Going beyond average Joe's Happiness: Using quantile regressions to analyze the full subjective well-being distribution

Arbeitspapier

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.

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• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Papers on Economics and Evolution ; No. 1010

Classification and Topics

• Classification: Wirtschaft ; Education and Research Institutions: General ; General Welfare; Well-Being ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
• Subject: quantile regressions ; subjective well-being ; happiness ; life satisfaction ; mental well-being ; BHPS ; Zufriedenheit ; Lebensqualität ; Einkommensverteilung ; Schätzung ; Großbritannien

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Binder, Martin ; Coad, Alex
• Event: Veröffentlichung
• (who): Max Planck Institute of Economics
• (where): Jena
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/57546