A Nonparametric Quantile Analysis of Intergenerational Mobility in China

Scientifically measuring intergenerational mobility (IGM) and comprehensively analyzing the effects of factors influencing IGM provide a theoretical basis to improve public policies. This paper measures the elasticity of IGM in China and investigates the interaction effects of macro and micro influencing factors using a nonparametric gradient boosting tree quantile regression model. The empirical results show that, first, the gradient boosting tree quantile regression model fits better than the linear quantile regression model, with particularly significant nonlinear characteristics among those with annual incomes between ¥30,000 and ¥150,000. The intergenerational income elasticity in China ranges from 0.1861 to 0.7026, indicating a clear ``strong at both ends and weak in the middle'' effect of parental income on offspring income. Second, intergenerational income mobility exhibits heterogeneity in both income and region, with significant differences in the income transmission process and degree of nonlinearity across different regions. Third, this paper specifically explores the IGM characteristics of the two income groups, revealing that the most significant influencing factors for achieving income stratification are economic growth, industrial optimization, intergenerational educational mobility, and wealth capital investment. Finally, this paper explores the poverty trap from the perspective of IGM, showing that in eastern regions, children from wealthy families may experience higher immobility or a wealth trap, while in other regions, children from impoverished families experience higher immobility or a poverty trap.