology = 0.269, t(98) = 4.54, P < 0.0001]. Moreover, including zero-sum thinking as a predictor in this model increased the explained variance in attitudes from R2 = 32% to R2 = 53%.
We replicated this finding in a second study, where we examined the relationship between zero-sum thinking and attitudes toward anti-immigration policies (study S2). In this study, we measured, in a counterbalanced order, participants’ tendency to view immigration as zero-sum, their support for various anti-immigration policies (e.g., building a wall in the U.S.-Mexico border, indefinitely detaining illegal immigrants until deportation), their prejudice against Mexican immigrants, and their tendency to blatantly dehumanize immigrants as savage, aggressive, and lacking basic morals. As expected, we found that zero-sum thinking significantly predicted support for tough anti-immigration policies [r(102) = 0.594, P < 0.0001]. The more participants viewed immigration as zero-sum, the more they supported taking a tough stance against immigration. We found that viewing immigration as zero-sum uniquely predicted support for anti-immigration policies [β = 0.551, t(98) = 6.24, P < 0.0001] above and beyond political ideology [β = 0.556, t(100) = 7.95, P < 0.0001], and including zero-sum thinking in the model increased the explained variance in attitudes from R2 = 45% to R2 = 60%. Furthermore, zero-sum thinking remained a significant predictor of support for anti-immigration policies [β = 0.333, t(98) = 3.85, P = 0.0002] even when we included in the model participants’ prejudice against Mexican immigrants [β = 0.012, t(98) = 2.19, P = 0.031] and their tendency to blatantly dehumanize them [β = 0.816, t(98) = 6.26, P < 0.0001]. Thus, despite the significant relationship between zero-sum thinking and political ideology, viewing life as zero-sum uniquely predicts attitudes about important social issues beyond people’s political leanings. Exploring when and why people view life as zero-sum can enrich our understanding of their attitudes beyond merely knowing their political ideology.
Future research would benefit from examining additional factors that, together with ideology, are related to zero-sum thinking. First, people may be more prone to view life as zero-sum after experiencing personal hardships. For example, it is possible that white applicants who fail to get into college are more likely to view racial relations as zero-sum than admitted applicants, that male candidates who do not get hired are more likely to view gender relations as zero-sum than hired candidates, that unemployed Americans are more likely to believe that immigrants take jobs away from U.S. citizens than employed Americans, and so forth. More generally, people may be especially prone to zero-sum thinking when comparing themselves to better-off others, which can help explain why upward comparisons exacerbate negative experiences (33–35). If people view their own (worse off) outcomes as having been caused by others’ better outcomes, they can then blame others for their own circumstances and resent their good fortune.
Cultural differences may also influence zero-sum thinking. The relationship between ideology and zero-sum thinking about the distribution of wealth varies considerably between countries. Whereas conservatism is negatively related to zero-sum thinking in most of the countries included in the World Values Survey (27), the strength and significance of this relationship varies substantially. Of the 55 countries in which respondents indicated whether they viewed the distribution of wealth as zero-sum, the relationship between ideology and zero-sum thinking was significantly or marginally negative in 31 countries, insignificantly negative (P > 0.10) in 16 countries, insignificantly positive in 7 countries, and significantly positive in only 1 country (Fig. 5). Although ideology is clearly related to zero-sum thinking, cultural factors surely influence the extent to which people see life as zero-sum.
[Fig. 5 The relationship between political ideology and zero-sum thinking about the distribution of wealth across 55 countries in the sixth wave of the World Value Survey.]
The current research offers insight into how ideology is related to people’s interpretation of the world and may further our understanding of partisan divides in the United States. Although liberals and conservatives often agree on many economic and social goals, they tend to disagree on how to best achieve them. For example, people across the political spectrum share similar views regarding what an ideal society would look like in terms of economic inequality and social mobility (36, 37) but disagree on how to create such a society. Although these partisan differences typically stem from beliefs about who stands to win or lose from any given policy, our findings suggest that these beliefs are unexpectedly malleable. Paying closer attention to how we discuss politically divisive issues can be the first step in bridging this partisan divide.
