Muslim and Black people experience significantly more often that they are not invited to view apartments due to discrimination. Muslim and Black people are 35% and 39% likely to report such experiences. For people who are not racially labeled, the probability is only 11%.

The field experiment also shows evidence of this pattern: for fictitious applicants with German-sounding names, the probability of being invited is 22%, while for formally identical applications with names from the MENAT region it is only 16%.

People with racist markings live on average in much smaller living space: they have an average of 47 m² and 1.3 rooms per person. In contrast, people who are not racially marked live on average on 69 m² and in 1.9 rooms per person.

People marked as racist are more likely to live in insecure rental situations than people not marked as racist. These include fixed-term contracts (12 % versus 3 %), index-linked rents (21 % versus 17 %) and graduated rents (13 % versus 9 %), which increase the risk of rising costs and low planning security.

The probability that people in Germany are overburdened by their housing costs, i.e. spend 40% or more of their income on housing costs, is at least 30% overall. This probability is 30% for people who are not racially marked and 37% for people who are racially marked. This also increases the risk of housing poverty: 36% of racially marked tenants are at risk of poverty after deducting their housing costs, while 19% of people who are not racially marked are at risk.

Overall, the probability of tenants living in apartments with defects is around 50%. For tenants marked as racist, the probability is 57%, while it is 48% for tenants not marked as racist.

A detailed look at the individual types of defects reveals clear differences between the groups of origin. 27% of Muslim respondents report inadequate insulation against the cold (vs. 11% of people not marked as racist). 20% of Muslim respondents, 19% of Black respondents and 14% of Asian respondents reported mold infestation, whereas only 5% of non-racially marked respondents reported this.

To examine the environmental impact, the respondents' residential location data was linked with other data. This showed that racially marked people are more frequently exposed to higher environmental pollution, for example in the form of higher nitrogen dioxide levels in their living environment.

Black and Muslim people are significantly less likely to live in property. Only 11% and 24% of respondents respectively own the property they live in. This applies to 57% of respondents who are not racially marked. However, home ownership is an important factor for wealth accumulation and social security in Germany.

The majority of people in Germany feel safe in their neighborhood. All respondents are more than 81% likely to feel safe in their own neighborhood during the day. This figure is highest among people who are not racially labeled at 90%, and lowest among Muslims at 82% and Asians at 81%.

There is a clear difference between the genders: regardless of their group affiliation, women are on average around ten percentage points less likely than men to feel safe in their living environment at night.

The probability of experiencing discrimination in the neighborhood is 23% among black respondents. Muslim people are also affected more frequently than average: The likelihood of being treated worse than others in their neighborhood - for example by being ignored, spoken to unkindly or insulted - is 18%. Among people who are not racially labeled, the figure is only 6%.

Overall, racialized groups are less satisfied with their housing situation. This is particularly evident among Muslim people: They are only 68% likely to be satisfied with their housing situation, compared to 80% of those not racially marked. People who rent more often, have higher housing costs and have comparatively less living space available have a lower level of housing satisfaction.

People who are dissatisfied with their housing situation are also around 20 percentage points more likely - across all analyzed groups - to suffer from moderate to severe psychological stress symptoms than satisfied residents (32% of those who are not satisfied vs. 11% of those who are fully satisfied).

The NaDiRa.panel works with self-identification. Respondents can identify themselves as Black, Asian, Muslim or Eastern European - sometimes summarized in the report as "racially marked". Multiple answers are possible.

In individual evaluations, a binary indicator was used instead of the individual group identities: This distinguishes respondents into those who are not racially marked and those who are racially marked, with the latter including Black, Muslim, Asian and Eastern European respondents. This classification is used if there are otherwise insufficient case numbers for statistical comparisons.

Predictive margins or average marginal effects (AMEs) - estimated probabilities - based on logistic regression analyses are predominantly used to present the results. In contrast to simple descriptive proportions, this makes it possible to compare groups under the same conditions. Regression analyses are particularly suitable for revealing systematic differences that are not attributable to demographic or socio-economic structural effects.

Black people (36 %) and Muslims (30 %) are more likely to be refused a property because of their group affiliation - this is significantly less likely for people who are not racially marked (5 %).

The probability of receiving a response to a housing application is highest for people with German-sounding names:

• 55 % German-sounding names
• 48 % MENAT
• 49 % African names (excluding North Africa)

There are also differences in invitations to viewings:

• 22 % German-sounding names
• 16 % MENAT
• 17 % African names (excluding North Africa)

• Strengthen protection against discrimination: Reform the AGG, enable class actions, extend deadlines.
• Expand social and non-profit housing: strengthen property-related funding.
• Regulate precarious tenancies: Limit index and graduated rents, rent caps.
• Facilitate property acquisition: targeted funding programs and first-time buyer support.
• Anchoring environmental justice: planned heat prevention, especially in cities, better access to green spaces.

• Design funding programs to be sensitive to discrimination: mandatory anti-discrimination clauses, evaluation.
• Strengthen supervision and transparency: review procurement practices, anonymized procedures, mandatory training.
• Expand advice centers: multilingual, barrier-free, long-term funding.

• Establish monitoring and testing: systematic control of procurement practices.
• Make neighborhood development critical of racism: Integrate anti-discrimination and mediation structures.
• Ensure environmental justice: create green spaces, unsealing,
• Making procurement more transparent: standardized and anonymized procedures.

• Standardize allocation processes: transparent criteria, anonymized applications.
• Raise awareness: mandatory training for landlords and administrations.
• Improve building quality: targeted refurbishment without displacement.
• Transparency obligations: regular publication of central rental data.

• Expand advice: nationwide, low-threshold and multilingual structures.
• Strengthen networking: collective complaints platforms, exchange between NGOs and the housing sector.
• Public relations and monitoring: make discrimination visible and document it.