ABSTRACT Favouritism 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.

中文翻译：

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印度制造业在社会经济劳动力属性方面的区域间职业差异

摘要偏爱和歧视减少了劳动力多样化，同时推动了不平等的增长。这些做法的发生增加了某些人无论其个人能力如何获得就业的可能性，从而导致非包容性增长。在印度，某些部门的就业取决于个人的个人，家庭，社会，文化和人口特征。这项研究试图分析个人的社会经济属性如何影响他们在特定部门或某种工作中的就业能力，特别关注印度制造业。该研究利用了印度政府年度就业和失业调查（EUS）第四轮（2013-14）和第五轮（2015-16）的单位水平数据。进行了逻辑回归分析，以分析制造业的就业可能性。我们发现，在确定个人在印度制造业中获得就业的可能性时，地理位置和种姓比教育和性别更重要。该模型的总体结果表明，所有选择的自变量对制造业中获得工作的可能性都有重大影响。