Examining gender discrimination in the labor force : evidence from gender pay gap and promotion in trading firms in Singapore
Gender discrimination remains as a global pervasive problem despite the implementation of substantial national and international measures to promote gender equality. Today, we continue living in a socially segregated and misogynistic world, where females were often viewed to be inferior and weak rel...
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Format: | Final Year Project |
Language: | English |
Published: |
2017
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Online Access: | http://hdl.handle.net/10356/72836 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Gender discrimination remains as a global pervasive problem despite the implementation of substantial national and international measures to promote gender equality. Today, we continue living in a socially segregated and misogynistic world, where females were often viewed to be inferior and weak relative to males. Females were constantly degraded, discriminated against, and were deprived of a levelled platform for growth and development. Such unfair practices could impact society adversely, be it in the form of lower talent retention rates, reduced productivity, weaker GDP growth or even a widening gender pay gap which demoralizes female workers, lowering their incentives to put their best foot forward when working. As such, given the associated alarming issues and detrimental drawbacks, addressing gender discrimination and their related issues must be made the top global priority as the economy progresses.
This paper seeked to first investigate the existence of a gender pay gap, and subsequently deduced the magnitude of the gap through the use of cross-sectional OLS regressions. It also aimed to examine if the gender gap was a result of gender discriminatory practices in the labor force or other self-dictated factors. Pooled OLS regressions were further conducted to examine if the gap varied over time or across firms. In addition, analysis was also conducted to investigate if acts of gender discrimination were present in the area of promotion, thereby resulting in differing rates of promotion across gender.
Firm-level data was utilized throughout the paper. Over a period of 3 months, 712 employees from 4 trading firms (3 local firms and 1 Asian MNC) engaging in Business-to-Business dealings, which have a strong presence in Singapore’s trading industry, were surveyed. Employees were involved in a one-time formal survey, and were constantly reassured on the confidentiality of the data collected. For each employee, their basic demographic data, employment-related information, compensation details and their personal views with regards to career progression were collected.
My regression models were built on past researchers’ models and upon conducting regression analysis, a gender pay gap of 4.75% was reported. This implied that males earned 4.75% more than females even after controlling for observable specific individual characteristics, firm-specific characteristics and productivity measures. The gender pay gap was observed to persist over 5 consecutive years, and comparing across 4 firms, the gap was most prevalent in the Asian MNC. This thus provided evidences for gender discriminatory practices in the labor force.
Gender discrimination could present itself in either the form of statistical discrimination or taste- based discrimination. However, given the limitations of my dataset, I am unable to conclude the
form of discrimination leading to the gender pay gap. This would be an interesting area for further research as the right forms of discrimination have to be first identified before policymakers are able to elicit the appropriate polices to eliminate gender discrimination, thereby narrowing the gender pay gap.
Surprisingly, results also revealed that males were promoted less frequently than females. However the results were not statistically significant when firm-specific factors and productivity measures were added into the regression model.
I also accounted for heteroskedasticity by clustering errors at individual level and my results stood strong even when robust standard errors were used. |
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