Occupation, Earning, and Gender : An Analysis with the Labour Force Survey in India

This study analyses the employment distribution of the working-age women by occupations across their activities in usual principal status in the Periodic Labour Force Survey for 2017–18 by taking into account the household-specific factors and workers’ personal characteristics by using a multinomial logit model. The study infers that gender differences in returns to schooling

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China , United States , India , Hyderabad , Andhra Pradesh , Washington , Amsterdam , Noord Holland , Netherlands , American , Shi Li , Amiya Kumar Bagchi , Albert Yung Hsu Liu , David Card , Peter Brummund , Orleyc Ashenfelter , International Monetary Fund , National Sample Survey Office , International Monetary Fundworking Paper , National Classification Of Occupations , Periodic Labour Force Survey , Elsevier , National Sample , Gender Wage Gap , National Sample Survey , Scheduled Tribes , Scheduled Castes , National Classification , Labor Economics , Occupational Coding System , Activity Status , Political Weekly , Temporary Employment , India Evidence , Quantile Regression , Post Reform Scenario , Post Reform Developmentin Asia , Second Class Workers , Decomposition Analysis , Comparative Economics , Methodological Analysis , Segregation Indexes , American Sociological Review , Male Wage Differential , Where You , Human Resources , Gender Composition , Why Do Women , Jobs Pay , Labour Economics , Wage Distri , Using Quantile Regression , Applied Econometrics , Indian Urban Labour Market , Wage Inequality , Wage Discrimination , Religious Groups , India Estimates , Unit Level Data , Relative Wages , One Phenomenon , American Economic Review ,