From Average Joe's happiness to Miserable Jane and Cheerful John: using quantile regressions to analyze the full subjective well-being distribution

By Martin Binder, Alex Coad. 2011

460 citations recorded by the source corpus.

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 a standard regression. 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. We explore the robustness of our findings in various ways.

Subfields: Health, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/9290f225c73df5fb773af7708dad854ff1c7b154

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Citations in the corpus

Asymmetric impact of fiscal decentralization and environmental innovation on carbon emissions: Evidence from highly decentralized countries (2021, methodology): “Furthermore, this procedure is considered more efficient, where the association between conditional means of two variables are insignificant.(103) In the current study, the Method of Moments Quantile Regression (MMQR) with fixed effects by Machado and Silva is employed.”
The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression (2016, background): “However, traditional regression techniques focus on the mean effects, which may lead to under- or over-estimating the relevant coefficient or even failing to detect important relationships (Binder and Coad, 2011).”
The relationship between financial efficacy, satisfaction with remuneration and personal financial well-being (2014, background): “Some researchers found that an increase in remuneration only leads to a small increase in well-being (Frey & Stutzer, 2000; Diener, Sandvik, Seidlitz, & Diener, 1993; Oswald, 1997; Easterlin, 1974; Binder & Coad, 2011).”
Measuring flourishing: The impact of operational definitions on the prevalence of high levels of wellbeing (2014, methodology): “Binder and Coad (2011) find that the importance to wellbeing of factors such as education and income diminishes at higher levels of the wellbeing distribution.”
Bentham or Aristotle in the Development Process? An Empirical Investigation of Capabilities and Subjective Well-Being (2015, methodology): “Quantile regressions do not assume that the error terms are identically distributed at all points of the conditional distribution, which allows for individual heterogeneity as the slope parameters differ along the quantiles (Binder & Coad, 2011).”
Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment (2018, background): “…relationship between independent and dependent variables at various quantiles and the relevant coefficients can be evaluated more accurately than using traditional regression techniques, which tend to assess the mean effect and may fail to detect significant relationship (Binder and Coad, 2011).”