Abstract: The tendency to see life as zero-sum exacerbates political conflicts. Six studies (N = 3223) examine the relationship between political ideology and zero-sum thinking: the belief that one party’s gains can only be obtained at the expense of another party’s losses. We find that both liberals and conservatives view life as zero-sum when it benefits them to do so. Whereas conservatives exhibit zero-sum thinking when the status quo is challenged, liberals do so when the status quo is being upheld. Consequently, conservatives view social inequalities—where the status quo is frequently challenged—as zero-sum, but liberals view economic inequalities—where the status quo has remained relatively unchallenged in past decades—as such. Overall, these findings suggest potentially important ideological differences in perceptions of conflict—differences that are likely to have implications for understanding political divides in the United States and the difficulty of reaching bipartisan legislation.
DISCUSSION
In six studies, we found that conservatives are more prone than liberals to view challenges to the status quo as zero-sum but that the opposite is true when the status quo is preserved. In addition, we found that the same issue can elicit zero-sum thinking among liberals and conservatives, depending on whether it is framed in terms of maintaining or challenging the status quo. Whereas liberals exhibit zero-sum thinking when issues are framed in terms of upholding current social structures, conservatives exhibit zero-sum thinking when they are framed in terms of changing the status quo.
These findings highlight the role of ideology in shaping people’s views of life as zero-sum. Rather than being a stable mindset associated with a specific ideology or worldview (14), we found that zero-sum thinking is exhibited across the political spectrum. When thinking about threats to the status quo, conservatives are susceptible to the same reasoning patterns for which they criticize liberals when the status quo is maintained, and vice-versa. As a result, political polarization can stem from liberals’ and conservatives’ diverging assumptions about interest incompatibility and the zero-sum nature of social and economic relationships.
This suggests that how an issue is talked about can predictably influence whether it would elicit zero-sum thinking. As shown in study 4, emphasizing how the distribution of wealth preserves the status quo decreases zero-sum thinking among conservatives while increasing such thinking among liberals. In contrast, emphasizing how the accumulation of wealth can challenge existing social structures achieves the opposite result. Similarly, studies 5A and 5B show that framing an issue in terms of challenges to the status quo increases zero-sum thinking among conservatives, whereas framing an issue in terms of maintaining existing social structures increases such thinking among liberals. Since many policies preserve some aspects of the status quo while challenging other aspects of it, politicians and policy-makers can (for better or for worse) strategically frame contentious policies in a manner that either increases or decreases zero-sum thinking among their constituents. For instance, many policies may be more likely to attain bipartisan support if framed in a manner that emphasizes the status quo when presented to conservative voters but in a manner that emphasizes the challenges to the status quo when presented to more liberal-leaning voters. Similarly, emphasizing how a proposed policy is not zero-sum (e.g., emphasizing how similar policies in the past had no effect on the majority group or may have even benefitted it) may help increase support for it.
This suggests that people may be motivated to view life as zero-sum both to preserve the integrity of their own beliefs and to convince others about them. By emphasizing how maintaining (or challenging) the status quo hurts many more people than one’s opponents allow, people may become more confident in their own views and may be better situated to convince others of their position. Of course, it is possible that some people may adopt zero-sum rhetoric as a tool to convince others without genuinely accepting it as true. Although the current research focused on examining how ideological motivations relate to zero-sum thinking in general, it did not distinguish between when it is used as a way for bolstering one’s own convictions versus as a tool for convincing others. Future research could examine whether people adopt zero-sum thinking as mere rhetoric without truly believing in it and the extent to which it is effective to do so.
