Skip to main content

What Makes People Happy? Evidence from International Data

Abstract

Individuals’ life satisfaction varies widely across countries. Differences in income explain a large part of this variation, but not all. The purpose of this study is to identify the country-level determinants, in addition to income, that best explain life satisfaction, with the objective of understanding how a country’s policies and developmental strategies may affect the well-being of its residents. To do so, we pool life satisfaction data and key economic, political, social, and environmental variables (including GDP per capita, unemployment rate, level of corruption, social capital, CO2 emissions and particulate matter (PM) concentrations) for a cross-section of countries to calculate the relative contribution of political, social, and environmental variables vis-à-vis economic factors to explain life satisfaction. Regression models indicate that religiosity, social capital, and pollution are among the strongest determinants of differences in life satisfaction. Employing a relative contribution analysis, we find that after individual characteristics, GDP is the most important predictor of life satisfaction, but that country fixed effects remain stubbornly important.

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

Fig. 1
Fig. 2
Fig. 3

Notes

  1. The group has highlighted the importance of mental health integration for “whole-person care,” supported a minimum wage increase to reduce the negative effect of income disparities on happiness, and promoted the prioritization of economic stability over economic growth to improve well-being.

  2. Jorm and Ryan (2014) review the literature and identify national income, inequality, social welfare, individualism, political stability, democracy, and life expectancy as important predictors of national SWB.

  3. In some specifications, where we include smaller sets of explanatory variables, we observe 96 countries (listed in "Appendix" Table 6).

  4. GDP per capita is included in log form to allow for nonlinear effects of GDP consistent with a diminishing marginal utility of income.

  5. We use the WVS sampling weights to ensure that the samples are representative of each country.

  6. Technically, DA is defined as the squared semi-partial correlation. The level of analysis is defined for all 2(p−2) subset models for which the comparison of each pair of predictors is relevant.

  7. Graham and Nikolova (2015) use the decomposition of explained variance proposed by Field (2003), and Lamu and Olsen (2016) apply a Shapely value decomposition method.

  8. This result may be driven by the education question in the WVS, which asks the age at which individuals finish their full-time education and does not reflect the exact level of education obtained; or as Helliwell (2003) argues using the same dataset, the insignificant association of education might have already be taken into account due to inclusion of income, health and trust.

  9. In a robustness analysis, we investigate impact of income inequality, measured by Gini coefficient, on LS. However due to large number of missing values (more than 50% of the sample), we exclude this variable from our main regressions results. The regression result of the model with a Gini variable showed that the Gini coefficient did not have a statistically significant effect on LS.

  10. The general DS is performed with Stata syntax “Domin.”.

  11. While Sd. DS and DS both convey the same information, excluding the unexplained variation in Sd. DS better reflects the relative importance of the variables in our analysis.

  12. Achieving complete dominance implies that conditional and general dominance, which are weaker criteria of dominance analysis are also obtained (Azen and Budescu, 2003).

References

  • Ahmadiani, M., Brereton, F., Ferreira, S., & Moro, M. (2020). Spatial variation in life satisfaction: A happiness puzzle. In D. Maddison, K. Rehdanz, & H. Welsch (Eds.), Handbook on Wellbeing Happiness and the Environment. UK: Edward Elgar Publishing Cheltenham.

    Google Scholar 

  • Ahmadiani, M., & Ferreira, S. (2019). Environmental amenities and quality of life across the United States. Ecological Economics, 164, 106341.

    Article  Google Scholar 

  • Akay, A., Constant, A., & Giulietti, C. (2014). The impact of immigration on the well-being of natives. Journal of Economic Behavior & Organization, 103, 72–92.

  • Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological Methods, 8, 129–148.

    Article  Google Scholar 

  • Barrington-Leigh, C., & Behzadnejad, F. (2017). Evaluating the short-term cost of low-level local air pollution: A life satisfaction approach. Environmental Economics and Policy Studies, 19(2), 269–298.

