  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.