It is important to note that despite the significant relationship between zero-sum thinking and people’s political leanings, the tendency to view life as zero-sum involves beliefs that go beyond people’s political ideology. Although we found a significant and systemic relationship between political ideology and zero-sum thinking, there was substantial variance among both conservatives and liberals in their tendency to view life as zero-sum. Whereas the majority (73.4%) of liberal participants exhibited zero-sum thinking consistent with their ideological stance (i.e., viewing the current status quo as zero-sum but challenges to the status quo as not zero-sum), a substantial minority of liberals (26.4%) did not do so. Similarly, whereas most conservative participants (56.9%) exhibited “ideologically consistent” zero-sum thinking patterns (i.e., viewing challenges to the status quo as zero-sum but the existing status quo as not zero-sum), many conservatives (43.1%) did not do so (see fig. S1 and table S2).
Zero-sum thinking also has a unique effect in its ability to predict people’s attitudes about important societal issues above and beyond their political ideology. In two additional studies (studies S1 and S2), we examined the extent to which zero-sum thinking predicts attitudes about economic inequality and anti-immigration policies. In the first study, we measured, in a counterbalanced order, participants’ tendency to view wealth as a zero-sum resource (14) and their attitudes regarding inequality using the Support for Economic Inequality Scale (32). As predicted, we found that zero-sum thinking was negatively related to the extent to which participants viewed economic inequality favorably [r(100) = −0.659, P < 0.0001]. The more participants believed that wealth was a zero-sum resource, the more they opposed inequality. A multiple regression analysis predicting attitudes toward inequality from political ideology and the tendency to view wealth as zero-sum found that zero-sum thinking remained a significant predictor of support for inequality beyond participants’ ideology [βzero-sum thinking = −0.531, t(98) = −6.69, P < 0.0001; βideology = 0.269, t(98) = 4.54, P < 0.0001]. Moreover, including zero-sum thinking as a predictor in this model increased the explained variance in attitudes from R2 = 32% to R2 = 53%.
We replicated this finding in a second study, where we examined the relationship between zero-sum thinking and attitudes toward anti-immigration policies (study S2). In this study, we measured, in a counterbalanced order, participants’ tendency to view immigration as zero-sum, their support for various anti-immigration policies (e.g., building a wall in the U.S.-Mexico border, indefinitely detaining illegal immigrants until deportation), their prejudice against Mexican immigrants, and their tendency to blatantly dehumanize immigrants as savage, aggressive, and lacking basic morals. As expected, we found that zero-sum thinking significantly predicted support for tough anti-immigration policies [r(102) = 0.594, P < 0.0001]. The more participants viewed immigration as zero-sum, the more they supported taking a tough stance against immigration. We found that viewing immigration as zero-sum uniquely predicted support for anti-immigration policies [β = 0.551, t(98) = 6.24, P < 0.0001] above and beyond political ideology [β = 0.556, t(100) = 7.95, P < 0.0001], and including zero-sum thinking in the model increased the explained variance in attitudes from R2 = 45% to R2 = 60%. Furthermore, zero-sum thinking remained a significant predictor of support for anti-immigration policies [β = 0.333, t(98) = 3.85, P = 0.0002] even when we included in the model participants’ prejudice against Mexican immigrants [β = 0.012, t(98) = 2.19, P = 0.031] and their tendency to blatantly dehumanize them [β = 0.816, t(98) = 6.26, P < 0.0001]. Thus, despite the significant relationship between zero-sum thinking and political ideology, viewing life as zero-sum uniquely predicts attitudes about important social issues beyond people’s political leanings. Exploring when and why people view life as zero-sum can enrich our understanding of their attitudes beyond merely knowing their political ideology.
Future research would benefit from examining additional factors that, together with ideology, are related to zero-sum thinking. First, people may be more prone to view life as zero-sum after experiencing personal hardships. For example, it is possible that white applicants who fail to get into college are more likely to view racial relations as zero-sum than admitted applicants, that male candidates who do not get hired are more likely to view gender relations as zero-sum than hired candidates, that unemployed Americans are more likely to believe that immigrants take jobs away from U.S. citizens than employed Americans, and so forth. More generally, people may be especially prone to zero-sum thinking when comparing themselves to better-off others, which can help explain why upward comparisons exacerbate negative experiences (33–35). If people view their own (worse off) outcomes as having been caused by others’ better outcomes, they can then blame others for their own circumstances and resent their good fortune.
