Field experiments testing discrimination in the marketplace have been conducted for over 30 years, involving matched pairs of bogus transactors across 10 countries. These experiments have consistently found significant, persistent, and pervasive discrimination against non-whites and women in labor, housing, and product markets. Rates of employment discrimination against non-whites exceed 25% in Australia, Europe, and North America. Experiments have also investigated discrimination against the disabled in Britain and the Netherlands, and against older applicants in the United States.
The technique of controlled field experiments to measure discrimination in the marketplace was developed by British sociologists in the 1960s. Daniel (1968) tested racial discrimination in the English housing and labor market using matched pairs of actors, followed by Jowell and Prescott-Clarke (1970) introducing written tests. The technique gained recognition in economics journals in the 1980s, with studies by Firth (1981), Yinger (1986), and Riach and Rich (1987). Interest in field experiments increased in the 1990s, with publications in economics journals and by the International Labour Office (ILO) and the Urban Institute (UI). This has led to a substantial body of literature showing discrimination in labor, housing, and product markets based on sex and race, with some studies on age and disability.
Field experiments in the labor market use three procedures: personal approaches (in-person or telephone), written applications, and correspondence tests. Testers are matched to be identical in all relevant employment characteristics except for the characteristic being tested (e.g., race, sex, disability). They are trained to give equivalent backgrounds and use identical CVs. The order of approach is considered to avoid bias, with minority applicants often making the first approach. The results are recorded and analyzed to determine discrimination.
Critics argue that matching and motivation of testers can affect results, and that some studies may have biased outcomes due to testers' awareness of discrimination. The British developed procedures using professional actors to ensure realistic role-playing. The UI has criticized PEP for not forming visually comparable teams, but professional actors can control subjective aspects of human capital.
Written tests involve sending matched pairs of applications to test for discrimination at the initial selection stage. Letters are carefully matched to ensure only the characteristic being tested differs. The content of applications is controlled, and results are analyzed to determine discrimination.
Interpreting results requires careful analysis, considering all possible outcomes, including cases where both applicants are rejected. Different interpretations of 'neither invited' or 'neither offered' can affect the calculated incidence of discrimination. Statistical significance is tested using methods like chi-squared tests.
Studies have shown significant discrimination against non-whites and women in various occupations, with net discrimination rates often exceeding 25%. The ILO and UI studies found significant discrimination in the initial hiring stages, with minority applicants often facing rejection basedField experiments testing discrimination in the marketplace have been conducted for over 30 years, involving matched pairs of bogus transactors across 10 countries. These experiments have consistently found significant, persistent, and pervasive discrimination against non-whites and women in labor, housing, and product markets. Rates of employment discrimination against non-whites exceed 25% in Australia, Europe, and North America. Experiments have also investigated discrimination against the disabled in Britain and the Netherlands, and against older applicants in the United States.
The technique of controlled field experiments to measure discrimination in the marketplace was developed by British sociologists in the 1960s. Daniel (1968) tested racial discrimination in the English housing and labor market using matched pairs of actors, followed by Jowell and Prescott-Clarke (1970) introducing written tests. The technique gained recognition in economics journals in the 1980s, with studies by Firth (1981), Yinger (1986), and Riach and Rich (1987). Interest in field experiments increased in the 1990s, with publications in economics journals and by the International Labour Office (ILO) and the Urban Institute (UI). This has led to a substantial body of literature showing discrimination in labor, housing, and product markets based on sex and race, with some studies on age and disability.
Field experiments in the labor market use three procedures: personal approaches (in-person or telephone), written applications, and correspondence tests. Testers are matched to be identical in all relevant employment characteristics except for the characteristic being tested (e.g., race, sex, disability). They are trained to give equivalent backgrounds and use identical CVs. The order of approach is considered to avoid bias, with minority applicants often making the first approach. The results are recorded and analyzed to determine discrimination.
Critics argue that matching and motivation of testers can affect results, and that some studies may have biased outcomes due to testers' awareness of discrimination. The British developed procedures using professional actors to ensure realistic role-playing. The UI has criticized PEP for not forming visually comparable teams, but professional actors can control subjective aspects of human capital.
Written tests involve sending matched pairs of applications to test for discrimination at the initial selection stage. Letters are carefully matched to ensure only the characteristic being tested differs. The content of applications is controlled, and results are analyzed to determine discrimination.
Interpreting results requires careful analysis, considering all possible outcomes, including cases where both applicants are rejected. Different interpretations of 'neither invited' or 'neither offered' can affect the calculated incidence of discrimination. Statistical significance is tested using methods like chi-squared tests.
Studies have shown significant discrimination against non-whites and women in various occupations, with net discrimination rates often exceeding 25%. The ILO and UI studies found significant discrimination in the initial hiring stages, with minority applicants often facing rejection based