## 3 Results
### Influencing Factors of Interprovincial Rural Migration  
To enhance data stability and mitigate scale-related biases, all variables were logarithmically transformed. The result of the Lagrange Multiplier (LM) test (\(p\) = 0.000) indicates that the random effect (RE) model is superior to the mixed effects model, and the result of the Hausman test (\(p\) = 0.000) indicates that the fixed effect (FE) model is superior to the RE model. Further, a comparison of the individual FE model and the two-way fixed-effects (FE_TW) model was conducted, and the results strongly reject the original hypothesis of no time fixed effects, leading to the selection of the FE_TW model. Due to the presence of explanatory variables that do not change over time, this study utilized the Least Squares Dummy Variable (LSDV) method, which allows for both fixed effects and the observation of variables that do not change over time. As a result, the LSDV method is employed to diagnose the drivers of interprovincial migration of China's rural population from 2000 to 2020 (Table 4). The results indicate that per capita GDP, natural disasters, topographic relief, and spatial distance are the primary drivers of interprovincial rural migration. Additionally, the rural hukou population and internet penetration rate also play significant roles. The effect of rural hukou populations in the destination province on the scale of interprovincial rural migration is significantly positive, which is not in line with expectations. This may be due to the fact that the size of the rural hukou population reflects, to a certain extent, the general situation of rural natural and human systems of the destination province. The large size of the rural hukou population implies that the province's villages have socio-economic and resource-environmental advantages, thus attracting population immigration. In the source regions, the effect of the total rural hukou population on interprovincial rural migration is not statistically significant. Economic development level, as represented by per capita GDP, is an important factor influencing interprovincial rural migration. A high level of economic development means that the province can provide more employment opportunities and that the income level of  
\begin{table}
\begin{tabular}{l c c c c c c c c c} \hline  & \multicolumn{2}{c}{**OLS**} & \multicolumn{2}{c}{**RE**} & \multicolumn{2}{c}{**FE**} & \multicolumn{2}{c}{**FE\_TW**} & \multicolumn{2}{c}{**LSDV**} \\ \cline{2-10}  & **Coefficient** & \(\mathbf{z}\) & **Coefficient** & \(\mathbf{z}\) & **Coefficient** & \(\mathbf{z}\) & **Coefficient** & \(\mathbf{z}\) & **Coefficient** & \(\mathbf{z}\) \\ \hline \(\ln S\_\)_propu_ & 0.44 *** & \(-\)7.16 & 0.58 *** & 12.45 & \(-\)0.06 & \(-\)0.57 & \(-\)0.15 & \(-\)1.18  
the people is higher. Accordingly, the province can attract more rural migrants from other provinces while retaining its rural population. A 1% decrease in the source's economic development level increases interprovincial rural migration by 0.21%, while a 1% increase in the destination's economic development level boosts rural immigration by 0.41%. Natural disasters have a significant impact on interprovincial rural migration. Human instincts to seek benefits and avoid harm dictate that people tend to avoid areas prone to natural disasters since their basic security needs cannot be met and their productive and living activities cannot be effectively conducted in such areas. This situation is significant not only in the source provinces but also in the destination provinces. Every 1% increase in natural disasters in the source regions is associated with a 0.11% increase in rural emigration, and every 1% increase in natural disasters in the destination is associated with a 0.09% decrease in rural immigration. Topographic relief is an important indicator of regional physical geography. Large topographic relief often implies poor spatial connectivity and accessibility, which is not conducive to productive and living activities.