Cultural differences may also influence zero-sum thinking. The relationship between ideology and zero-sum thinking about the distribution of wealth varies considerably between countries. Whereas conservatism is negatively related to zero-sum thinking in most of the countries included in the World Values Survey (27), the strength and significance of this relationship varies substantially. Of the 55 countries in which respondents indicated whether they viewed the distribution of wealth as zero-sum, the relationship between ideology and zero-sum thinking was significantly or marginally negative in 31 countries, insignificantly negative (P > 0.10) in 16 countries, insignificantly positive in 7 countries, and significantly positive in only 1 country (Fig. 5). Although ideology is clearly related to zero-sum thinking, cultural factors surely influence the extent to which people see life as zero-sum.
[Fig. 5 The relationship between political ideology and zero-sum thinking about the distribution of wealth across 55 countries in the sixth wave of the World Value Survey.]
The current research offers insight into how ideology is related to people’s interpretation of the world and may further our understanding of partisan divides in the United States. Although liberals and conservatives often agree on many economic and social goals, they tend to disagree on how to best achieve them. For example, people across the political spectrum share similar views regarding what an ideal society would look like in terms of economic inequality and social mobility (36, 37) but disagree on how to create such a society. Although these partisan differences typically stem from beliefs about who stands to win or lose from any given policy, our findings suggest that these beliefs are unexpectedly malleable. Paying closer attention to how we discuss politically divisive issues can be the first step in bridging this partisan divide.
Movie theater context enhances the valuation and aesthetic experience of watching films, compared to watching at home
Fröber, K., & Thomaschke, R. (2019). In the dark cube: Movie theater context enhances the valuation and aesthetic experience of watching films. Psychology of Aesthetics, Creativity, and the Arts, Dec 2019, https://doi.org/10.1037/aca0000295
Abstract: There is a worldwide increase in feature film releases each year. While a theatrical release is still the primary release form, more and more films are watched via online streaming in home cinemas. Watching films at home is unquestionably high in convenience, but an understudied question is, how this shift in context—from the movie theater to the home cinema—affects the cinematic experience while watching a feature film. To test this, aesthetic emotions and the overall judgment of the cinematic experience were compared between watching a film in a movie theater or home cinema. In line with cognitive models of art appreciation, it was found that a movie theater context leads to a stronger emotional experience and a more favorable judgment. Only boredom was felt stronger in the home cinema. This movie theater effect persisted during a second viewing, regardless of context. These results have theoretical and practical implications for empirical aesthetics, movie fans, and the movie industry.
Abstract: There is a worldwide increase in feature film releases each year. While a theatrical release is still the primary release form, more and more films are watched via online streaming in home cinemas. Watching films at home is unquestionably high in convenience, but an understudied question is, how this shift in context—from the movie theater to the home cinema—affects the cinematic experience while watching a feature film. To test this, aesthetic emotions and the overall judgment of the cinematic experience were compared between watching a film in a movie theater or home cinema. In line with cognitive models of art appreciation, it was found that a movie theater context leads to a stronger emotional experience and a more favorable judgment. Only boredom was felt stronger in the home cinema. This movie theater effect persisted during a second viewing, regardless of context. These results have theoretical and practical implications for empirical aesthetics, movie fans, and the movie industry.
