Can behavioral economics models help us measure stigma – and reduce it?

Stigma is often most evident in specific decision contexts, and these setting may be most amenable to intervention. Using quantitative, often experimental procedures, and stressing the shortcomings of conventional expected utility models, behavioral economics studies how people in various contexts construe and act in response to risk and uncertainty, resource allocation, cost/benefit judgments, and multiple trade-offs between values in conflict. Stigma research can benefit by adapting measures, methods, and models from this field, but only by critical attention to their limitations and presuppositions.

The presentation will review empirical applications by the author to issues such as disclosure, work discrimination, and housing. Potential advantages are discussed.. One is enhanced realism and ecological validity. Decisions concerning stigma are often contextually embedded and require assigning a comparative disutility (e.g. “how beneficial would an accommodation have to be to be worth the negative impact of stigma it may produce?”). Another is scientific, since general principles are used to explain stigma phenomena and experimental quantification of, say, the impact of stigma on wages can be compared with survey data on labor market outcomes. A third is policy relevance, since, increasingly, so-called ‘public choice' approaches apply market-influenced frameworks to policy choice.

Potential problems will also be noted, particularly concerning the risks posed by reliance on findings to promote market-based incentive programs to combat stigma. An empirically-motivated critique based in Relational Framing Theory and social psychology will highlight the probability of unintended adverse consequences of inappropriate applications to policy.