# Assessing the Effects of District-Level Segregation on Meritocratic Beliefs in Germany

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

#### 2.1. Perceiving Inequality: The Role of Locality

#### 2.2. Beliefs and Local Inequality: Three Competing Theories

- Newman et al. (2015) put forward and test the “activated class conflict hypothesis”. Based on the assumption that social classes hold latent attitudes relating to their relative position within social hierarchies, they argue that when inequality rises, citizens become aware of this relative position and adjust their beliefs accordingly. Newman et al. (2015) find that when inequality is high, low-income individuals are more likely to reject meritocratic beliefs, in contrast to higher incomes groups who are more likely to embrace these beliefs.
- Solt et al. (2016) do not only offer a methodological critique of Newman et al. (2015), but focus on the dimension of discourse. As social discourses are shaped through power relations, they propose that high inequality increases the ability of those in power to influence public discourse in a way that justifies the current system. In contrast to the findings of Newman et al. (2015), they find that low-income individuals are more likely to hold meritocratic beliefs when inequality is high. Their findings were recently, in part, corroborated by Morris et al. (2022).
- Mijs (2018) offers a somewhat different theoretical approach. He proposes that individuals who encounter people from a diverse range of social backgrounds and social positions will become more critical of meritocratic principles than those whose social relations are more homogeneous. The more diverse the relationships of individuals are, the more likely they are to experience (by proxy) different facets of success and failure, leading them to call meritocratic principles into question (Mijs 2018, 2019). He argues that as inequality rises, so does segregation between social groups, making citizens less likely to meet those from different social backgrounds. More recent work supports these findings (García-Castro et al. 2020).

#### 2.3. A Note on the Underlying Mechanisms

#### 2.4. Segregation and Meritocratic Beliefs in Germany

**Hypothesis**

**1.**

**Hypothesis**

**2.**

**Hypothesis**

**3.**

**Hypothesis**

**4.**

## 3. Data and Method

#### 3.1. Data

#### 3.2. Dependent Variable

#### 3.3. Independent Variables

#### 3.3.1. District-Level Segregation

#### 3.3.2. District-Level Controls

#### 3.3.3. Individual-Level Controls

#### 3.4. Method and Models

## 4. Results

#### 4.1. District-Level Segregation and Meritocratic Beliefs: An Urban Phenomenon?

#### 4.2. Probing the Results: MAUP and Spatial Units

## 5. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## Appendix A

Variable | Coding | Description |
---|---|---|

Meritocratic beliefs | 0–100 | “One has to work hard in order to succeed”, agree at all) to 7 (completely agree), rescaled [SOEP data] |

Dissimilarity index | 0–1 | microm status data, calculated following Duncan and Duncan (1955) [SOEP data] |

Isolation index | 0–1 | microm status data, calculated following Bell (1954) for both high and low status [SOEP data] |

Avg. monthly income per inhabitant (EUR) | district-level household income [INKAR data] | |

Population density | district-level total population divided by 10,000 [INKAR data] | |

Foreign population | individuals without German citizenship of total population in % [INKAR data] | |

Proportion of basic benefits recipients (SGBII) | 0 = below1 = above | individuals without German citizenship of total population in %, dummy coded on 3rd quartile [INKAR data] |

Proportion of high-income households | 0 = below1 = above | Proportion of household with net income above EUR 3600 per month of total population in %, dummy coded on 3rd quartile [INKAR data] |

Equivalized monthly household income (EUR 000) | OECD equivalized monthly income divided by 1000 [SOEP data] | |

Duration of residence (years) | own calculation [SOEP data] | |

Region | 0 = West1 = East | NUTS region (East–West Version), recoded [SOEP data] |

District type | 0 = urban1 = rural | spatial category by BBSR [SOEP data] |

Moved in the past year | 0 = no1 = yes | own calculation [SOEP data] |

Gender | 0 = female1 = male | female = 1, male = 2, recoded [SOEP data] |

Migration background | 0 = none1 = first gen2 = second gen | migration background, no migration background = 1, first generation = 2, second generation = 3, recoded [SOEP data] |

