Employment

India’s exceptional growth pattern after the 1980s is attributed to the robust growth of the service sector. The growth pattern of services is not homogeneous and uniform.

Increased dependence on agriculture and self-employment points to the growing deficit in decent work.

A new system of data collection on issues pertaining to labour and employment, called the Periodic Labour Force Survey, replacing the very comprehensive and detailed surveys on the employment and unemployment situation, also known as quinquennial surveys, was introduced in India in 2017. This paper is an attempt to highlight the effects of the modified sampling methods adopted in the PLFS on data outcomes and inconsistencies. Compared to the EUS survey, the determining criteria used in the PLFS for classifying households across various socio-economic strata seem to be irrational, less comprehensive, and technically incorrect. A fundamental change in the basis of sample selection introduced with the PLFS makes it incomparable to the earlier surveys.

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 are in favour of female workers, but they earned less than male workers in almost every occupation and employment status. The effect of education is stronger in selecting high-paying jobs.