Negative racial stereotypes routinely work together with myths about American equality to undermine public support for policies that would reduce inequality. But what happens when white Americans are confronted with information about structural racial inequality, which contradicts the myth of equal opportunity? Evidence from an original survey experiment conducted among approximately 4,000 white Americans demonstrates that emphasizing the systemic origins of racial inequalities in the COVID-19 pandemic makes respondents more accepting of policies aimed at reducing racial inequalities in a variety of domains. Qualitative insights from post-treatment reflections further show that facing the reality of structural inequality disrupts blame-based narratives and generates support for policies meant to confront inequality. The findings suggest that discussing structural inequality can disrupt individualistic understandings and increase approval for policies that promote equality across multiple domains; they also illuminate why opponents of equality see discussions of structural inequality as so threatening.

This paper introduces a new estimation technique for discretely observed diffusion processes. Transform functions are applied to transform the data to obtain good and easily calculated estimators of both the drift and diffusion coefficients. Consistency and asymptotic normality of the resulting estimators is investigated. Power transforms are used to estimate the parameters of affine diffusions, for which explicit estimators are obtained.