Statistical discrimination theory explains wage differences between demographic groups by referring to differences in group averages or heuristic-based decision-making. This study investigates whether providing employers with accurate information about individual productivity affects wage-setting practices. We replicate a labor market scenario in which employers determine wages based on perceived productivity differences between male and female workers. Our experimental findings suggest that statistical discrimination influences initial wage decisions, but access to individual performance data reduces reliance on group-based heuristics. The dominant strategy when the actual information about performance is to share the resources according to contribution. We observe that in tasks where women statistically outperform, higher-scoring individuals tend to receive slightly less than their proportional contribution, whereas in tasks where men perform better, they tend to receive slightly more than their contribution. Furthermore, we show that with only statistical information, significant gender-based wage discrimination aligned with performance stereotypes occurs, but there is no gender discrimination under full information about performance. Our results contribute to the broader discussion on labour market inequalities and approaches to reducing statistical discrimination.
