| Title |
The impact of green digital finance on migration decisions: Evidence from China |
| ID_Doc |
62209 |
| Authors |
Zhuo, SH; Jia, L |
| Title |
The impact of green digital finance on migration decisions: Evidence from China |
| Year |
2024 |
| Published |
|
| DOI |
10.1007/s10668-024-05141-z |
| Abstract |
An important topic of how the burgeoning green digital finance development affects the resident migration decisions is explored in this research. Green digital finance has considerably elevated the quality of life for residents, which largely promotes migration. To conduct the empirical analysis, a unique dataset was compiled, combining the China Family Panel Studies in micro-level and the Digital Inclusive Finance Index in macro-level. This micro-level survey contains 156,133 observations covering 25 provinces in mainland China from 2012 to 2020 biannually. The logit model is employed as a robust tool for examining the importance of green digital finance in predicting migration decisions, which is more efficient than the traditional ordinary least squares method. Due to the relative minority proportion of migrants within the overall sample, SMOTE is utilized to address the sample imbalance issue. Our primary findings indicate that green digital finance significantly and positively affects migration decisions. This means that for areas with higher green digital finance, residents prefer to immigrate. The relationship is distinguished in terms of several subdimensions. The results of the sub-dimensional analysis show that coverage breadth, use depth, payment, insurance, and credit strongly promote migration decisions. Further analysis of the moderator effects on several personal characteristics reveals that marriage and education strengthen this positive effect on attracting migrants. Heterogeneity analysis suggested that green digital finance is more attractive to non-coastal residents than to coastal residents. |
| Author Keywords |
Green digital finance; Migration decisions; Logit model; Heterogeneity analysis; CFPS; China |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001251515700001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
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