Skip to main content

Exploring the Myth of Unhappiness in Former Communist Countries: The Roles of the Sex Gap in Life Expectancy and the Marital Status Composition

Abstract

National average happiness and the difference in happiness between women and men are positively correlated in European countries. This study focuses on this cross-country relationship and tests (1) whether, after controlling for socio-economic factors, the correlation is attributed to their direct relationship, or, alternatively, explained by the sex difference in life expectancy, and (2) whether the correlation is not only exogenously explained but also endogenously generated by the sex difference in life expectancy. Performing regression analyses, this study shows that the correlation between happiness and its sex difference is spurious, and that the sex difference in life expectancy generates this correlation and accounts for about one-third of the correlation. A decline in happiness influences men’s mortality more than women’s, and widens the life expectancy gap between women and men. This in turn raises the widowhood ratio among women, lowers women’s average happiness, and reduces the happiness gap between women and men. The results obtained in this study points to the importance of controlling for the demographic composition of the population when we use aggregate happiness measures as national happiness indicators.

This is a preview of subscription content, access via your institution.

Fig. 1

Notes

  1. This, however, does not necessarily mean that the level of psychological stress is higher for men. As found in Mirowsky and Ross (1995), women are generally at a higher risk of depression. The ways that women and men react to psychological stress are simply different. As described in Nathanson (1977), “women get sick and men die”.

  2. This result also casts a doubt on the general idea that women are less happy than men in European countries.

  3. As the data set is heavily unbalanced and eight countries have only one observation, we treat it as pooled data set. Thus, the present analysis intends to test the cross-sectional correlation.

  4. Since the outcome that the coefficient of FCD is significantly positive could potentially be caused by the non-linear relationship between HPGAP and HPN, we also test if adding the square of HPN in equations (1-1) and (1-6) changes the regression results. However, the results do not change in any meaningful way. Both HPN and HPN squared are insignificant in both equations.

  5. WLR and FCD compete for explanatory power. If WLR is included instead of FCD in equation (1-6), the coefficient of WLR becomes significantly positive at the 5% level while other results remain the same. Assuming that a higher WLR indicates greater autonomy in women and more gender equality, this result suggests that women’s autonomy and gender equality contribute to women’s happiness.

  6. We use PL because it is most significant in explaining HPN in the previous regression model.

  7. The coefficients of LEGAP on HPGAP and HPN are respectively −0.011 and −0.041, both at the 1% level of significant. These results are virtually equivalent to the results of the previous sample.

References

  • Glei, D. A., & Horiuchi, S. (2007). The narrowing sex differential in life expectancy in high-income populations: Effects of differences in the age pattern of mortality. Population Studies, 61, 141–159.

    Article  Google Scholar 

  • Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50, 1029–1054.

    Article  Google Scholar 

  • Helliwell, J. F. (2007). Well-being and social capital: Does suicide pose a puzzle? Social Indicators Research, 81, 455–496.

    Article  Google Scholar 

  • Kageyama, J. (2011). Happiness and sex difference in life expectancy. Journal of Happiness Studies. doi:10.1007/s10902-011-9301-7.

    Google Scholar 

  • Kleibergen, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of Econometrics, 127, 97–126.

    Article  Google Scholar 

  • Mirowsky, J., & Ross, C. E. (1995). Sex differences in distress: Real or artifact? American Sociological Review, 60, 449–468.

    Article  Google Scholar 

  • Möller-Leimkühler, A. M. (2003). The gender gap in suicide and premature death or: Why are men so vulnerable? European Archives of Psychiatry and Clinical Neuroscience, 253, 1–8.

    Article  Google Scholar 

  • Nathanson, C. A. (1977). Sex, illness, and medical care: A review of data, theory, and method. Social Science and Medicine, 11, 13–25.

    Article  Google Scholar 

  • Pampel, F. C., & Zimmer, C. (1989). Female labour force activity and the sex differential in mortality: Comparisons across developed nations, 1950–1980. European Journal of Population, 5, 281–304.

    Article  Google Scholar 

  • Pressman, S. D., & Cohen, S. (2005). Does positive affect influence health? Psychological Bulletin, 131, 925–971.

