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Corruption Takes Away Happiness: Evidence from a Cross-National Study

Abstract

Both corruption and subjective well-being are of concern to academics, governments, and policy makers. This paper studies the impact of corruption on subjective well-being, using cross-national data for 126 countries. By employing preindustrial local traditional democracy level as a novel instrument variable for current corruption, the paper addresses the endogeneity issue. We find the national average of subjective well-being would decrease by 0.23 points if a government became more corrupt by 10 points, and unemployment rate had to decrease equivalently by 9.2% to keep the national average subjective well-being unchanged. Further investigation shows that corruption had a significant effect in democratic or high-income countries only. The results are robust to alternative measures of corruption and happiness, estimation strategies, and excluding outliers.

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Notes

  1. In following Ott (2010a), life satisfaction, happiness, subjective well-being, and quality of life are used interchangeably in this paper. The dominant view is that both subjective well-being and happiness are umbrella terms (e.g., Diener 2006; The World Health Organization Quality of Life Group 1995). Happiness is normally defined as a positive affect but can also be thought of as a universal evaluation of a person’s life satisfaction (Camfield and Skevington 2008). Life satisfaction is thus a subordinate term to the general concept of happiness. However, it should be noted that Ott (2011) provided discussions on differences between happiness and subjective well-being.

  2. In addition, a growing body of literature focuses on the effect of the general quality of government on happiness. For example, Bjørnskov, Dreher, and Fischer (2010), Samanni and Holmberg (2010), Teorell (2009), and Kim and Kim (2012) provided comprehensive literature reviews.

  3. Specifically, Arvin and Lew (2014) used a 10-year lag of freedom, house and population growth, share of exports made up of resource products, great circle distance from a country’s principal city to the equator, and the legal origin of a country’s judicial system (British, French, or socialist) as IVs for corruption. Apparently, some of its IVs, such as share of exports, have a direct effect on happiness, which violates the exclusion criteria for a valid IV. Sulemana (2015) used democracy as an IV for corruption, which also violates the exclusion criteria because democracy has been shown to have a direct impact on happiness (Inglehart 1999).

  4. PM2.5 is fine particulate matter in micrograms per cubic meter that is 2.5 microns and smaller, ug/m3, which can lodge deep in lung and blood tissue and is injurious to health.

  5. Religious fractionalization reflects the probability that two randomly selected people from a given country will not belong to the same religious group. The higher the number, the more fractionalized the society.

  6. Ethnic fractionalization reflects the probability that two randomly selected people from a given country will belong to different ethnic groups. The variable thus ranges from 0 (perfectly homogeneous) to 1 (highly fragmented).

  7. Language fractionalization reflects the probability that two randomly selected people from a given country will not belong to the same linguistic group. The higher the number, the more fractionalized the society.

  8. We would see that the difference between 2SLS and OLS estimators is significant when using the BCI as a robustness check for measurement of corruption.

  9. TI adopted a scale of 0–10 before 2013 for its CPI and then switched to a scale of 0–100 in 2014.

  10. Standard deviation is the most commonly used set of statistics for measuring inequality of happiness within a nation (Kalmijn and Veenhoven 2005). Other measures include absolute difference, the mean pair distance, the interquartile range, and inequality-adjusted happiness (Kalmijn and Veenhoven). For simplicity, this paper only reports results using standard deviation as a measure of inequality of happiness.

  11. Happy life expectancy = life expectancy at birth times happiness (0–1 point scale).

  12. We owe this observation to an anonymous referee.

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Acknowledgements

This research was supported by National Social Science Foundation (15AZD079) and Humanities and Social Sciences Project from the Ministry of Education of China (15XJC790012). We would like to thank Gordon Liu, and Qinying He for helpful comments.

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Appendix

Appendix

See Table 9.

Table 9 First stage correlations between preindustrial democracy and current corruption

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Li, Q., An, L. Corruption Takes Away Happiness: Evidence from a Cross-National Study. J Happiness Stud 21, 485–504 (2020). https://doi.org/10.1007/s10902-019-00092-z

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