There is a double standard for making forecasts about self vs others: Justice is a more fundamental motive in forecasts about others, & wishful thinking a more fundamental motive in forecasts about the self
Mata, A., & Simão, C. (2019). Karmic forecasts: The role of justice in forecasts about self and others. Motivation Science, Dec 1019. https://doi.org/10.1037/mot0000162
Abstract: Three studies show that people make karmic forecasts, expecting good things to come to those who perform good deeds, and predicting bad outcomes for wrongdoers. However, these justice-based forecasts only apply to others; when making forecasts about themselves, people tend to make optimistic predictions, regardless of whether they consider good or bad things that they did. This pattern emerged for both forecasts about the likelihood of experiencing positive versus negative events, as well as affective forecasts about how people will feel upon experiencing such events. Thus, there is a double standard for making forecasts about self versus others, with justice being a more fundamental motive in forecasts about others, and wishful thinking being a more fundamental motive in forecasts about the self.
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From a previous publication... Mata, A., Simão, C., Farias, A. R., & Steimer, A. (2018, July 12). Forecasting the Duration of Emotions: A Motivational Account and Self-Other Differences. Emotion, http://dx.doi.org/10.1037/emo0000455
General Discussion
Six studies provided systematic evidence for the influence of
wishful thinking on the estimated duration of emotions. In Studies
1 through 3, desirable emotions triggered by positive events were
expected to last longer than undesirable emotions triggered by
negative events, but this difference only held for the self, not for
other people. Additionally, Study 2 showed that desirability mediated the effect of event valence on expected emotional duration
only for the self, not for other people. Studies 4 through 5 directly
tested our motivational account: Study 4 revealed that manipulating the desirability of certain emotions (happiness depicted as less
desirable, and sadness as more desirable) influenced the forecasted
duration of those emotions. In Study 5 the same positive–negative
asymmetry that was found for the self in Studies 1 through 4 was
also observed for another person that was described as likable, but
not when the other person was described in a negative manner.
And Study 6 replicated the pattern of more optimistic forecasts
about the self versus about others, for a wide variety of emotions,
and importantly, both for positive and negative emotions: To the
extent that an emotion is desirable, be it positive or negative in
valence, people expect it to last longer for themselves than for
others. These results suggest that desirability is one of the factors
driving the forecasts that people make about how long they will
experience certain emotions: People expect themselves (or others)
to feel certain emotions for a longer while to the extent that that is
desirable. This research extends the body of findings in the optimism literature by showing that people not only expect to experience more positive events than negative ones, but they also
expect the positive emotions produced by the former to last longer
than the negative emotions resulting from the latter.
Differences From Previous Research
The vast majority of research on affective forecasting has focused on demonstrating people’s inability to accurately predict
future emotional reactions at a certain point of time in the future:
People overestimate their future emotional reactions to both positive and negative events, as compared with how they actually feel
when the time comes. In the present studies, we did not compare
forecasts against experience, but rather assessed in a direct way
estimates of emotion duration. This methodology revealed two
novel findings: first, people expect positive emotions to last longer
than negative ones, and second, this asymmetric pattern only holds
for themselves, not others.
At first, it might appear that our results contradict previous
findings in this field (see Wilson & Gilbert, 2003, for a review).
Indeed, previous studies typically show that the overestimation of
experienced affect when compared with forecasts is greater for
negative versus positive emotions, whereas the present studies
show that people forecast a longer duration for positive versus
negative emotions. This apparent discrepancy can be resolved if
we consider (1) differences in method and (2) differences in the
time course of positive versus negative emotions.
First, differences in method: Typical studies of affective forecasting compare the intensity (and not the duration) of forecasted
(T1) versus experienced (T2) emotions. The present studies, on the
other hand, compared forecasts (T1) about the duration of positive
versus negative emotions (as well as the critical social comparison
dimension: self vs. others). Thus, the present research cannot and
does not make claims about the accuracy of predictions, as it
neither tests nor shows whether there is overestimation about
positive versus negative emotions, but simply demonstrates that
positive emotions are estimated to last longer than negative ones.
There is a difference in the measures and contrasts that are relevant
to test different hypotheses: Research examining the impact bias is
concerned with comparing forecasts of intensity against intensity
of experience, whereas the present research is concerned with
testing a desirability bias in forecasts about the duration of positive
versus negative emotions.