    Article  Google Scholar 

  • Bartolini, S., & Bilancini, E. (2010). If not only GDP, what else? Using relational goods to predict the trends of subjective well-being. International Review of Economics, 57(2), 199–213.

    Article  Google Scholar 

  • Berg, M. C., & Veenhoven, R. (2010). Income inequality and happiness in 119 nations. In B. Greve (Ed.), Happiness and social policy in Europe (pp. 174–194). Edward Elgar: Cheltenham / Aldershot, UK/ Northampton, MA, USA. https://doi.org/10.4337/9781781000731.00017.

  • Binder, M., & Blankenberg, A. K. (2017). Green lifestyles and subjective well-being: More about self-image than actual behavior? Journal of Economic Behavior and Organization, 137, 304–323.

    Article  Google Scholar 

  • Bonini, A. N. (2008). Cross-national variation in individual life satisfaction: Effects of national wealth, human development, and environmental conditions. Social Indicators Research, 87(2), 223–236.

    Article  Google Scholar 

  • Budescu, D. V. (1993). Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychological Bulletin, 114, 542–551.

    Article  Google Scholar 

  • Cimedregzen, S. (2020). Air pollution and happiness: Evidence from the coldest capital in the world. University of Georgia, ProQuest Dissertations Publishing, 27830073.

  • Chophel, S. (2012). Culture, public policy & happiness. Journal of Bhutanese Studies, 26, 82–99.

    Google Scholar 

  • Clark, A. E., Frijters, P., & Shields, M. A. (2008). Relative income, happiness, and utility: An explanation for the Easterlin Paradox and other puzzles. Journal of Economic Literature, 46(1), 95–144.

    Article  Google Scholar 

  • Clark, A. E., & Senik, C. (2010). Who compares to whom? The anatomy of income comparisons in Europe. The Economic Journal, 120(544), 573–594.

    Article  Google Scholar 

  • Corruption Perceptions Index. (2018). Retrieved from http://www.transparency.org/cpi

  • Deaton, A., & Stone, A. A. (2013). Two happiness puzzles. American Economic Review, 103(3), 591–597.

    Article  Google Scholar 

  • Di Tella, R., MacCulloch, R. J., & Oswald, A. J. (2001). Preferences over inflation and unemployment: Evidence from surveys of happiness. American Economic Review, 91(1), 335–341.

    Article  Google Scholar 

  • Dominko, M., & Verbič, M. (2021). The effect of income and wealth on subjective well-being in the context of different welfare state regimes. Journal of Happiness Studies, 22(1), 181–206.

    Article  Google Scholar 

  • Easterlin, R. A., & Angelescu, L. (2009). Happiness and growth the world over: Time series evidence on the happiness-income paradox. IZA Discussion Paper No. 4060.

  • Easterlin, R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. In P. A. David & M. W. Reder (Eds.), Nations and Households in Economic Growth: Essays in Honor of Moses Abramovitz. New York: Academic Press Inc.

    Google Scholar 

  • Evans, M. F., & Smith, V. K. (2005). Do new health conditions support mortality-air pollution effects? Journal of Environmental Economics and Management, 50, 496–518.

    Article  Google Scholar 

  • Exton, C., Smith, C., & Vandendriessche, D. (2015). Comparing happiness across the world: Does culture matter?. OECD Statistics Working Papers, 2015(4).

  • University of Groningen and University of California, Davis, Average Annual Hours Worked by Persons Engaged for United States, retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/AVHWPEUSA065NRUG, March 28, 2018.

  • Ferreira, S., Akay, A., Brereton, F., Cuñado, J., Martinsson, P., Moro, M., & Ningal, T. F. (2013). Life satisfaction and air quality in Europe. Ecological Economics, 88, 1–10.

    Article  Google Scholar 

  • Frey, B. S., & Stutzer, A. (2002). What can economists learn from happiness research? Journal of Economic Literature, 40(2), 402–435.

    Article  Google Scholar 

  • Frijters, P., Haisken-DeNew, J. P., & Shields, M. A. (2004). Money does matter! Evidence from increasing real income and life satisfaction in East Germany following reunification. American Economic Review, 94(3), 730–740.

