Economists are increasingly using experiments to study and measure discrimination between groups. In a meta-analysis containing 441 results from 77 studies, we find groups significantly discriminate against each other in roughly a third of cases. Discrimination varies depending upon the type of group identity being studied: it is stronger when identity is artificially induced in the laboratory than when the subject pool is divided by ethnicity or nationality, and higher still when participants are split into socially or geographically distinct groups. In gender discrimination experiments, there is significant favouritism towards the opposite gender. There is evidence for both taste-based and statistical discrimination; tastes drive the general pattern of discrimination against out-groups, but statistical beliefs are found to affect discrimination in specific instances. Relative to all other decision-making contexts, discrimination is much stronger when participants are asked to allocate payoffs between passive in-group and out-group members. Students and non-students appear to discriminate equally. We discuss possible interpretations and implications of our findings.This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change; to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.

We run a meta-analysis on the body of studies investigating discrimination in lab and lab-in-the-field experiments.For inclusion, an experiment must involve interaction between individuals whose decisions determine real material payoffs for participating players. In other words, it must be incentivised. For more information, see the publication under Related Resources.