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Author:

Meng, Zhang (Meng, Zhang.) | Hong, Feng (Hong, Feng.) (Scholars:冯虹)

Indexed by:

CPCI-SSH

Abstract:

The number of peasant laborers is large, the wage income level is relatively low, and the gap in wages in the labor market caused by regional segmentation is more obvious in China. The results of HLM (hierarchical linear model) show that the ICC value of wage in different provinces is 8.4%, with significant differences. The nine individual factors, such as gender and education, have a significant influence, which can explain 17.9% of the differences. The five area factors, such as the consumer price index, the commodity price index, have a significant impact, which can explain 72.4% of the differences. Gender, education, marital status, and range of outflows have a significant impact. The wage of peasant laborers is closely related to the regional characteristics and is affected by the regional labor market segmentation. It is proposed to further improve policies such as minimum wage standards, labor market supervision, industry wage level management, and personal characteristic wage protection, increase development efforts, and create a good development environment and conditions.

Keyword:

Regional segmented Peasant laborers Wage HLM (hierarchical linear model)

Author Community:

  • [ 1 ] [Meng, Zhang]Beijing Univ Technol, Coll Econ & Management, Beijing, Peoples R China
  • [ 2 ] [Hong, Feng]Beijing Univ Technol, Coll Econ & Management, Collaborat Innovat Ctr Beijing Soc Bldg & Social, Beijing, Peoples R China

Reprint Author's Address:

  • 冯虹

    [Hong, Feng]Beijing Univ Technol, Coll Econ & Management, Collaborat Innovat Ctr Beijing Soc Bldg & Social, Beijing, Peoples R China

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Source :

PROCEEDINGS OF THE 2019 5TH INTERNATIONAL CONFERENCE ON HUMANITIES AND SOCIAL SCIENCE RESEARCH (ICHSSR 2019)

ISSN: 2352-5398

Year: 2019

Volume: 319

Page: 753-757

Language: Chinese

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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