Empirical methods for studying diversity and (in)equality

All IDES faculty employ cutting-edge tools – from new online experimental methods to improved surveying and sampling techniques – but the group also develops basic scientific tools, applied to the study of inequality. Peter Christensen (Economics) designs large-scale field-based experiments to assess the magnitude of racial discrimination in US housing markets. Avital Livny (Political Science) leverages machine learning to identify systematic measurement error in existing estimates of ethnic and religious diversity worldwide, suggesting improvements in how demographers and other social scientists should measure ethnic and religious identity. Lena Song (Economics) develops new tools for recruiting representative survey samples through social media platforms.