We examine employer preferences for hiring men vs women using 160,000 job ads posted on an online job portal in India, linked with more than 6 million applications. We apply machine learning algorithms on text contained in job ads to predict an employer's gender preference. We find that...

We study the demand for skills by using text analysis methods on job descriptions in a large volume of ads posted on an online Indian job portal. We make use of domain-specific unlabeled data to obtain word vector representations (i.e., word embeddings) and discuss how these can be leveraged for...

We examine how overall delivery of public goods (i.e., efficiency) is affected by affirmative action in elections, i.e., restricting candidate entry in elections to one population group. We argue that when group identities are salient, such restrictions on candidate entry need not necessarily...