在线数据揭示预期薪金的影响因素

Online Data Reveal Key Factors on Salary Expectation

  • 摘要: 数据资源的丰富和分析方法的创新,促使社会经济学逐渐转变为数据驱动的定量化学科。作为定量化人力资源的组成部分,薪金研究对社会经济发展有重要意义。然而,以往研究大多基于规模有限的普查数据,对不同经济和文化背景的考虑也不足。本文基于中国人力资源网站获取的大规模简历数据,分析了多种因素对求职者预期薪金的影响,结果发现身高、工作经验和教育程度等因素影响预期薪金,并且男女存在显著的差异。其中,女性平均预期低于男性,相比男性差大约五年工作经验或一个教育学位。最后,多变量回归方法验证了分析结果的鲁棒性。

     

    Abstract: The enrichment of data resources and the innovation of analytic methods are gradually facilitating the transformation of socioeconomics into a data-driven and quantitative discipline. As a part of quantitative human resources, the investigation of salary has a significant role on social and economic development. However, previous studies are mainly based on census data with limited sizes and lack of considerations in a different economic and cultural background. Based on large-scale resume data that were crawled from websites of Chinese human resource service providers, this paper analyzes key factors on job seekers' salary expectation. Results suggest that height, working experiences, and educational degree affect salary expectation, and there are significant gender differences. In particular, females have lower salary expectation on average and lag behind males for five years' working experience or one educational degree. Finally, the robustness of the analytical results is checked using the multivariate regression method.

     

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