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Do Losses Bite More than Gains? Evidence from a Panel Quantile Regression Analysis of Subjective Well-being in Japan

Author

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  • Fang, Zheng
  • Niimi, Yoko
Abstract
This paper conducts an empirical analysis of the distributional effects of the determinants of happiness by applying quantile regression techniques to panel data from the “Preference Parameters Study” of Osaka University, a nationally representative survey conducted in Japan. The key question examined in the paper is whether we observe an asymmetry between the effects of positive and negative changes on individual happiness, and if it exists, whether it is observed uniformly across the happiness distribution. Such an asymmetry is referred to as loss aversion in prospect theory. Loss aversion effects are analyzed with respect to relative income as well as expected future income changes. We find that feeling relatively poor has a greater negative effect on happiness than the positive effect of feeling relatively rich, i.e., losses bite more than gains. However, no evidence for loss aversion is detected with respect to expected future income changes as individual happiness is found to be more sensitive to gains than to losses, though the happiness of the least happy group is found to be affected more by losses than by equivalent gains.

Suggested Citation

  • Fang, Zheng & Niimi, Yoko, 2015. "Do Losses Bite More than Gains? Evidence from a Panel Quantile Regression Analysis of Subjective Well-being in Japan," MPRA Paper 68059, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:68059
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    References listed on IDEAS

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    Cited by:

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    2. Martín Leites & Xavier Ramos, 2022. "The Effect of Relative Income Concerns on Life Satisfaction: Relative Deprivation and Loss Aversion," Journal of Happiness Studies, Springer, vol. 23(7), pages 3485-3515, October.

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    More about this item

    Keywords

    Happiness; Japan; Loss Aversion; Panel Quantile Regression; Subjective Well-being;
    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
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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