More importantly, research on emotions and how they develop
across time reveals a crucial clue that reconciles our findings with
those of previous studies: People might predict a longer duration
for positive versus negative events (as was consistently observed
in the present studies), and yet overestimate the impact of negative
events to a greater extent, provided that negative emotions fade
more quickly than positive ones. Indeed, there is a great deal of
evidence suggesting that negative emotions fade more quickly than
positive ones (Ritchie, Skowronski, Hartnett, Wells, & Walker,
2009; Ritchie et al., 2006; Skowronski, Gibbons, Vogl, & Walker,
2004; Walker, Skowronski, Gibbons, Vogl, & Ritchie, 2009;
Walker, Skowronski, Gibbons, Vogl, & Thompson, 2003; Walker,
Skowronski, & Thompson, 2003; Walker, Vogl, & Thompson,
1997). This is known as the fading affect bias (Walker et al.,
2003), and it is explained by strategic memory rehearsal. For
instance, Walker et al. (2009) document different types of memory
rehearsal that prevent emotions from fading, such as “rehearsal for
maintaining memory for events” or “rehearsal for the purpose of
re-experiencing the emotion associated with the event”, and they
find that (1) memory rehearsal is more frequent for positive events
than for negative ones and (2) events that are frequently rehearsed
are associated with less fading of emotions. Thus, to the extent that
positive emotions are kept alive for longer, forecasts that such
emotions will last long might not be off target. On the other hand,
to the extent that negative emotions fade more quickly (for instance via coping mechanisms such as reappraisal or memory
suppression), people might err by a greater margin in their forecasts, such that they predict that they will have a certain duration
(though shorter than positive emotions—the optimistic bias that
we found), but fail to take into account the immune system
(immune neglect; Gilbert et al., 1998) and therefore fail to see how
they will last for much shorter than they predicted.
For instance, forecasters might predict that the duration of
positive emotions is x times longer than that of negative ones, but
to the extent that the difference in decay for negative versus positive
emotions is larger than x, we might observe both an optimistic bias in
predictions (predictions at T1: positive negative) and a greater
impact bias for negative versus positive emotions (comparing
predictions at T1 to experiences at T2). Thus, the self-protective
and enhancing nature of memory helps to both legitimize the
asymmetry that we found (i.e., forecasters might be accurate in
predicting that positive emotions last longer than negative ones)
and reconcile it with the typical findings in affective forecasting
research: For positive emotions, people actively work to keep them
alive, whereas for negative emotions they work at suppressing
them, and so it will be easier to overestimate the duration/impact
of negative emotions.
In addition to the relevance of studying forecasts about emotion
duration, we also believe that the asymmetry in affective forecasting that we find for self versus for others might be important in
explaining well-documented effects, such as the difference in
choice (for self) versus advice (for others), as we explain in the
following text.
Moreover, this research goes beyond the valence dimension that
previous research has focused on, by showing that regardless of
whether certain emotions are positive or negative, to the extent that
it is desirable to experience them in a certain situation, forecasters
predict that they will feel such emotions for a long time (even
clearly negative-valenced emotions such as shame, envy or disgust; Study 6). In this sense, these results do not allow for a simple
portrayal of our findings as merely showing that people make
optimistic predictions. In Study 6, it is not easy to define optimism.
What is more optimistic: to expect a positive emotion that is
nevertheless undesirable (or at least socially proscribed), or to
expect a desirable emotion that is nevertheless negative and upsetting? Indeed, it has recently been suggested that:
Abstract: Three studies show that people make karmic forecasts, expecting good things to come to those who perform good deeds, and predicting bad outcomes for wrongdoers. However, these justice-based forecasts only apply to others; when making forecasts about themselves, people tend to make optimistic predictions, regardless of whether they consider good or bad things that they did. This pattern emerged for both forecasts about the likelihood of experiencing positive versus negative events, as well as affective forecasts about how people will feel upon experiencing such events. Thus, there is a double standard for making forecasts about self versus others, with justice being a more fundamental motive in forecasts about others, and wishful thinking being a more fundamental motive in forecasts about the self.
