Population aging, technological innovation and industrial differentiation
Bibliographic Data
| ID | 22088613 |
|---|---|
| Authors | Chunhua Li (0000-0003-2224-7365, Guangxi University for Nationalities), Zhangqing Chen (Guangxi University for Nationalities), Wangchun Wu, Wei-Xiong Wu (Guangxi University for Nationalities, corresponding author), Bin Gao (0009-0001-6001-7790, Guangxi University for Nationalities, corresponding author), Lingfeng Zou (Guangxi University for Nationalities) |
| Year | 2025 |
| Volume | 13 |
| Pages | 1502713-1502713 |
| Publication date | 2025-01-27 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2025.1502713 |
| PMID | 39931297 |
| OpenAlex | W4406851776 |
| Language | EN |
| References cited | 42 |
As China’s aging population deepens and its pace accelerates, it is particularly crucial to rely on technological innovation to drive industrial differentiation. Is there a connection between population aging, technological innovation, and industrial differentiation? Does technological innovation have a moderating effect? Based on the panel data of 31 provinces in China from 2006 to 2022, this paper constructs the entropy index to measure the overall industrial differentiation and tertiary industrial differentiation in China, and subsequently investigates the relationship among the three using the two-way fixed effect model. The results indicate that population aging has a significant positive impact on the overall industrial differentiation in China, with a regression coefficient of 1.1025. Technological innovation plays a positive moderating role, with an interaction coefficient of 0.3489. The effects of population aging on the differentiation of the three industries differ: the regression coefficient for the primary industry is −0.6437, which is significantly negative; for the secondary industry, the regression coefficient is 0.9252, which is statistically insignificant; and for the tertiary industry, the regression coefficient is 0.1539, which is significantly positive. The government should encourage enterprises to invest in technology research and development through tax cuts and subsidies, and enterprises should absorb high-quality talents, carry out intelligent transformation of traditional industries of enterprises, and improve their competitiveness
Business · China · Econometrics · Economics · Geography · Industrial organization · Macroeconomics · Market economy · Panel data · Population · Population ageing · Regression analysis · Statistics · Subsidy · Technological change · Economic and Technological Innovation · Energy, Environment, Economic Growth · Innovation Diffusion and Forecasting · Mathematics · Medicine
| Citation velocity | historical |
|---|---|
| Highly cited | No |