Statistical and Taste-Based Discrimination in Labor Market: An Analysis of European Countries to Identify Optimal Policy Interventions.

Giovanni Busetta , University of Messina
Irma Baraku, University of Shkodra “Luigi Gurakuqi”

This study examines statistical and taste-based discrimination in European labor markets and identifies effective policy interventions. Statistical discrimination uses stereotypical assumptions to predict individual productivity based on available information when complete data is unavailable. Taste-based discrimination arises from personal biases, leading to employer, employee, and customer discrimination. The effectiveness of anti-discrimination policies hinges on the nature of discrimination, whether it is statistical or taste-based. Strategies designed to mitigate statistical discrimination often revolve around reducing perceived productivity disparities between different groups. In contrast, taste-based discrimination requires a different approach, including the establishment of legal regulations, promoting equal opportunities, and implementing diversity training programs to challenge and mitigate biases in the workplace. To evaluate the depth and variations of discrimination, a discrimination index is applied to data from a harmonized field experiment across five European countries, compared with the Italian labor market. The findings underscore the substantial impact of taste-based discrimination, which frequently accounts for a significant portion of overall discrimination, sometimes reaching up to 90%. The study also assesses affirmative action measures such as quotas and hiring subsidies and their potential impact on mitigating discrimination. Prioritizing subsidies over quotas, basing subsidy levels on evidence of hiring discrimination, and involving specialized employment intermediaries can effectively address potential resentment and promote equitable hiring practices. This research offers valuable insights into the issue of discrimination in labor markets and proposes practical policy interventions to address both statistical and taste-based discrimination, thereby contributing to the creation of more inclusive and equitable labor markets.

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 Presented in Session P3. Migration, Economics, Policies, History