-------------------------------------------------------------------------------------------------------------------
From a previous publication... Mata, A., Simão, C., Farias, A. R., & Steimer, A. (2018, July 12). Forecasting the Duration of Emotions: A Motivational Account and Self-Other Differences. Emotion, http://dx.doi.org/10.1037/emo0000455
Abstract: This research investigates the forecasts that people make about the duration of positive versus negative emotions, and tests whether these forecasts differ for self versus for others. Consistent with a motivated thinking framework, six studies show that people make optimistic, asymmetric forecasts that positive emotions will last longer than negative ones. However, for other people, wishful thinking is absent, and therefore people make less optimistic, more symmetric forecasts. Potential implications of these motivated forecasts and self–other differences are discussed.
General Discussion
Six studies provided systematic evidence for the influence of
wishful thinking on the estimated duration of emotions. In Studies
1 through 3, desirable emotions triggered by positive events were
expected to last longer than undesirable emotions triggered by
negative events, but this difference only held for the self, not for
other people. Additionally, Study 2 showed that desirability mediated the effect of event valence on expected emotional duration
only for the self, not for other people. Studies 4 through 5 directly
tested our motivational account: Study 4 revealed that manipulating the desirability of certain emotions (happiness depicted as less
desirable, and sadness as more desirable) influenced the forecasted
duration of those emotions. In Study 5 the same positive–negative
asymmetry that was found for the self in Studies 1 through 4 was
also observed for another person that was described as likable, but
not when the other person was described in a negative manner.
And Study 6 replicated the pattern of more optimistic forecasts
about the self versus about others, for a wide variety of emotions,
and importantly, both for positive and negative emotions: To the
extent that an emotion is desirable, be it positive or negative in
valence, people expect it to last longer for themselves than for
others. These results suggest that desirability is one of the factors
driving the forecasts that people make about how long they will
experience certain emotions: People expect themselves (or others)
to feel certain emotions for a longer while to the extent that that is
desirable. This research extends the body of findings in the optimism literature by showing that people not only expect to experience more positive events than negative ones, but they also
expect the positive emotions produced by the former to last longer
than the negative emotions resulting from the latter.
Differences From Previous Research
The vast majority of research on affective forecasting has focused on demonstrating people’s inability to accurately predict
future emotional reactions at a certain point of time in the future:
People overestimate their future emotional reactions to both positive and negative events, as compared with how they actually feel
when the time comes. In the present studies, we did not compare
forecasts against experience, but rather assessed in a direct way
estimates of emotion duration. This methodology revealed two
novel findings: first, people expect positive emotions to last longer
than negative ones, and second, this asymmetric pattern only holds
for themselves, not others.
At first, it might appear that our results contradict previous
findings in this field (see Wilson & Gilbert, 2003, for a review).
Indeed, previous studies typically show that the overestimation of
experienced affect when compared with forecasts is greater for
negative versus positive emotions, whereas the present studies
show that people forecast a longer duration for positive versus
negative emotions. This apparent discrepancy can be resolved if
we consider (1) differences in method and (2) differences in the
time course of positive versus negative emotions.
First, differences in method: Typical studies of affective forecasting compare the intensity (and not the duration) of forecasted
(T1) versus experienced (T2) emotions. The present studies, on the
other hand, compared forecasts (T1) about the duration of positive
versus negative emotions (as well as the critical social comparison
dimension: self vs. others). Thus, the present research cannot and
does not make claims about the accuracy of predictions, as it
neither tests nor shows whether there is overestimation about
positive versus negative emotions, but simply demonstrates that
positive emotions are estimated to last longer than negative ones.
There is a difference in the measures and contrasts that are relevant
to test different hypotheses: Research examining the impact bias is
concerned with comparing forecasts of intensity against intensity
of experience, whereas the present research is concerned with
testing a desirability bias in forecasts about the duration of positive
versus negative emotions.
