Assessing U.S. Racial and Gender Differences in Happiness, 1972–2016: An Intersectional Approach

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Abstract

This study assesses trends and differentials in happiness among the U.S. population. Using data from the General Social Survey, 1972–2016 and the intersectionality paradigm to guide this work, I find that happiness differentials across gender and race are generally converging; however, patterns are quite complex and contingent on group membership (i.e. gender, race). Black women for instance, present a consistent pattern of improvement in happiness across decades, while White women display a persistent pattern of decline. In contrast, Black men experienced a discernable pattern of improvement in happiness between the 1970s and 1990s, followed by a leveling off in the early-2000s. White men experienced moderate gains in happiness between the 1970s and 1990s, but after the Great Recession/Obama Era, White male happiness followed a pattern of unprecedented decline, with the “happiness advantage” they once enjoyed (as a group) over Black men and women largely vanishing. In fact, although advantaged White men in the general population (i.e. financially satisfied) were about as happy as their White female and African–American female peers after the Great Recession, disadvantaged White men who were financially dissatisfied were less likely to report the same sentiment when compared to their White female and Black female peers who were similarly disadvantaged. Taking these patterns in account, I conclude with a discussion of what these patterns demonstrate regarding the changing nature of racial and gender inequality in the United States, past and present.

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Fig. 1
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Change history

  • 02 January 2020

    In the original publication, Table 1 was published incorrectly. The correct Table 1 is given below. The original article has been corrected.

Notes

  1. 1.

    It should be noted that although I am assessing “sex differences” in happiness (comparing self-identified males and females), per convention, I retain the language “gender” and “gender differences” consistent with the work of intersectional scholars (i.e. gender, race and class) and published work on temporal patterns in happiness using the General Social Survey (see Blanchflower and Oswald 2004; Coverdill et al. 2011; Hughes and Thomas 1998; Schnittker 2008; Stevenson and Wolfers 2009).

  2. 2.

    Supplementary analysis using the fully interactive intersectional model (race × gender × year) as opposed to the simplified intersectional model presented here (e.g. black men × year), demonstrates that coefficients are nearly identical across models, and the general pattern presented here does not differ depending on the model of choice.

  3. 3.

    This analytic choice does not bias the “year” variable in anyway. In fact, it facilitates a more substantive interpretation of the effect of year. By recoding year to 0–4.4, a unit increase in year can be interpreted as a 10-year or decade change in the odds of being happy.

  4. 4.

    I refer to political economy to highlight the intersection of economics (markets) and politics (the state) and the degree to which individuals are embedded in societies, markets and the state.

  5. 5.

    In the few cases where results differ, I discuss these differences in my descriptions of Tables 4 and 5 where race-gender group-specific predicted probabilities are presented across the upper (“very happy”) to lower (“not too happy”) bounds of happiness.

  6. 6.

    To adjust for noise, these temporal patterns are presented with a race-gender specific (best fit) trend lines from 1972 to 2016.

  7. 7.

    Based on the analysis alternating the race/gender referent, it was determined that the “main effect” variable for Black Women in Model 1 (representing average differences across the span of the survey for Black women) and Model 2 (representing Black female–White male happiness differentials in 1972) was significantly different from the main effect for White women and the omitted category (White men), but not Black men.

  8. 8.

    Supplementary analysis (not shown in Table 4) demonstrates that White male–female gap in happiness across the lower and upper bounds of happiness were statistically indistinguishable in the 2000s. The pattern in the 2010’s represents a complete reversal of White male progress in the prior decade.

  9. 9.

    To ensure substantive and reliable conclusions could be drawn regarding changes in predicted probabilities across income, the top category was set to 50% of median household income to accommodate variation in income distributions across race and gender. Although about 29% of White women and 36% of White men resided in households with incomes in excess of $80,000 during the 2010s, 11% of Black Women and about 19% of Black men earned incomes in this range.

  10. 10.

    Among unemployed Black men the distribution of the happiness outcome during the post-recession years was as followed: Not Too Happy (n = 22); Pretty Happy (n = 28); Very Happy (n = 5). Among Black men who were employed Full-Time, the distribution of happiness was as followed: Not Too Happy (n = 41); Pretty Happy (n = 153); Very Happy (n = 83).

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Acknowledgements

Research reported in this publication was supported by the National Center of Minority Health and Health Disparities (NCMHD) of the National Institutes of Health (NIH) under award #R36MD004957. The author would also like to acknowledge the helpful comments from the editor, reviewers and colleagues.

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Correspondence to Jason L. Cummings.

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The original version of this article was revised. Table 1 was published incorrectly. The correct Table 1 is updated in the article.

Appendix

Appendix

See Table 6.

Table 6 Predicted probabilities for general happiness, post great recession (2010–2016) with adjusted estimates (subjective SES)

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Cummings, J.L. Assessing U.S. Racial and Gender Differences in Happiness, 1972–2016: An Intersectional Approach. J Happiness Stud 21, 709–732 (2020). https://doi.org/10.1007/s10902-019-00103-z

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Keywords

  • Happiness
  • Subjective well-being
  • Intersectionality
  • Race
  • Gender
  • SES
  • Financial satisfaction
  • Great recession
  • Unemployment