Article

Subjective well-being and its determinants in rural China

School of Sociology and Social Policy, University of Nottingham, Nottingham NG7 2RD, UK
China Economic Review (Impact Factor: 0.94). 12/2009; DOI: 10.1016/j.chieco.2008.09.003
Source: RePEc

ABSTRACT A national household survey for 2002, containing a specially designed module on subjective well-being, is used to estimate pioneering happiness functions in rural China. The variables that are predicted by economic theory to be important for happiness prove to be relatively unimportant. Our analysis suggests that we need to draw on psychology and sociology if we are to understand. Rural China is not a hotbed of dissatisfaction with life, possibly because most people are found to confine their reference groups to the village. Relative income within the village and relative income over time, both in the past and expected in the future, are shown to be important for current happiness, whereas current income is less so. Even amidst the poverty of rural China, attitudes, social comparisons and aspirations influence subjective well-being. The implications of the findings for the future and for policy are considered.

0 Bookmarks
 · 
90 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The study examines the association between subjective well-being and income, using data of 3 600 individuals from the TÁRKI Household Monitor for the year 2007. To explore this relationship, most of the relevant empirical papers use either ordinary least squares (OLS) regression or ordered probit model, but the authors follow different approaches. Comparing the results of OLS regression with quantile regression and the ordered probit model with a generalized ordered probit model, they show that more flexible techniques provide a more complete picture of the income-satisfaction relationship. According to OLS regression, income has a positive impact on satisfaction, but the quantile regression models show that this association is weaker at the upper end and stronger at the lower end of the conditional distribution of well-being. The standard ordered probit model predicts a significant positive effect for the highest satisfaction category, whereas the generalized model finds that income does not affect the probability of this highest response. In addition, the generalized ordered probit model shows a more negative effect on the lower response categories of satisfaction than the standard ordered probit model. The results suggest that higher income reduces unhappiness, but one can be satisfied without high income as well. The findings draw attention to the importance of method selection in satisfaction research.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Does more money always mean that people are happier with their lives? To test the social comparison hypothesis as applied to happiness, this study uses survey data from the 2002 Chinese Household Income Project to examine the association between household economic resources and happiness in urban China. Household economic resources are measured as both income and assets (e.g., net worth and net worth minus home equity). In addition, the analyses include measures of relative income and relative assets. Results of ordinary least square regression analysis show a positive association of absolute income with the happiness score whereas relative income is negatively associated with happiness. Although household assets are a significant and positive predictor of self-assessments of happiness, measures of relative household assets do not correlate with happiness. Study findings suggest the level of happiness among urban populations could be increased through policies that promote pro-poor growth and equal distribution of economic resources. In addition, introducing asset-building policies as supplements to other social assistance programs may promote happiness.
    Social Indicators Research 03/2015; DOI:10.1007/s11205-015-0936-3 · 1.26 Impact Factor
  • Social Indicators Research 01/2015; DOI:10.1007/s11205-015-0864-2 · 1.26 Impact Factor

Full-text (2 Sources)

Download
48 Downloads
Available from
May 19, 2014