Age group | 0 = under 651 = aged 65+ | Calculated based on year of birth, dummy coded [SOEP data] |

University educated | 0 = degree1 = no degree | CASMIN, recoded, 3a/3b Tertiary Education = 0 [SOEP data] |

Unemployed | 0 = no1 = yes | Labor force status, recoded, 1 = registered unemployed [SOEP data] |

Religion | 0 = no1 = yes | Religion, non-denominational = 0 [SOEP data] |

Political attitude | 0 = other1 = left-leaning2 = right-leaning | “If you think about your own political views: Where would you place yours?”, 0 (left) to 10 (right), recoded to left (0–4), right (6–10), other (5) [SOEP data, 2014] |

**Figure A2.**Isolation index (low status) by district type, 2015. Source: microm, GeoBasis-DE/BKG (2023).

**Figure A3.**Isolation index (high status) by district type, 2015. Source: microm, GeoBasis-DE/BKG (2023).

**Table A2.**Linear mixed-effect models of meritocratic beliefs in Germany (alternative specification of segregation).

“Dissimilarity Index” | “Isolation Index (Low Status)” | “Isolation Index (High Status)” | ||||
---|---|---|---|---|---|---|

(XI) | (XII) | (XIII) | (XIV) | (XV) | (XVI) | |

District level | ||||||

(Intercept) | 78.60 (0.95) *** | $80.41\phantom{\rule{0.277778em}{0ex}}\left(1.47\right)$ *** | $77.43\phantom{\rule{0.277778em}{0ex}}\left(0.74\right)$ *** | $77.40\phantom{\rule{0.277778em}{0ex}}\left(0.91\right)$ *** | $78.63\phantom{\rule{0.277778em}{0ex}}\left(0.70\right)$ *** | $78.52\phantom{\rule{0.277778em}{0ex}}\left(0.81\right)$ *** |

Index | $-1.79\phantom{\rule{0.277778em}{0ex}}\left(1.21\right)$ | $-4.87\phantom{\rule{0.277778em}{0ex}}\left(2.28\right)$ * | $0.19\phantom{\rule{0.277778em}{0ex}}\left(2.85\right)$ | $1.36\phantom{\rule{0.277778em}{0ex}}\left(4.68\right)$ | $-6.52\phantom{\rule{0.277778em}{0ex}}\left(2.13\right)$ ** | $-5.52\phantom{\rule{0.277778em}{0ex}}\left(3.62\right)$ |

Avg. monthly income (EUR 000) | $-0.29\phantom{\rule{0.277778em}{0ex}}\left(1.48\right)$ | $-0.08\phantom{\rule{0.277778em}{0ex}}\left(1.52\right)$ | $-0.61\phantom{\rule{0.277778em}{0ex}}\left(1.61\right)$ | $-0.72\phantom{\rule{0.277778em}{0ex}}\left(1.63\right)$ | $2.59\phantom{\rule{0.277778em}{0ex}}\left(1.80\right)$ | $2.43\phantom{\rule{0.277778em}{0ex}}\left(1.87\right)$ |

Population density | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ |

Foreign population | $-0.05\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.06\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.04\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.06\phantom{\rule{0.277778em}{0ex}}\left(0.08\right)$ | $-0.06\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.06\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ |

Basic security benefits (> 12.3%) | $1.21\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ * | $0.52\phantom{\rule{0.277778em}{0ex}}\left(1.60\right)$ | $1.22\phantom{\rule{0.277778em}{0ex}}\left(0.67\right)$ | $2.40\phantom{\rule{0.277778em}{0ex}}\left(1.43\right)$ | $1.57\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ ** | $1.67\phantom{\rule{0.277778em}{0ex}}\left(0.74\right)$ * |

