Event

About the Seminar:
Prof. Mahajan examines employer preferences for hiring men vs. women using newly collected data on approximately 160,000 job ads posted on an online job portal in India, linked with 6.45 million applications. She applies machine learning algorithms on text contained in job ads to construct measures that indicate whether the job ad text is predictive of an employer's explicit gender preference. She finds that advertised wages are lowest in jobs where employers prefer women, even when the job text only contains implicit markers of female preference, and that these jobs also attract a larger share of female applicants. She then systematically uncovers what lies beneath these relationships by retrieving words that are predictive of an explicit gender preference, or gendered words, and assigning them to the categories of hard and soft skills, personality traits, and exibility. She finds that skills related female-gendered words have low returns but attract a higher share of female applicants while male-gendered words indicating decreased flexibility (e.g., frequent travel or unusual working hours) have high returns but result in a smaller share of female applicants. This contributes to a gender earnings gap. Her findings highlight how non-wage elements in job text are associated with search behavior in the labor market.

About the Speaker:
Kanika Mahajan is an Assistant Professor of Economics at Ashoka University, Sonepat, India. Her primary research interests include empirical development economics in the field of gender, labor, and agriculture. As part of her research agenda on gender and labor, she is currently working on issues around stagnation of women's labor force participation in urban India and decline in female employment in rural areas—exploring both the supply side and the demand side linkages. Her other projects in the area of gender examine links between economic shocks and women's employment, gender and sanitation, and violence against women. In the context of COVID-19, her research examines resilience of supply chains in agriculture and manufacturing sectors in India.