More importantly, research on emotions and how they develop
across time reveals a crucial clue that reconciles our findings with
those of previous studies: People might predict a longer duration
for positive versus negative events (as was consistently observed
in the present studies), and yet overestimate the impact of negative
events to a greater extent, provided that negative emotions fade
more quickly than positive ones. Indeed, there is a great deal of
evidence suggesting that negative emotions fade more quickly than
positive ones (Ritchie, Skowronski, Hartnett, Wells, & Walker,
2009; Ritchie et al., 2006; Skowronski, Gibbons, Vogl, & Walker,
2004; Walker, Skowronski, Gibbons, Vogl, & Ritchie, 2009;
Walker, Skowronski, Gibbons, Vogl, & Thompson, 2003; Walker,
Skowronski, & Thompson, 2003; Walker, Vogl, & Thompson,
1997). This is known as the fading affect bias (Walker et al.,
2003), and it is explained by strategic memory rehearsal. For
instance, Walker et al. (2009) document different types of memory
rehearsal that prevent emotions from fading, such as “rehearsal for
maintaining memory for events” or “rehearsal for the purpose of
re-experiencing the emotion associated with the event”, and they
find that (1) memory rehearsal is more frequent for positive events
than for negative ones and (2) events that are frequently rehearsed
are associated with less fading of emotions. Thus, to the extent that
positive emotions are kept alive for longer, forecasts that such
emotions will last long might not be off target. On the other hand,
to the extent that negative emotions fade more quickly (for instance via coping mechanisms such as reappraisal or memory
suppression), people might err by a greater margin in their forecasts, such that they predict that they will have a certain duration
(though shorter than positive emotions—the optimistic bias that
we found), but fail to take into account the immune system
(immune neglect; Gilbert et al., 1998) and therefore fail to see how
they will last for much shorter than they predicted.
For instance, forecasters might predict that the duration of
positive emotions is x times longer than that of negative ones, but
to the extent that the difference in decay for negative versus positive
emotions is larger than x, we might observe both an optimistic bias in
predictions (predictions at T1: positive negative) and a greater
impact bias for negative versus positive emotions (comparing
predictions at T1 to experiences at T2). Thus, the self-protective
and enhancing nature of memory helps to both legitimize the
asymmetry that we found (i.e., forecasters might be accurate in
predicting that positive emotions last longer than negative ones)
and reconcile it with the typical findings in affective forecasting
research: For positive emotions, people actively work to keep them
alive, whereas for negative emotions they work at suppressing
them, and so it will be easier to overestimate the duration/impact
of negative emotions.
In addition to the relevance of studying forecasts about emotion
duration, we also believe that the asymmetry in affective forecasting that we find for self versus for others might be important in
explaining well-documented effects, such as the difference in
choice (for self) versus advice (for others), as we explain in the
following text.
Moreover, this research goes beyond the valence dimension that
previous research has focused on, by showing that regardless of
whether certain emotions are positive or negative, to the extent that
it is desirable to experience them in a certain situation, forecasters
predict that they will feel such emotions for a long time (even
clearly negative-valenced emotions such as shame, envy or disgust; Study 6). In this sense, these results do not allow for a simple
portrayal of our findings as merely showing that people make
optimistic predictions. In Study 6, it is not easy to define optimism.
What is more optimistic: to expect a positive emotion that is
nevertheless undesirable (or at least socially proscribed), or to
expect a desirable emotion that is nevertheless negative and upsetting? Indeed, it has recently been suggested that:
biases in emotion attribution might not always reflect a desire to view one’s self as experiencing more positively valenced emotions, but should flexibly tune individuals towards the belief that they experience more desirable emotions, irrespective of valence. This is also a natural prediction of theories of motivated cognition (e.g., Hughes & Zaki, 2015). Future work should test this prediction by varying the goal consistency of emotions across a variety of contexts. (Ong, Goodman, & Zaki, 2018, p. 124)Study 6 offers precisely this test.