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Economic Freedom and Life Satisfaction: Mediation by Income per Capita and Generalized Trust

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Abstract

Several researches have shown that economic freedom is positively related to life satisfaction. Only a few studies, however, have examined which aspects of economic freedom (small government size, quality of the legal system, sound money, trade openness or no regulation) drive this relationship. Furthermore, most studies construe the influence of economic freedom as additional to the influence of income per capita on life satisfaction. No research has studied the potential mediating role of income per capita or other mediators in the relationship between economic freedom and life satisfaction. In order to fill these gaps, this paper aims (1) to investigate which aspects of economic freedom are most related to life satisfaction, and (2) to test whether these relationships are mediated by income and trust. Based on a sample of 120 countries, we find that life satisfaction is positively related to the quality of the legal system and negatively related to small government size. Income per capita mediates the positive influence of the quality of the legal system on life satisfaction. Trust is found to mediate the positive influence of the quality of legal system and the negative influence of small government size on life satisfaction, but the significance of these indirect effects depends on the type of economic freedom indicators used. We find no significant direct effects from the economic freedom indicators on life satisfaction.

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Notes

  1. Source: http://www.freetheworld.com.

  2. Also unemployment is found to be related to economic freedom (Feldmann 2006, 2009).

  3. Furthermore, Ovaska and Takashima (2006) find that economic growth positively affects life satisfaction. In contrast, Deaton (2008) finds that economic growth enters happiness equations with a negative sign. Other studies have found no significant relationship between economic growth and life satisfaction, once corrected for income per capita.

  4. Blanchflower and Oswald (2011) find, however, that (for Americans) education only affects life satisfaction when there is no control for the level of income. The effect disappears when income is added. Also Helliwell (2003) finds that the well-being effects of education flow primarily through their effects on higher incomes, trust and health and not through a direct impact on life satisfaction.

  5. Ott (2010) finds that the quality of governance (which is related to the second aspect of economic freedom) is more important in poor countries than in rich countries.

  6. In contrast, Bjørnskov et al. (2010) find that economic institutions (which include legal quality and honest and efficient government) affect life satisfaction in both poor and rich countries, whereas political institutions only affect life satisfaction in rich countries.

  7. Besides these control variables, literature shows that life satisfaction is also influenced by several other variables. However, in order to increase the sample size and degrees of freedom, we limited the number of explanatory variables and used a specification that is quite parsimonious. As Gropper et al. (2011) argue, most of the potential control variables (for example, inflation, unemployment, life expectancy, age structure, skill level, political freedom and other indicators) are highly correlated with GDP per capita or economic freedom indicators. Thus, GDP per capita and economic freedom indicators are likely to capture most of the variation associated with any omitted variable. We checked this by performing regression analyses including other control variables (life expectancy, share of aged people, female participation rate, income inequality as measured by the Gini index, education, unemployment and political freedom), but the results did not change our main findings and conclusions. The results are available with the authors on request.

  8. Another reason why the relationship between income and well-being is stronger for the aggregate well-being of countries than for individual well-being within countries is that, besides individual income, societal goods are important for individual well-being. This is empirically confirmed by Diener et al. (2010) who found a strong association between well-being and national income, even when individual income was included in the equation.

  9. One can question whether the meaning of life satisfaction varies in different cultures. Helliwell et al. (2008) find, however, that, despite cultural differences, people value the same (relatively small) set of variables in comparable ways across the globe. Also Veenhoven (2000) and Diener and Suh (2002) argue that aggregate SWB scores can be meaningfully compared across cultures.

  10. See http://www.fraserinstitute.org/uploadedFiles/fraser-ca/Content/research-news/research/publications/economic-freedom-of-the-world-2012-appendix.pdf.

  11. When we add trust as explanatory variable in the equation for income per capita (Eq. 2) or income as explanatory variable in the trust equation (Eq. 3), we find that these cross effects between income per capita and trust are both insignificant. Therefore, we abstract from the cross relations between income per capita and trust.

  12. If we use the governance indices that Helliwell and Huang (2008) use in their analysis (governance quality delivery and governance quality democratic) instead of the five economic freedom indicators, we still find highly significantly positive coefficients of income per capita and trust, whereas the institutional variables are insignificant in the life satisfaction equation. Furthermore, governance quality delivery appears to be highly significantly positive in the equations for income per capita and trust. This again confirms mediation by income per capita and trust. The results are available with the authors.

  13. We tested whether these differences can be explained by the fact that EF3f and EF5h partly overlap, since both include inflation. But if we test separately for monetary freedom (the index in EF5h that includes inflation), we find (insignificant) negative rather than positive coefficients in the life satisfaction and GDP per capita regressions.

  14. For the technical details, see Preacher et al. (2007) and Preacher and Hayes (2008). For a macro that allows an easy application of bootstrap technique proposed by Preacher and Hayes (2008) in SPSS, see http://www.afhayes.com/spss-sas-and-mplus-macros-and-code.html.

  15. The simultaneity problem arises if some of the regressors are endogenous and are therefore likely to be correlated with the disturbance, or error, term. Therefore, a test of simultaneity is essentially a test of whether a regressor is correlated with the error term. If it is, OLS produces biased estimates. If it is not, we can use OLS. The Hausman endogeneity test that we employ tests just this and is recommended by Maddala (1991) and Gujarati and Porter (2009) and also applied in other studies to test for endogeneity (de Haan and Sturm 2000).

  16. The F test is calculated as {(R 2new  − R 2old )/number of restrictions in old model}/{(1 − R 2new )/(n-number of parameters in new model} (Gujarati and Porter 2009: 245).

  17. See: http://data.worldbank.org/about/country-classifications/country-and-lending-groups#High_income).

  18. It should be noted that the sample for poor countries is relatively small which reduces the reliability of our findings.

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Authors and Affiliations

  1. CentER, Tilburg Sustainability Center, European Banking Center, Departments of Economics and Philosophy, Tilburg University, P.O. Box 90153, 5000 LE, Tilburg, The Netherlands

    Johan Graafland

  2. Mn Services, P.O. Box 30025, 2500 GA, The Hague, The Netherlands

    Bart Compen

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Correspondence to Johan Graafland.

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Table 7 List of countries included in the study
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Graafland, J., Compen, B. Economic Freedom and Life Satisfaction: Mediation by Income per Capita and Generalized Trust. J Happiness Stud 16, 789–810 (2015). https://doi.org/10.1007/s10902-014-9534-3

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