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Academic Journal of Business & Management, 2023, 5(21); doi: 10.25236/AJBM.2023.052114.

A Study of the Gender Wage Gap Based on Big Data Regression Analysis of the Urban Employed Population and Wages: A Technological Progress Perspective

Author(s)

Boxin Hao

Corresponding Author:
Boxin Hao
Affiliation(s)

Chengdu Jinjiang Jiaxiang Foreign Languags High School, Chengdu, China

Abstract

The concept of wage propensity coefficient is introduced, a mathematical model is established to accurately measure the gender wage propensity index, and a regression model is further established to analyze the impact of technological progress on gender wage gap by using the big data of China's urban employed population and wages. The results found that technological progress and the proportion of urban female employed persons to all urban employed persons are important factors affecting the gender wage gap in urban areas, and the female wage propensity index increases with the increase of technological progress, and decreases with the increase of the proportion of urban female employed persons to all urban employed persons. Among them, technological progress has a greater impact, for every one-point increase in technological progress, the wage propensity index of women increases by 5.15%. Technological progress has helped to increase the wage propensity index of employed women, thereby contributing to the reduction of the gender wage gap. It is suggested that, firstly, the influence of women's own characteristics such as education and years of working experience should be improved; secondly, women's employment should be promoted, and the proportion of urban women employed in the total number of urban employed persons should be expanded; and thirdly, the simultaneous improvement of women's employment and wages should be ensured, and technological advancement should be strengthened even more.

Keywords

Population; Wage; Gender wage gap; Technological progress; Big data

Cite This Paper

Boxin Hao. A Study of the Gender Wage Gap Based on Big Data Regression Analysis of the Urban Employed Population and Wages: A Technological Progress Perspective. Academic Journal of Business & Management (2023) Vol. 5, Issue 21: 96-102. https://doi.org/10.25236/AJBM.2023.052114.

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