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Panel Quantile Regressions and the Subjective Well-Being in Urban China: Evidence from RUMiC Data

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  • Zheng Fang

    (Southwestern University of Finance and Economics
    Nanyang Technological University)

Abstract

Using RUMiC data and a simple panel quantile regression method, this paper accounts for the time-invariant individual specific characteristics and investigates the heterogeneous effects of factors on the distribution of subjective well-being (SWB, measured by GHQ-12) in urban China. Comparing results from the pooled regression and fixed effect regression, we find that most results from pooled regressions are likely overestimated. Panel quantile regression results show that income affects the least happy 10 % group twice as much as the happiest 10 % people. Being unemployed brings down the happiness level by 0.97 points on average, but individuals with high SWB seem to be not significantly affected. The complete picture of the relationship between SWB and various factors would have been veiled without using quantile techniques. This paper therefore not only contributes to the happiness literature in China, but also adds evidence to stylized findings going beyond the average.

Suggested Citation

  • Zheng Fang, 2017. "Panel Quantile Regressions and the Subjective Well-Being in Urban China: Evidence from RUMiC Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 132(1), pages 11-24, May.
    • Handle: RePEc:spr:soinre:v:132:y:2017:i:1:d:10.1007_s11205-015-1126-z
    DOI: 10.1007/s11205-015-1126-z
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    Cited by:

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    2. Fang, Zheng & Niimi, Yoko, 2017. "Does everyone exhibit loss aversion? Evidence from a panel quantile regression analysis of subjective well-being in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 46(C), pages 79-90.
    3. Philippe Tessier & Josselin Thuilliez, 2018. "Does freedom make a difference?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1189-1205, November.
    4. David G. Blanchflower & Carol L. Graham, 2022. "The Mid-Life Dip in Well-Being: a Critique," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(1), pages 287-344, May.
    5. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, New Economic School (NES).
    6. Wang, Jinxian & Wang, Yangjie & Sun, Cuicui & Chen, Xiaohong, 2021. "Does mandatory air quality information disclosure raise happiness? Evidence from China," Energy Economics, Elsevier, vol. 94(C).
    7. Cristina Bernini & Silvia Emili & Federica Galli, 2021. "Does urbanization matter in the expenditure‐happiness nexus?," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1403-1428, December.
    8. Miri Endeweld & Anat Herbst-Debby & Amit Kaplan, 2022. "Do the Privileged Always Win? Economic Consequences of Divorce by Income and Gender Groups," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 77-100, January.
    9. Wang, Jinxian & Wang, Chen & Li, Sihao & Luo, Zhi, 2021. "Measurement of relative welfare poverty and its impact on happiness in China: Evidence from CGSS," China Economic Review, Elsevier, vol. 69(C).
    10. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, Center for Economic and Financial Research (CEFIR).

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    More about this item

    Keywords

    Subjective well-being; GHQ-12; Panel quantile regression; Heterogeneity; RUMiC; China;
    All these keywords.

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

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