少子老龄化、工业智能化与宏观经济波动——基于内生经济增长理论的DSGE模型分析

Low Fertility and Aging,Industrial Intelligence and Macroeconomic Fluctuations:An Analysis of DSGE Model Based on Endogenous Economic Growth Theory

少子化与老龄化成为中国人口发展新特征,经济增长亟需探寻现代化新路径。本文基于内生经济增长理论,构建包含劳动力供给冲击、工业智能化、内生性技术创新的动态随机一般均衡模型,揭示工业智能化对少子老龄化负向影响的双重调节机制。研究发现:短期内,工业智能化可优化劳动力与资本要素配置,进而提升经济均衡总产出,有效缓解少子老龄化的不利冲击。然而这一调节效应呈现显著的时期异质性:长期内,工业智能化难以弥补研发型劳动力缺口,并可能引发过度替代、贫富分化和通货膨胀等问题,对经济长期可持续增长的支撑作用有限。研究结论表明:政府宜在合理布局工业智能化的同时,兼顾增进人力资本积累、提升自主创新质量,实现少子老龄化时代下的经济长期高质量发展。

The recent demographic shift in China,characterized by a low fertility and an aging population,presents critical challenges for economic growth,necessitating an urgent exploration of Chinese path to modernization.Based on the endogenous economic growth theory,this paper constructs a dynamic stochastic general equilibrium model that includes labor supply shocks,industrial intelligence,and endogenous technological innovation.Our findings are as follows:in the short term,industrial intelligence can raise the equilibrium output of the economy by optimising the allocation of labour and capital factors,which effectively mitigates negative impacts of low fertility and aging.However this moderating effect shows significant period heterogeneity.In the long term,industrial intelligence struggles to fill the gap of R&D-based labour.This also could lead to over-substitution,polarization of wealth and inflation.Thereby,industrial intelligence provides limited support for sustained economic growth.Taken together,the results demonstrate that the government may appropriately deploy industrial intelligence while concurrently focusing on enhancing human capital accumulation and improving the quality of independent innovation.This will lead to long-term,high-quality economic development in the time of low fertility and aging.