Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/114016
Authors: 
Nordman, Christophe Jalil
Sarr, Leopold
Sharma, Smriti
Year of Publication: 
2015
Series/Report no.: 
IZA Discussion Papers 9132
Abstract: 
We use a first-hand linked employer-employee dataset representing the formal sector of Bangladesh to explain gender wage gaps by the inclusion of measures of cognitive skills and personality traits. Our results show that while cognitive skills are important in determining mean wages, personality traits have little explanatory power. However, quantile regressions indicate that personality traits do matter in certain parts of the conditional wage distribution, especially for wages of females. Cognitive skills as measured by reading and numeracy also confer different benefits across the wage distribution to females and males respectively. Quantile decompositions indicate that these skills and traits reduce the unexplained gender gap, mainly in the upper parts of the wage distribution. Finally, results suggest that employers place greater consideration on observables such as academic background and prior work experience, and may also make assumptions about the existence of sex-specific skills of their workers, which could then widen the within-firm gender wage gap.
Subjects: 
gender wage gap
cognitive skills
personality traits
matched worker-firm data
quantile decompositions
Bangladesh
JEL: 
J16
J24
J31
J71
C21
O12
Document Type: 
Working Paper

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