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Regional Heterogeneity of Life Satisfaction in Urban China: Evidence from Hierarchical Ordered Logit Analysis

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Abstract

Given sheer geographic size and unequal regional development, common wisdom may attribute the heterogeneity of individual subjective wellbeing largely to regional disparity in China. Using a hierarchical ordered logit model and the Subjective Survey for Chinese Livelihood Index in 2012, this study however finds that regional factors only account for 3.7 % of total variance of individual subjective wellbeing in urban China. It implies that regional differences are not important for explaining individual happiness though some regional variables are statistically significant. Correspondingly, the Chinese governments should make policies down to individual level to promote people's life satisfaction. Other findings on income and social demographical variables are consistent with the current studies.

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Notes

  1. For per capita GDP, it has increased by nearly 20 times from 1978 to 2014 (NBS 2015). In 2012, China entered into the upper middle income country according to the World Bank and became the largest economy in the world based on GDP volume measured by purchasing power parity (PPP) in 2014.

  2. In addition, Li and Raine (2014) also find Chinese people have been experiencing a marked decline of life satisfaction by multiple national representative samples.

  3. The effect of relative income on happiness has been confirmed in China. For instance, Knight et al. (2009) find that relative income within the village is very important in rural China, while the absolute income is not so important.

  4. Such as income (Chu and Hail 2013; Knight et al. 2009; Zhang and Tsang 2013), cultural conceptions of happiness (Lu 2001; Lu and Gilmour 2004), perceived quality of life (Chappell 2005), satisfaction with different life domains (Appleton and Song 2008), acculturation (Zheng et al. 2004), employee involvement and participation (Cheng 2013), individualism (Steele and Lynch 2013), social grouping (Cheung and Leung 2004), and social support (Chan and Lee 2006). On different social groups, such as rural residents (Davey et al. 2009; Ji et al. 2002; Knight et al. 2009), urban residents (Appleton and Song 2008; Hu 2013; Smyth et al. 2010), and rural–urban migration (Dai et al. 2006; Knight and Gunatilaka 2010a, b; Nielsen et al 2010).

  5. According to NBS (2015), the per capita GDP gap between the richest and the poorest region amounts to about four times in 2014.

  6. Though religion is known to be related to subjective wellbeing, the religion variable is not included in the study, because religion is correlated with regional effects. For instance, China has three provincial Autonomous Regions which are linked to religions: namely, Ningxia Hui Autonomous Region and Xinjiang Uyghur Autonomous Region for Islamic religion and Tibet Autonomous Region for Buddhism religion. It exactly can be captured by the hierarchical ordered logit model.

  7. The average life satisfaction score for the widowed is slightly higher than the married, perhaps due to its small sample size (1.9 % of total sample). The widowed usually are seniors, and have good economic status.

  8. We do not include the provincial variables in Table 2 into the coefficients of other level-1 variables except for log (per capital income), because the mixed model would very long, and can not reach convergence.

  9. This study was based on a survey among Beijing inhabitants.

  10. According to the fifth and sixth population census, China has made great achievements on education. For example, the proportion with primary school or below in urban China decreased dramatically from 21.2 % in 2000 to 13.4 % in 2010, and the proportion of high education groups, including associate bachelor, bachelor, and postgraduate, increased significantly from 13.3 % in 2000 to 23.4 % in 2010.

  11. According to NBS (2012), gender ratios between males and females are 1.19 for aged 0–9, 1.17 for aged 10–14, and 1.10 for aged 15–19.

  12. For example, a comparative study conducted by Tafarodi et al. (2012) shows that Chinese university students consider a happy and healthy family as the most important factor in assessing the worth of their lives as compared with Canadian, Indian, and Japanese students.

  13. According the sixth population census, the urbanization rate was 49.7 % in China, but the proportion of non-agricultural hukou was only 28 %.

  14. However, migrants who don’t have a regular residence or whose residences do not install a fixed telephone are generally excluded in this survey.

  15. This finding is compatible with other studies, such as Di Tella et al. (2001), Stutzer (2004), and Lelkes (2006). For example, Lelkes (2006) found that unemployment reduces the probability of a high life satisfaction score by 19 %, and a high overall happiness score by 15 % in European countries.

  16. The employment proportion in the state-owned enterprises decreased from 35 % in 2000 to 18.7 % in 2011, and that in the privately-owned enterprises or self-employment increased from 14.7  % in 2000 to 33.8 % in 2011 (NBS 2012).

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Acknowledgments

The authors would like to thank China Development Research Foundation (CDRF) for providing the data used in this paper, and three anonymous reviewers and Dr. Filomena Maggino for the constructive comments. The author acknowledges the financial support from the National Natural Science Foundation of China (Project No. 71273006) and the Independent Scientific Research Fund of Tsinghua University. Content of this paper is solely the responsibility of the authors.

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Authors and Affiliations

  1. School of Public Policy and Management, Tsinghua University, Beijing, China

    Shaojie Zhou

  2. College of Economics and Management, Jilin Agricultural University, Jilin, China

    Xiaohua Yu

  3. Courant Research Centre ‘Poverty, Equity and Growth’, University of Goettingen, 2027, Platz der Goettinger Sieben 5, 37073, Goettingen, Germany

    Xiaohua Yu

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  1. Shaojie Zhou
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Zhou, S., Yu, X. Regional Heterogeneity of Life Satisfaction in Urban China: Evidence from Hierarchical Ordered Logit Analysis. Soc Indic Res 132, 25–45 (2017). https://doi.org/10.1007/s11205-016-1377-3

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