| Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|
|
|---|---|---|
| Article Number | 01044 | |
| Number of page(s) | 5 | |
| Section | Big Data Analysis Application and Energy Consumption Research | |
| DOI | https://doi.org/10.1051/e3sconf/202021401044 | |
| Published online | 07 December 2020 | |
The Impact of Healthy Human Capital on the Labor Participation of Chinese Elderly
1 School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
2 School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
a 18113024@bjtu.edu.cn
b* 17120547@bjtu.edu.cn
The labor participation of the elderly is an important level of labor supply in China, and healthy human capital is one of the main factors affecting the labor participation of the elderly. Based on the data of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2014, this paper uses the Probit model to empirically analyze the impact of the healthy human capital of the elderly in China on their labor force participation rate. The results show that when individual characteristic variables, family characteristic variables and social characteristic variables are added, healthy human capital is positively correlated with labor participation of retired elderly people. The better health status is, the higher labor participation rate is. With the decline in health status, the labor force participation rate of retired elderly people decreased significantly. The influence of healthy human capital on labor participation of the elderly in China is also heterogeneous between urban and rural areas, gender and age, among which the influence of healthy human capital on labor participation of the elderly in rural areas, males and young age groups is higher than that in urban areas, females and elderly retirees.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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