    Article  Google Scholar 

  • Graham, C., & Nikolova, M. (2015). Bentham or Aristotle in the development process? An empirical investigation of capabilities and subjective well-being. World Development, 68, 163–179.

    Article  Google Scholar 

  • Helliwell JF, Barrington-Leigh C, Harris A, Huang H (2010) International evidence on the social context of well-Being. In Diener E, Helliwell JF, Kahneman D (2010) International Differences in Well-Being. Oxford University Press.

  • Helliwell, J. F., Huang, H., & Wang, S. (2017). The social foundations of world happiness. In J. Helliwell, R. Layard, J. Sachs, J. E. De Neve, H. Huang, & S. Wang (Eds.), World Happiness Report 2017. New York: Sustainable Development Solutions Network.

  • Helliwell, J. F. (2003). How’s life? Combining individual and national variables to explain subjective well-being. Economic Modelling, 20(2), 331–360.

    Article  Google Scholar 

  • Helliwell, J. F. (2006). Well-being, social capital and public policy: What’s new? The Economic Journal, 116(510), C34–C45.

    Article  Google Scholar 

  • Helliwell, J. F., & Huang, H. (2008). How’s your government? International evidence linking good government and well-being. British Journal of Political Science, 38(4), 595–619.

    Article  Google Scholar 

  • Inglehart, R., C. Haerpfer, A. Moreno, C. Welzel, K. Kizilova, J. Diez-Medrano, M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2014. World Values Survey: Round Five -Country-Pooled Datafile Version: www.worldvaluessurvey.org/WVSDocumentationWV5.jsp.Madrid: JD Systems Institute.

  • Inglehart, R. (2002). Gender, aging, and subjective well-being. International Journal of Comparative Sociology, 43(3–5), 391–408.

    Article  Google Scholar 

  • Inglehart, R., Foa, R., Peterson, C., & Welzel, C. (2008). Development, freedom, and rising happiness: A global perspective (1981–2007). Perspectives on Psychological Science, 3(4), 264–285.

    Article  Google Scholar 

  • INSCR Data Page. (2017). Retrieved from http://www.systemicpeace.org/inscrdata.html.

  • Jorm, A. F., & Ryan, S. M. (2014). Cross-national and historical differences in subjective well-being. International Journal of Epidemiology, 43, 330–340.

    Article  Google Scholar 

  • Kaida, N., & Kaida, K. (2016). Pro-environmental behavior correlates with present and future subjective well-being. Environment, Development and Sustainability, 18(1), 111–127.

    Article  Google Scholar 

  • Lamu, A. N., & Olsen, J. A. (2016). The relative importance of health, income and social relations for subjective well-being: An integrative analysis. Social Science & Medicine, 152, 176–185.

    Article  Google Scholar 

  • Levinson, A. (2012). Valuing public goods using happiness data: The case of air quality. Journal of Public Economics, 96(9–10), 869–880.

    Article  Google Scholar 

  • Li, Q., & An, L. (2020). Corruption takes away happiness: Evidence from a cross-national study. Journal of Happiness Studies, 21(2), 485–504.

    Article  Google Scholar 

  • Lo, A., Chernoff, H., Zheng, T., & Lo, S. H. (2015). Why significant variables aren’t automatically good predictors. Proceedings of the National Academy of Sciences of the United States of America, 112(45), 13892–13897.

    Article  Google Scholar 

  • O’Connor, K. J. (2020). Life satisfaction and noncognitive skills: Effects on the likelihood of unemployment. Kyklos, 73(4), 568–604.

    Article  Google Scholar 

  • Organization for Economic Co-operation and Development (OECD). (2013). OECD guidelines on measuring subjective well-being.

  • Pope, C. A., III., Burnett, R. T., Thurston, G. D., Thun, M. J., Calle, E. E., Krewski, D., & Godleski, J. J. (2004). Cardiovascular mortality and long-term exposure to particulate air pollution: Epidemiological evidence of general pathophysiological pathways of disease. Circulation, 109(1), 71–77.

