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The Impact of Exposure to Other Countries on Life Satisfaction: An International Application of the Relative Income Hypothesis

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Abstract

The cause of international differences in life satisfaction is usually ascribed to differences in living standards. Yet, despite improving living standards in a lot of middle-income countries, significant differences in life satisfaction between middle- and high-income countries remain. This paper examines if there is an international comparison effect and assesses to what extent the relative income hypothesis can be applied to explain international differences in life satisfaction. We test this by analyzing how exposure to other countries impacts life satisfaction. It is hypothesized that higher exposure to other countries in low- and middle-income countries has a negative effect due to increased aspirations and relative deprivation, while the opposite holds true for rich countries. We draw on data from the World Value Survey, the World Bank and the KOF Globalization index to perform a multilevel analysis. The results suggest that an international comparison effect indeed exists and is capable of partially explaining international differences in life satisfaction. Additional analyses reveal that people in lower income classes, in all countries, are affected more by exposure to other countries, indicating that individual characteristics are important when assessing the impact of exposure on life satisfaction. We demonstrate the robustness of these findings by showing that both sub-indicators of exposure, informational flow and international contact, have an impact on life satisfaction that is similar to that of our overall exposure-index.

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Notes

  1. KOF is a Swiss Economic Institute staffed mainly by academics. KOF is an acronym for the German word "Konjunkturforschungsstelle" (business cycle research institute). The index is described in the Sect. 3.

  2. Well-being research in general has been subject to several criticisms. We do not address these issues in detail here, but refer to the Stiglitz Report (Stiglitz et al. 2010) for a discussion on these matters.

  3. The other cited articles would be subject to similar remarks.

  4. Research has shown that it is easier to explain variance at country level than at individual level. Compare for instance Engelbrecht (2009) who looks at country level determinants and Knight et al. (2009) who test the strength of individual level predictors. Engelbrecht finds a higher R2 and is thus more capable of explaining differences between countries than Knight et al. (2009) are in explaining differences between individuals.

  5. Calculated by dividing the country level variance by the total variance i.e. 0.830/(0.830 + 4.225) = 0.164.

  6. Trinidad and Tobago have an average life expectancy of only 69 years, while the rest of the sample has an average around 80. Additionally, Trinidad and Tobago have a relatively high average life satisfaction. This causes the model to predict a negative effect of life expectancy. Omitting this country from our model leads to the same conclusions as before, except that life expectancy no longer has a significant impact.

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Acknowledgments

The author would like to thank Elsy Verhofstadt, Luc Van Ootegem, Brent Bleys, Walter van Trier and two anonymous referees for their helpful comments and valuable suggestions on earlier drafts.

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  1. Department of Social Economics, Faculty of Economics and Business Administration, Ghent University, Sint-Pietersplein 6, 9000, Ghent, Belgium

    Benjamin Schalembier

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Appendix

Appendix

See Table 6.

Table 6 Country-specific values on all constructed country level characteristics
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Schalembier, B. The Impact of Exposure to Other Countries on Life Satisfaction: An International Application of the Relative Income Hypothesis. Soc Indic Res 128, 221–239 (2016). https://doi.org/10.1007/s11205-015-1027-1

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