The Social And Cultural Determinants Of Happiness, And Internet’s Demonstration Effect

Recent decades have witnessed a large amount of research on happiness of developedeconomies as well as some recent study of happiness in China. Series of problems ineconomic development make people realize the importance of happiness research. Thispaper relies on Chinese Family Panel Studies (CFPS) data to investigate the social andcultural factors that affect happiness and the internet’s demonstration effect in China, whichis ignored in the literature. We find that health, mood, marriage and interpersonal factorsplay more significant roles in happiness than traditional economic factors. The values placedon the importance of different dimensions of life along with beliefs in sources of success andsocial problems also affect happiness. Happy people tend to value family, believe in hardwork, adapt to inequality, and pursue fun and achievements. Aspects related to workincluding earnings, work environments, promotion opportunities, work time requirementsand organizations working in also affect happiness significantly. Experience with injusticeand bad government services can significantly compromise happiness. Deep understandingof social culture could be helpful for making policies suitable for society. Relative incomehas been argued to be critical in happiness. Indeed, we find that more access to informationand a broader horizon lead urban people compare income nationwide instead of locally,while rural people do the opposite. Internet influences rural people’s happiness throughexpanding their horizons. Contrary to predictions in the literature, internet does not shownegative effects on the happiness level of rural low-income residents through shifting up theaverage income of reference group; rather, it shows positive effects through thedemonstration effect. That is, internet makes low-income group see the hope of a better lifeand enhances their confidence, so as to enhance their sense of happiness. This effect does notexist for higher income groups in rural areas or any group in cities. We use OLS regressionin our baseline analysis, with ordered probit and the fixed effect panel model for robustnesscheck.