    Article  Google Scholar 

  • Ram, B. (1993). Sex differences in mortality as a social indicator. Social Indicators Research, 29, 83–108.

    Article  Google Scholar 

  • Stock, J. H., & Yogo, M. (2005). Testing for weak instruments in linear iv regression. In D. W. K. Andrews & J. H. Stock (Eds.), Identification and inference for econometric models: Essays in honor of Thomas Rothenberg (pp. 80–108). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Tesch-Römer, C., Motel-Klingebiel, A., & Tomasik, M. J. (2008). Gender differences in subjective well-being: Comparing societies with respect to gender equality. Social Indicators Research, 85, 329–349.

    Article  Google Scholar 

  • Veenhoven, R. (2008). Healthy happiness: Effects of happiness on physical health and the consequences for preventive health care. Journal of Happiness Studies, 9, 449–469.

    Article  Google Scholar 

  • Weidner, G., & Cain, V. S. (2003). The gender gap in heart disease: Lessons from eastern Europe. American Journal of Public Health, 93, 768–770.

    Article  Google Scholar 

Download references

Acknowledgments

I wish to thank the anonymous referees for helpful comments, the Max Planck Institute for Demographic Research for providing research facilities, and the Miyata Research Fund of Meikai University for financial support. Part of this research was conducted while I was a visiting researcher at the MPIDR. Any remaining errors are my own.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junji Kageyama.

Appendix

Appendix

Data sources

HPN, HPGAP, AGE, and other happiness-related variables: European and World Values Surveys (2006). European and World Values Surveys four-wave integrated data file, 1981−2004, v.20060423. Surveys designed and executed by the European Values Study Group and World Values Survey Association. File Producers: ASEP/JDS, Madrid, Spain and Tilburg University, Tilburg, the Netherlands. File Distributors: ASEP/JDS and GESIS, Cologne, Germany.

YPC, LYPC, PL, OPEN, GS and GYPC: Heston, A., Summers, R., & Aten, B. (2006). Penn World Table Version 6.2. Center for International Comparisons of Production, Income and Prices, University of Pennsylvania.

SMGAP: WHO Regional Office for Europe (2007). Health for All database. (http://www.euro.who.int/hfadb).

WLR and FTR: World Bank (2008). World development indicators 2008. Washington, DC.

LEGAP and LE: United Nations Population Division (2007). World population prospects: The 2006 revision. (http://data.un.org/).

Sample Periods

The sample periods consist of four periods: 1980–1984 (1), 1990–1994 (2), 1995–1999 (3), and 2000–2004 (4), following the data in UN. Happiness data are attached to these periods according to wave number. For the variables taken from PWT, WHO Europe, and the World Bank, the averages are calculated within each period.

Sample Countries and Sample Periods

Albania (4), Austria (2), Belgium (1, 2, 4), Bosnia and Herzegovina (4), Belarus (3, 4), Croatia (3, 4), Czech Republic (2, 3, 4), Denmark (2, 4), Estonia (2, 3, 4), Finland (2, 3, 4), France (1, 2, 4), Germany (3, 4), Greece (4), Hungary (2, 3, 4), Iceland (2, 4), Ireland (1, 2, 4), Italy (2, 4), Latvia (2, 3, 4), Lithuania (2, 3, 4), Luxembourg (4), Malta (2, 4), Republic of Moldova (4), Netherlands (1, 2, 4), Norway (1, 2, 3), Poland (2, 3, 4), Portugal (2), Romania (2, 4), Russia (2, 3, 4), Slovakia (2, 3), Slovenia (2, 3, 4), Spain (2, 3, 4), Sweden (1, 2, 3, 4), Switzerland (2, 3), Ukraine (3, 4), Macedonia (3), UK (1, 2, 3). Note that, for regressing LEGAP, Iceland (2), Latvia (2), Malta (2), and Netherlands (1) are excluded.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Kageyama, J. Exploring the Myth of Unhappiness in Former Communist Countries: The Roles of the Sex Gap in Life Expectancy and the Marital Status Composition. Soc Indic Res 111, 327–339 (2013). https://doi.org/10.1007/s11205-012-0008-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11205-012-0008-x

Keywords

  • Subjective well-being
  • Happiness
  • Life expectancy
  • Sex difference
  • East–West divide