    Article  Google Scholar 

  • Post, S. G. (2005). Altruism, happiness, and health: It’s good to be good. International Journal of Behavioral Medicine, 12(2), 66–77.

    Article  Google Scholar 

  • Powdthavee, N. (2010). How much does money really matter? Estimating the causal effects of income on happiness. Empirical Economics, 39(1), 77–92.

    Article  Google Scholar 

  • Putnam, R. D. (2007). E Pluribus Unum: Diversity and community in the twenty-first century the 2006 Johan Skytte Prize Lecture. Scandinavian Political Studies, 30(2), 137–174.

    Article  Google Scholar 

  • Reardon, L. H., & Bache, I. (2015). The Wellbeing Agenda: Implications for Policy. East-West Institute for Advanced Studies (EWIAS) Viewpoints Journal, 2.

  • Rojas, M. (2018). Happiness in Latin America has social foundations. World happiness report, 115–145.

  • Sachs, J. D., Layard, R., & Helliwell, J. F. (2018). World Happiness Report 2018 (No. id: 12761).

  • Senik, C. (2014). The French unhappiness puzzle: The cultural dimension of happiness. Journal of Economic Behavior & Organization, 106, 379–401.

    Article  Google Scholar 

  • Stavrova, O., Fetchenhauer, D., & Schlösser, T. (2013). Why are religious people happy? The effect of the social norm of religiosity across countries. Social Science Research, 42(1), 90–105.

    Article  Google Scholar 

  • Stevenson, B., & Wolfers, J. (2008). Economic growth and subjective well-being: Reassessing the Easterlin paradox (No. w14282). National Bureau of Economic Research.

  • Stevenson, B., & Wolfers, J. (2013). Subjective well-being and income: Is there any evidence of satiation? American Economic Review, 103(3), 598–604.

    Article  Google Scholar 

  • Stiglitz, J., Sen, A., & Fitoussi, J. P. (2009). Report by the commission on the measurement of economic performance and social progress. The Commission on the Measurement of Economic Performance and Social Progress.

  • Streimikiene, D. (2015). Environmental indicators for the assessment of quality of life. Intellectual Economics, 9(1), 67–79.

    Article  Google Scholar 

  • Tay, L., Herian, M. N., & Diener, E. (2014). Detrimental effects of corruption and subjective well-being: Whether, how, and when. Social Psychological and Personality Science, 5(7), 751–759.

    Article  Google Scholar 

  • The World Values Survey. (2013) Retrieved from http://www.worldvaluessurvey.org/WVSContents.jsp

  • Welsch, H. (2006). Environment and happiness: Valuation of air pollution using life satisfaction data. Ecological Economics, 58(4), 801–813.

    Article  Google Scholar 

  • Welsch, H. (2008). The welfare costs of corruption. Applied Economics, 40(14), 1839–1849.

    Article  Google Scholar 

  • World Development Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/world-development-indicators)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mona Ahmadiani.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

The first five columns of Table 6 below show the unconditional country averages of self-reported LS data from the WVS. That is the national average of LS (before controlling for individual characteristics) for each wave as well as the average of the four waves. Data is ordered from highest to lowest LS, based on the average across the four waves. The last column shows the conditional country average LS from multi-level regression for years 1995 to 2014.

See Tables 6,

Table 6 Self-reported life satisfaction from the World Values Survey
Table 7 Multilevel regression results

7,

Table 8 Relative importance (Complete Dominance Test)

8.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ahmadiani, M., Ferreira, S. & Kessler, J. What Makes People Happy? Evidence from International Data. J Happiness Stud 23, 2083–2111 (2022). https://doi.org/10.1007/s10902-021-00478-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10902-021-00478-y

Keywords

  • Life satisfaction
  • Subjective well-being
  • International comparisons
  • World Values Survey

JEL Classification

  • I31
  • C31
  • D63