Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/57546
Year of Publication: 
2010
Series/Report no.: 
Papers on Economics and Evolution No. 1010
Publisher: 
Max Planck Institute of Economics, Jena
Abstract: 
Standard regression techniques are only able to give an incomplete picture of the relationship between subjective well-being and its determinants since the very idea of conventional estimators such as OLS is the averaging out over the whole distribution: studies based on such regression techniques thus are implicitly only interested in Average Joe's happiness. Using cross-sectional data from the British Household Panel Survey (BHPS) for the year 2006, we apply quantile regressions to analyze effects of a set of explanatory variables on different quantiles of the happiness distribution and compare these results with an ordinary least squares regression. We also analyze some reversed relationships, where happiness enters the regression equation as an explanatory variable (e.g., the effects of happiness on individual's financial success). Among our results we observe a decreasing importance of income, health status and social factors with increasing quantiles of happiness. Another finding is that education has a positive association with happiness at the lower quantiles but a negative association at the upper quantiles.
Subjects: 
quantile regressions
subjective well-being
happiness
life satisfaction
mental well-being
BHPS
JEL: 
I20
I31
C31
Document Type: 
Working Paper

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