Ma, WanglinVatsa, PuneetZheng, HongyunOwusu, VictorDonkor, Emmanuel2024-01-302024-01-302022-02-082022-02https://hdl.handle.net/10182/16819The present study examined the impacts of ICT adoption on objective and objective well-being inequality using 2018 China Family Panel Studies (CFPS) data. We used income inequality and consumption inequality to capture the objective well-being inequality, while happiness inequality and life-satisfaction inequality were used to capture objective well-being inequality. We employed the the two-stage residual inclusion (2SRI) model to address the endogeneity problem inherent in ICT adoption. We contribute to the growing literature on ICT adoption and household well-being in three important ways. First, we examine the impacts of ICT adoption on both objective well-being inequality (measured by the Gini coefficient) and subjective well-being inequality (measured by the variance). Specifically, we capture objective well-being inequality using income and consumption inequality and subjective well-being inequality using happiness and life-satisfaction inequality. Second, we apply a two-stage residual inclusion approach to address the endogeneity of ICT adoption emanating from self-selection of individuals as adopters and non-adopters, and the presence of systematic differences in observed heterogeneity between the two groups. Third, we investigate how objective well-being inequality affects subjective well-being and inequalities. The empirical results of the first-stage 2SRI model showed that people’s decisions to adopt ICTs are positively and significantly influenced by education, CCP membership, insurance ownership, dependency ratio, average education of household members, car ownership, and living in urban areas. Age and family size are two key factors that negatively affect people’s ICT adoption decisions. The second-stage estimates of the 2SRI model revealed that ICT adoption tends to lower income inequality and consumption inequality. Furthermore, ICT adoption significantly decreases happiness inequality but shows no effect on life-satisfaction inequality. The results indicated that the age of household heads, family size, and urban residence significantly lower income and consumption inequality, while the average education of household members significantly increases income and consumption inequality. We also found that subjective well-being inequality, as captured by happiness inequality and life-satisfaction inequality, is negatively influenced by age. The comparison analysis using the AIPW estimator revealed that the inequality effects of ICT adoption tend to be underestimated if one only controls for observable selection bias but ignores unobservable selection bias. Further analysis demonstrated that both income inequality and consumption inequality have insignificant impacts on happiness and life satisfaction. Income inequality significantly increases both happiness inequality and life-satisfaction inequality, while consumption inequality does not have a significant impact on objective well-being inequality.pp.45-45Conference Contribution - published