Title page for ETD etd-11252003-050633

Type of Document

Dissertation

Author

Aydin, Necati

Author's Email Address

naydin@cefa.fsu.edu

URN

etd-11252003-050633

Title

Gender Wage Differentials and Under-representation of Women in IT Education Programs and IT Workforce

Degree

Doctor of Philosophy

Department

Middle and Secondary Education, Department of

Advisory Committee

Advisor Name	Title
John P. Lunstrum	Committee Co-Chair
Victoria M. MacDonald	Committee Co-Chair
Douglas N. Harris	Committee Member
James H. Cobbe	Committee Member
John H. Hansen	Committee Member

Keywords

IT Workers
Gender Wage Differentials
Discrimination
Earnings
Women

Date of Defense

2003-11-11

Availability

unrestricted

Abstract

This study examines the determinants of earnings and gender wage differentials for Florida’s IT graduates and IT workers by using the Mincerian regression model and the Blinder-Oaxaca wage decomposition model. Florida Education and Training Placement Information Program (FETPIP) data and Census Microdata (PUMS) are used in both models to shed some light on the increasing under-representation of women in the IT workforce. The study finds that there has been little or no gender wage difference for IT graduates from the Community Colleges (CC) and Post-Secondary Education (PSE) programs, while there has been an increasing gender wage difference for the Public University (SUS) IT graduates since 1993. The gender coefficients from the Mincerian regression models indicate that the rate for the SUS IT graduates increased from its low value of 2% to the high value of 12% in the year 2002.
The gender wage differential rates for the SUS IT graduates measured from the Blinder-Oaxaca model are consistent with the Mincerian Regression results. The wage decomposition model reveals that the gender wage differentials for SUS IT graduates increased from 10% in the year 1996, to 18% in the year 2002. The model further indicates that 30% of this wage gap in the year 2002 was due to gender discrimination. The study finds that a proxy experience variable overestimates the impact of experience on earnings for female workers. The study presents a notable difference between the impact of the actual experience variable based on FETPIP data and that of a proxy variable based on the PUMS data.

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