File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Height conditions salary expectations: Evidence from large-scale data in China

TitleHeight conditions salary expectations: Evidence from large-scale data in China
Authors
KeywordsData analysis
Height premium
Regression model
Salary expectation
Statistical method
Issue Date2018
Citation
Physica A: Statistical Mechanics and its Applications, 2018, v. 501, p. 86-97 How to Cite?
AbstractHeight premium has been revealed by extensive literature, however, evidence from China based on large-scale data remains still lacking. In this paper, we study how height conditions salary expectations by exploring a dataset covering over 140,000 Chinese job seekers. By using graphical and regression models, we find evidence in support of height premium that tall people expect a significantly higher salary in career development. In particular, regression results suggest stronger effects of height premium on female than on male, however, the gender differences decrease as the education level increases and become insignificant after holding all control variables fixed. Further, results from graphical models suggest three promising ways in helping short people: (i) to accumulate more working experiences, since one year seniority can respectively make up about 3 cm and 7 cm shortness for female and male; (ii) to increase the level of education, since one higher academic degree may eliminate all disadvantages that brought by shortness; (iii) to target jobs in regions with a higher level of development. Our work provides a cross-culture supportive evidence of height premium and contributes two novel features to the literature: the compensation story in helping short people, and the focus on salary expectations in isolation from discrimination channels.
Persistent Identifierhttp://hdl.handle.net/10722/346660
ISSN
2023 Impact Factor: 2.8
2023 SCImago Journal Rankings: 0.661

 

DC FieldValueLanguage
dc.contributor.authorYang, Xiao-
dc.contributor.authorGao, Jian-
dc.contributor.authorLiu, Jin Hu-
dc.contributor.authorZhou, Tao-
dc.date.accessioned2024-09-17T04:12:24Z-
dc.date.available2024-09-17T04:12:24Z-
dc.date.issued2018-
dc.identifier.citationPhysica A: Statistical Mechanics and its Applications, 2018, v. 501, p. 86-97-
dc.identifier.issn0378-4371-
dc.identifier.urihttp://hdl.handle.net/10722/346660-
dc.description.abstractHeight premium has been revealed by extensive literature, however, evidence from China based on large-scale data remains still lacking. In this paper, we study how height conditions salary expectations by exploring a dataset covering over 140,000 Chinese job seekers. By using graphical and regression models, we find evidence in support of height premium that tall people expect a significantly higher salary in career development. In particular, regression results suggest stronger effects of height premium on female than on male, however, the gender differences decrease as the education level increases and become insignificant after holding all control variables fixed. Further, results from graphical models suggest three promising ways in helping short people: (i) to accumulate more working experiences, since one year seniority can respectively make up about 3 cm and 7 cm shortness for female and male; (ii) to increase the level of education, since one higher academic degree may eliminate all disadvantages that brought by shortness; (iii) to target jobs in regions with a higher level of development. Our work provides a cross-culture supportive evidence of height premium and contributes two novel features to the literature: the compensation story in helping short people, and the focus on salary expectations in isolation from discrimination channels.-
dc.languageeng-
dc.relation.ispartofPhysica A: Statistical Mechanics and its Applications-
dc.subjectData analysis-
dc.subjectHeight premium-
dc.subjectRegression model-
dc.subjectSalary expectation-
dc.subjectStatistical method-
dc.titleHeight conditions salary expectations: Evidence from large-scale data in China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.physa.2018.02.151-
dc.identifier.scopuseid_2-s2.0-85042729692-
dc.identifier.volume501-
dc.identifier.spage86-
dc.identifier.epage97-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats