The Measurement of Race and Gender Wage Differentials: Evidence from the Federal Sector

ILR Review ◽  
1983 ◽  
Vol 37 (1) ◽  
pp. 79 ◽  
Author(s):  
George J. Borjas
Keyword(s):  
Wage Differentials ◽  
Federal Sector ◽  
Race And Gender ◽  
And Gender ◽  
Gender Wage Differentials

The Measurement of Race and Gender Wage Differentials: Evidence from the Federal Sector

ILR Review ◽  
1983 ◽  
Vol 37 (1) ◽  
pp. 79-91 ◽  
Author(s):  
George J. Borjas
Keyword(s):  
Wage Differentials ◽  
Wage Differential ◽  
Relative Wage ◽  
Federal Sector ◽  
Race And Gender ◽  
Black Females ◽  
Dummy Variable ◽  
Earnings Functions ◽  
And Gender ◽  
Gender Wage Differentials

This paper presents an empirical analysis of wage differentials based on race and gender in the federal bureaucracy. By focusing on the study of interagency variations in wage differentials, the author shows, first, that the use in earnings functions of a simple dummy variable to indicate race and gender leads to downward-biased estimates of the standardized wage differential. Second, across federal agencies there is a positive correlation between wage differentials based on race and those based on gender. Finally, the low relative wage of black females is more a result of their gender than of their race. This variety of empirical findings shows the promise of future studies that concentrate on the interfirm variance in employment policies that affect women and minorities.

Children and Gender ? Wage Differentials

Labour ◽  
1996 ◽  
Vol 10 (3) ◽  
pp. 511-537 ◽  
Author(s):  
Paola Tanda ◽  
Germana Bottone
Keyword(s):  
Wage Differentials ◽  
And Gender ◽  
Gender Wage Differentials

Occupational Segregation and Gender Wage Differentials: Evidence from Malaysia

2017 ◽  
Vol 31 (4) ◽  
pp. 381-401 ◽  
Author(s):  
Rahmah Ismail ◽  
Maryam Farhadi ◽  
Chung-Khain Wye
Keyword(s):  
Wage Differentials ◽  
Occupational Segregation ◽  
And Gender ◽  
Gender Wage Differentials

Early-Career Work Experience and Gender Wage Differentials

1995 ◽  
Vol 13 (1) ◽  
pp. 121-154 ◽  
Author(s):  
Audrey Light ◽  
Manuelita Ureta
Keyword(s):  
Work Experience ◽  
Wage Differentials ◽  
Early Career ◽  
And Gender ◽  
Gender Wage Differentials

Education and gender wage differentials in Portugal: what can we learn from an age cohort analysis?

2009 ◽  
Vol 17 (2) ◽  
pp. 263-278 ◽  
Author(s):  
Pilar González ◽  
Luis Delfim Santos ◽  
Maria Clementina Santos
Keyword(s):  
Wage Differentials ◽  
Cohort Analysis ◽  
Age Cohort ◽  
And Gender ◽  
Gender Wage Differentials

Referral Patterns for Youths Identified at Risk for Suicide by Trained Gatekeepers

Crisis ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 113-119 ◽  
Author(s):  
Michael S. Rodi ◽  
Lucas Godoy Garraza ◽  
Christine Walrath ◽  
Robert L. Stephens ◽  
D. Susanne Condron ◽  
...  
Keyword(s):  
Suicide Prevention ◽  
Demographic Characteristics ◽  
Service Access ◽  
Referral Patterns ◽  
Race And Gender ◽  
Lee Smith ◽  
Prevention Behavior ◽  
Key Variables ◽  
And Gender ◽  
To Receive

Background: In order to better understand the posttraining suicide prevention behavior of gatekeeper trainees, the present article examines the referral and service receipt patterns among gatekeeper-identified youths. Methods: Data for this study were drawn from 26 Garrett Lee Smith grantees funded between October 2005 and October 2009 who submitted data about the number, characteristics, and service access of identified youths. Results: The demographic characteristics of identified youths are not related to referral type or receipt. Furthermore, referral setting does not seem to be predictive of the type of referral. Demographic as well as other (nonrisk) characteristics of the youths are not key variables in determining identification or service receipt. Limitations: These data are not necessarily representative of all youths identified by gatekeepers represented in the dataset. The prevalence of risk among all members of the communities from which these data are drawn is unknown. Furthermore, these data likely disproportionately represent gatekeepers associated with systems that effectively track gatekeepers and youths. Conclusions: Gatekeepers appear to be identifying youth across settings, and those youths are being referred for services without regard for race and gender or the settings in which they are identified. Furthermore, youths that may be at highest risk may be more likely to receive those services.

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