Happiness over the financial crisis

ABSTRACT

This paper adds to the literature on the macroeconomic driving forces of happiness. Using data for 106 countries over the financial crisis (2006–2013), we estimate a dynamic panel data model. We find that there is a strong relation between income and happiness. Further, individuals have a stronger aversion against unemployment than against inflation. We perform various robustness checks including cultural differences and additional driving forces such as gender inequality and macroeconomic policies. Finally, we identify happiness shocks using the performance of ones’ country at the FIFA World Cups. We show that movements in happiness can generate business cycles. Interestingly, happiness shocks increase income on impact but decrease it after 1 year.

KEYWORDS:

• Business cycles
• happiness
• macroeconomics

JEL CLASSIFICATION:

• D63
• E00
• I31

Acknowledgements

I would like to thank two anonymous referees for comments. Further, I am highly indebted to David Fielding, Stephen Knowles, Trent Smith and Tarja Viitanen for very helpful comments and suggestions. All remaining errors are my own.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. In a sense, we use this period as a natural experiment and observe happiness before, over and after this crisis.

2. Deaton (2014, p.1) with respect to the usefulness of happiness data writes, ‘even if the data on wellbeing have their problems and their critics, a flawed but broader measure, such as wellbeing, can lead to better policy than a flawed but narrow one, such as income’.

3. To be precise, the term ‘macro’ here refers to aggregate variables related to the business cycle. The definition for ‘micro’ is that those variables are observed at the individual level.

4. The absolute autocorrelation in the sample is 0.35.

5. Di Tella et al. (2001) also find that happiness is higher when inflation and unemployment are low.

6. https://worlddatabaseofhappiness.eur.nl/.

7. The precise timing (within each year) of the survey is unknown. However, each year, the same question is asked.

8. Appendix presents the key statistics of all time series.

9. Gudmundsdottir (2013) finds that the crisis had only limited effects on happiness in Iceland.

10. Appendix presents a robustness check using a different estimator confirming these results.

11. A final cautionary note is in order: given that the analysis is limited to 8 years, one full business cycle frequency, this might limit the ability to test the Easterlin Paradox. Here, the results will be largely driven by the cross-section variation.

12. Sacks et al. (2010) find that the effect of the level of GDP is larger in transition countries than in non-transition countries.

13. We also interact regions with the growth rate of GDP, which gives us smaller coefficients. Significance levels are identical to the country dummies.

14. The results are robust to controlling for CO₂ emissions and internet use.

15. The results are robust when adding Asia or Africa.

16. See also Hausmann, Tyson and Zahidi (2007). I also estimate a school enrolment variable that is adjusted for gender inequality. The results show that more gender equality in schooling significantly increases happiness. A further robustness check using the secondary completion rate of women supports this finding. The results are available upon request.

17. Our results are robust to using a simple World Cup participation indicator, an indicator of relative Gold medal performance won at Winter and Summer Olympics, the number of total Olympic medals won at Winter and Summer Olympics and an indicator of terrorist attacks.

18. Tests used were the Aikaike Information Criterion, the Bayesian Information Criterion and the Quasi-Information Criterion.

Additional information

Notes on contributors

Dennis Wesselbaum

Dennis Wesselbaum is a macroeconomist with both theoretical and empirical interests. My research interests are Macroeconomics (esp. Monetary and Fiscal Policy), Quantitative Economics, Economic Growth, Labor Economics, Econometrics, and Game Theory. My earlier work has mainly focused on labor market dynamics, e.g. combining search and matching frictions with efficiency wages orto disentangle the role played by the intensive and the extensive margin of labor adjustment. Most recently, I focus on issues related to the interaction between fiscal and monetary policy, the effects and transmission mechanisms of fiscal and monetary policy inthe short- and long-run, and, still, labor market dynamics. Most recently, my work studies international migration, central bank communication via social media, and firms' inflation expectations.