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Going Beyond Average Joe's Happiness: Using Quantile Regressions to Analyze the Full Subjective Well-Being Distribution

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  • Martin Binder
  • Alex Coad

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.

Suggested Citation

  • Martin Binder & Alex Coad, 2010. "Going Beyond Average Joe's Happiness: Using Quantile Regressions to Analyze the Full Subjective Well-Being Distribution," Papers on Economics and Evolution 2010-10, Philipps University Marburg, Department of Geography.
    • Handle: RePEc:esi:evopap:2010-10
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    References listed on IDEAS

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    1. Ada Ferrer-i-Carbonell & Paul Frijters, 2004. "How Important is Methodology for the estimates of the determinants of Happiness?," Economic Journal, Royal Economic Society, vol. 114(497), pages 641-659, July.
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    Cited by:

    1. Martin Binder & Leonhard K. Lades, 2015. "Autonomy-Enhancing Paternalism," Kyklos, Wiley Blackwell, vol. 68(1), pages 3-27, February.
    2. Suhee Kim & Junghee Kim, 2017. "Analysis of Factors Affecting Quality of Life of Workers in Korea Participating in Leisure Activities Using Quantile Regression," Global Journal of Health Science, Canadian Center of Science and Education, vol. 9(7), pages 150-150, July.
    3. Martin Binder & Alex Coad, 2013. "Life satisfaction and self-employment: a matching approach," Small Business Economics, Springer, vol. 40(4), pages 1009-1033, May.
    4. Wenjing Han & Yang Fu & Wen Sun, 2023. "Farmland Transfer Participation and Rural Well-Being Inequality: Evidence from Rural China with the Capability Approach," Land, MDPI, vol. 12(7), pages 1-21, June.

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    More about this item

    Keywords

    quantile regressions; subjective well-being; happiness; life satisfaction; mental well-being; BHPS Length 32 pages;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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