Following Rosenbaum and Rubin (1983), we employ PSM to reconstruct counterfactuals using observational data. In our paper, the key variable of interest, 𝐹 𝑖 (financial inclusion) is binary, thus we can set this as the treatment variable. Using one-to-one matching, Table S1 shows the balancing of the variables before and after matching.After matching, all variables are well balanced, providing a bias of less than 5 per cent (%bias<5%).Moreover, because all t-test are not significant, we cannot reject that null hypothesis that there is no systematic difference between treatment and control groups. Figure S1 shows the histogram of matched sub-samples along common support. It shows that most of the observations are on support.
This paper studies the relationship of financial development and income inequality in China over the period of 1978-2013. Using the structural vector auto-regression (SVAR), the empirical results are consistent with the G-J hypothesis of an inverted U-shaped relationship between financial development and income inequality. An economy in its initial stages of financial development would present increasing inequality and only in a second or even third stage of development would inequality actually decrease. The evidence is valid for two indicators defined to measure the scale and the efficiency of financial development, respectively. Financial reform aimed at forming an appropriate financial system should be accelerated to help to reducing income inequality in China.
Using four waves of longitudinal data from the China Family Panel Studies (CFPS), we examine the effects of income inequality on subjective wellbeing (SWB). We take a dual approach in measuring income inequality, and thus, we examine the effects of inequality using province-level Gini coefficient as well as between-group inequality or identity-related inequality defined as the income gap between migrants without urban household registration identity (hukou) and urban residents. We find negative effects of both province-level income inequality and between-group income inequality on SWB, measured by life satisfaction. Our results also show that the effects of income inequality on SWB is stronger for rural hukou residents compared to urban hukou residents. These findings are robust to alternative ways of measuring SWB and income inequality. In addition, we find evidence suggesting that neighbourhood trust is an important channel through which income inequality operates to reduce SWB. We suggest policies that promote trust in communities with high inequality with a view of addressing the negative effects of inequality on SWB.
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