Subjective well-being and its determinants in rural China

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 predicted by economic theory to be important for happiness are relatively unimportant. The 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 influence happiness. 'Subjective well-being poverty' functions are estimated, in which income and various proxies for 'capabilities' and 'functionings' appear as arguments. Even amidst the poverty of rural China, social functionings, attitudes and expectations are important to subjective well-being.

Identity, Inequality, and Happiness: Evidence from Urban China

“…Luo (2006) explores the effects of unemployment on happiness and finds that families with unemployed members have lower happiness scores. Knight et al (2009) examined the role of absolute and relative income on the happiness of rural Chinese residents, and their results agree with intuition: higher household income per capita results in a higher happiness level; higher relative income status within a village also leads to higher happiness. Knight and Gunatilaka (2010b) studied the happiness determination of rural migrants.…”

“…Our explanation is similar to that of Knight et al (2009). : in an era of rapidly increasing incomes, people may optimistically expect their future opportunities to be at the higher end of the income distribution (demonstration effect).…”

“…They attribute it to the perception of worsening income distribution in China. However, in exploring determinants of happiness in rural China, Knight et al (2009) find that happiness of rural residents is positively associated with countylevel income Gini coefficients. This can be explained using the metaphor of "the tunnel effect": when you are stuck in a tunnel and see cars in front of you move, you feel happy.…”

“…The second reason is that we control the interaction terms in our regression, and it is difficult to interpret the marginal effects of the interacted variables when using ordered probit/logit. Knight et al (2009) and Gunatilaka (2010a, 2010b) also used OLS to explore happiness determination in China. Of course, we also estimated ordered probit models and found that ordered probit models and the corresponding OLS results are consistent in terms of the signs and significance of the coefficients.…”

“…So we add several city-level variables, including per capita GDP, population growth, whether the city is big, 8 Rather surprisingly, after controlling BI, the city-level Gini coefficient is significantly positive. Interestingly, Knight et al (2009) 8 The criterion of defining a big city is whether it had more than 1.5 million non-agricultural population in 1990.…”