Abstract
ABSTRACTFavouritism and discrimination reduce labour force diversification while driving unequal growth. The incidence of these practices increases the probability of securing employment for some people irrespective of their individual capabilities, leading to non-inclusive growth. In India, employment in certain sectors is determined by the personal, familial, social, cultural, and demographic traits of individuals. This study attempts to analyse how the socio-economic attributes of individuals affect their employability in a particular sector or kind of work, with a special focus on the Indian manufacturing sector. The study utilises unit-level data from the fourth (2013–14) and fifth (2015–16) rounds of the annual Employment and Unemployment Surveys (EUS) by the Government of India. Logistic regression analysis was undertaken to analyse employment probabilities in the manufacturing sector. We found that location and caste are more important than education and gender in determining an individual’s probability of gaining employment in the Indian manufacturing sector. The overall results from the model show that all the selected independent variables have a significant impact on the probability of getting jobs in the manufacturing sector.
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