Analysing the Gender Wage Gap Using Personnel Records of a Large German Company

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Analysing the Gender Wage Gap Using Personnel Records of a Large German Company. / Pfeifer, Christian; Sohr, Tatjana.
Bonn: Forschungsinstitut zur Zukunft der Arbeit, 2008. (IZA-Discussion Paper; No. 3533).

Research output: Working paperWorking papers

Harvard

Pfeifer, C & Sohr, T 2008 'Analysing the Gender Wage Gap Using Personnel Records of a Large German Company' IZA-Discussion Paper, no. 3533, Forschungsinstitut zur Zukunft der Arbeit, Bonn. <http://ftp.iza.org/dp3533.pdf>

APA

Pfeifer, C., & Sohr, T. (2008). Analysing the Gender Wage Gap Using Personnel Records of a Large German Company. (IZA-Discussion Paper; No. 3533). Forschungsinstitut zur Zukunft der Arbeit. http://ftp.iza.org/dp3533.pdf

Vancouver

Pfeifer C, Sohr T. Analysing the Gender Wage Gap Using Personnel Records of a Large German Company. Bonn: Forschungsinstitut zur Zukunft der Arbeit. 2008 Jun. (IZA-Discussion Paper; 3533).

Bibtex

@techreport{4650f4b3e25d498fb133cf0f050bc47d,
title = "Analysing the Gender Wage Gap Using Personnel Records of a Large German Company",
abstract = "We use monthly personnel records of a large German company to analyse the gender wage gap (GWG). Main findings are: (1) the unconditional GWG is 15 percent for blue-collar and 26 percent for white-collar workers; (2) conditional on tenure, entry age, schooling, and working hours, the GWG is 13 percent for blue-collar as well as for white-collar workers; (3) after additionally controlling for hierarchical levels, the GWG is less than 4 percent for bluecollar and 8 percent for white-collar workers; (4) Oaxaca decompositions reveal that theunexplained part of the GWG is 87 percent for blue-collar workers and 46 percent for whitecollar workers; (5) males have larger absolute wage growths than females; (6) the relative GWG gets larger with tenure for blue-collar but smaller for white-collar workers; (7) individual absenteeism has no significant impact on the GWG; (8) the gender gap in absenteeism is between 26 and 46 percent. Overall, the results are consistent with statistical discriminationexplanations of the gender wage gap, though we cannot rule out other forms ofdiscrimination. A simple model within the context of absenteeism and statistical discrimination is offered.",
keywords = "Economics, Absenteeism, gender, personnel data, statistical discrimination, wage differentials, Gender and Diversity",
author = "Christian Pfeifer and Tatjana Sohr",
year = "2008",
month = jun,
language = "English",
series = "IZA-Discussion Paper",
publisher = "Forschungsinstitut zur Zukunft der Arbeit",
number = "3533",
type = "WorkingPaper",
institution = "Forschungsinstitut zur Zukunft der Arbeit",

}

RIS

TY - UNPB

T1 - Analysing the Gender Wage Gap Using Personnel Records of a Large German Company

AU - Pfeifer, Christian

AU - Sohr, Tatjana

PY - 2008/6

Y1 - 2008/6

N2 - We use monthly personnel records of a large German company to analyse the gender wage gap (GWG). Main findings are: (1) the unconditional GWG is 15 percent for blue-collar and 26 percent for white-collar workers; (2) conditional on tenure, entry age, schooling, and working hours, the GWG is 13 percent for blue-collar as well as for white-collar workers; (3) after additionally controlling for hierarchical levels, the GWG is less than 4 percent for bluecollar and 8 percent for white-collar workers; (4) Oaxaca decompositions reveal that theunexplained part of the GWG is 87 percent for blue-collar workers and 46 percent for whitecollar workers; (5) males have larger absolute wage growths than females; (6) the relative GWG gets larger with tenure for blue-collar but smaller for white-collar workers; (7) individual absenteeism has no significant impact on the GWG; (8) the gender gap in absenteeism is between 26 and 46 percent. Overall, the results are consistent with statistical discriminationexplanations of the gender wage gap, though we cannot rule out other forms ofdiscrimination. A simple model within the context of absenteeism and statistical discrimination is offered.

AB - We use monthly personnel records of a large German company to analyse the gender wage gap (GWG). Main findings are: (1) the unconditional GWG is 15 percent for blue-collar and 26 percent for white-collar workers; (2) conditional on tenure, entry age, schooling, and working hours, the GWG is 13 percent for blue-collar as well as for white-collar workers; (3) after additionally controlling for hierarchical levels, the GWG is less than 4 percent for bluecollar and 8 percent for white-collar workers; (4) Oaxaca decompositions reveal that theunexplained part of the GWG is 87 percent for blue-collar workers and 46 percent for whitecollar workers; (5) males have larger absolute wage growths than females; (6) the relative GWG gets larger with tenure for blue-collar but smaller for white-collar workers; (7) individual absenteeism has no significant impact on the GWG; (8) the gender gap in absenteeism is between 26 and 46 percent. Overall, the results are consistent with statistical discriminationexplanations of the gender wage gap, though we cannot rule out other forms ofdiscrimination. A simple model within the context of absenteeism and statistical discrimination is offered.

KW - Economics

KW - Absenteeism

KW - gender

KW - personnel data

KW - statistical discrimination

KW - wage differentials

KW - Gender and Diversity

M3 - Working papers

T3 - IZA-Discussion Paper

BT - Analysing the Gender Wage Gap Using Personnel Records of a Large German Company

PB - Forschungsinstitut zur Zukunft der Arbeit

CY - Bonn

ER -

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