Statistical or taste-based Discrimination at the gates of admission to Senior High in Germany – Evidence from the field

With regard to the study design, we sent an application via email to all high schools with aliases as prospective graduates of the 10th grade - randomized with and without a migration background, female or male and with a high vs. low GPA (2x2x2 interventions).

2024-01-07

2024-02-18

The primary outcome variable is responsiveness of the addressed high schools. Responsiveness is measured as follows. If we observe a non-automated response to our treatment email, we mark it as “1”. If we do not observe a non-automated response, we mark it as “0”.

(i) We expect that the overall responsiveness towards inquirers without immigrant backgrounds is higher compared to high school's responsiveness towards inquirers with immigrant backgrounds.
(ii) We expect that high schools within districts that have a higher share of immigrants answer more frequently to inquirers with an immigrant background than schools in districts that have a low share of immigrants.
(iii) We expect that schools are more responsive to male compared to female inquirers.
(iv) We expect that schools are more responsive to inquirers with high GPA compared to inquirers with low GPA.

(i) There is evidence that German elites rather respond to inquiries made by people without immigrant background compared to inquiries made by people with immigrant background.
(ii) We expect this outcome due to pre-tests in the state of North Rhine-Westfalia.
(iii) This expectations are based the observation from pre-tests in the state of North Rhine-Westfalia. It can also be explained by gender studies.
(iv) This outcome can be driven by rational choice: High-GPA students are preferred by admission offices over low-GPA students.

Apart from responsiveness we are interested in the tonality and the text length of the written answers to the students. We expect that the tonality also varies across the treatment dimensions. This will be an additional variable we will use once we have a sufficient number of observations. In addition, we are interested in categorizing the answers between helpful answers, rejections and other categories that exemplify good, bad or even ugly answer types.
(i) We expect that migrant inquires receive non-helpful answers more often compared to non-migration inquires. .
(ii) We expect that that migrant inquires receive neutral or even negative answers more often compared to non-migrant inquires.
(iii) We expect that non-migrant inquirers receive shorter answers compared to migrant inquires because respondents are spending more time to write non-helpful or negative answers compared to positive answers.

All effects are based on rational behavior or cognitive dissonances :
(i) The respondent shows discrimination not by neglect but by choosing a lower effort level.
(ii) The respondent shows discrimination not by neglect but by choosing a lower effort level quality.
(iii) We believe that humans who are intentionally discriminate are aware of this action and justify their behavior by writing longer answers.

This experiment aims to find effects of taste-based discrimination within German High School System in the responsiveness towards students with immigrant background and without immigrant background with either very good or intermediate grades.
Therefore, we designed an experiment with three binary dimensions on side of the inquirers who ask High School Admission offices about information on how to apply for High School.

We take all High Schools of the 16 states in the Federal Republic of Germany into account. The first of the three treatment dimensions of the inquirers is a potential immigrant background. The inquirer’s name signals, from a German point of view, an immigrant background or not The second dimension is the gender of the inquirer. Again, the name signals out female or male gender. The third dimension varies the quality of the educational background of the inquirer. This is either high with a GPA for 1,3 or low with a GPA of 3,0.
Each school is contacted via email by one of the eight profiles which consist of all convex combinations of the three dimensions. We will then observe whether a High School responds to the request and if, how much time was required.

Randomization is done in office by a computer.

State level

Yes

Between 14-16 clusters with respect to randomization unit (state level). 8 clusters with respect to treatment clusters (three binary dimensions) within randomization unit.

between 1600 and 10000 which will be the number of High Schools in the 1-16 States of the Federal Republic of Germany.

dependends on the above available total sample size