This paper surveys the literature on theories of discrimination, focusing mainly on new contributions. Recent theories expand on the traditional taste-based and statistical discrimination frameworks by considering specific features of learning and signaling environments, often using novel information- and mechanism-design language
analyzing learning and decision making by algorithms
and introducing agents with behavioral biases and misspecified beliefs. This survey also attempts to narrow the gap between the economic perspective on ``theories of discrimination'' and the broader study of discrimination in the social science literature. In that respect, I first contribute by identifying a class of models of discriminatory institutions, made up of theories of discriminatory social norms and discriminatory institutional design. Second, I discuss issues relating to the measurement of discrimination, and the classification of discrimination as bias or statistical, direct or systemic, and accurate or inaccurate.