On the Risks of Belonging to Disadvantaged Groups: A Bayesian Analysis of Labour Market Outcomes

Although methods of analysis based on Bayes’ theorem have had rich applications in Law and in Medicine they have not been much used in Economics. We use Bayes’ theorem to construct two concepts of the “risk” associated with belonging to a particular group in terms of a favourable labour market outcome; this, in the Indian context, is taken as being in “regular employment”. The first concept, the Employment Risk Ratio, measures the odds of a person being in regular employment to being in non-regular employment, given that he belongs to a particular group. The second, the Group Risk Ratio, measures the odds of a person being in regular employment, given that he belongs to one group against belonging to another group. We then apply these concepts of risk to data for four subgroups in India: forward-caste Hindus; Hindus from the Other Backward Classes; Dalits (collectively the Scheduled Castes and Scheduled Tribes); and Muslims. We show that, on both measures of risk, forward caste Hindus do best in the Indian labour market. This is partly due to their superior labour market attributes and partly due to their better access to good jobs. When inter-group differences in attributes are neutralised, the favourable labour market performance of forward caste Hindus is considerably reduced. We conclude that it is the lack of attributes necessary for, rather than lack of access to, regular employment that holds back India’s deprived groups.