High-income households (> 24%) | $-0.80\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $-1.30\phantom{\rule{0.277778em}{0ex}}\left(1.90\right)$ | $-0.94\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $-1.29\phantom{\rule{0.277778em}{0ex}}\left(0.92\right)$ | $-0.83\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $-0.57\phantom{\rule{0.277778em}{0ex}}\left(0.81\right)$ |

Region: East | $1.77\phantom{\rule{0.277778em}{0ex}}\left(0.66\right)$ ** | $1.89\phantom{\rule{0.277778em}{0ex}}\left(0.67\right)$ ** | $1.75\phantom{\rule{0.277778em}{0ex}}\left(0.67\right)$ ** | $1.41\phantom{\rule{0.277778em}{0ex}}\left(0.75\right)$ | $1.96\phantom{\rule{0.277778em}{0ex}}\left(0.66\right)$ ** | $1.88\phantom{\rule{0.277778em}{0ex}}\left(0.70\right)$ ** |

Rural Areas | $-0.89\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ | $-3.47\phantom{\rule{0.277778em}{0ex}}\left(1.45\right)$ * | $-0.84\phantom{\rule{0.277778em}{0ex}}\left(0.50\right)$ | $-1.18\phantom{\rule{0.277778em}{0ex}}\left(0.74\right)$ | $-1.05\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ * | $-1.07\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ |

Individual level | ||||||

Household income (EUR 000) | $0.00\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $-0.53\phantom{\rule{0.277778em}{0ex}}\left(0.44\right)$ | $0.01\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $0.19\phantom{\rule{0.277778em}{0ex}}\left(0.16\right)$ | $0.02\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $-0.22\phantom{\rule{0.277778em}{0ex}}\left(0.19\right)$ |

Moved in the past year | $-0.37\phantom{\rule{0.277778em}{0ex}}\left(1.09\right)$ | $-0.36\phantom{\rule{0.277778em}{0ex}}\left(1.09\right)$ | $-0.40\phantom{\rule{0.277778em}{0ex}}\left(1.11\right)$ | $-0.41\phantom{\rule{0.277778em}{0ex}}\left(1.11\right)$ | $-0.38\phantom{\rule{0.277778em}{0ex}}\left(1.11\right)$ | $-0.37\phantom{\rule{0.277778em}{0ex}}\left(1.11\right)$ |

Duration of residence (years) | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ |

Male | $0.84\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.84\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** |

First-generation migrant | $4.59\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.58\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.62\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.60\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.62\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.61\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** |

Second-generation migrant | $4.63\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.61\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.67\phantom{\rule{0.277778em}{0ex}}\left(0.59\right)$ *** | $4.65\phantom{\rule{0.277778em}{0ex}}\left(0.59\right)$ *** | $4.67\phantom{\rule{0.277778em}{0ex}}\left(0.59\right)$ *** | $4.66\phantom{\rule{0.277778em}{0ex}}\left(0.59\right)$ *** |

Aged 65+ | $2.21\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** | $2.20\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** | $2.22\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** | $2.21\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** | $2.23\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** | $2.20\phantom{\rule{0.277778em}{0ex}}\left(0.36\right)$ *** |

No university degree | $3.42\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.40\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.44\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.41\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.39\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.35\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** |

Unemployed | $0.98\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $0.96\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $0.87\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $0.83\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ |

Religious | $0.29\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.28\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.35\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.37\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.32\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.31\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ |

Left-leaning | $-2.40\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.40\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.48\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.48\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.46\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.45\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** |

Right-leaning | $0.79\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.80\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.75\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.75\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.76\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * |

Interaction terms | ||||||

Index × income | $0.79\phantom{\rule{0.277778em}{0ex}}\left(0.64\right)$ | $-1.14\phantom{\rule{0.277778em}{0ex}}\left(0.72\right)$ | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ | |||

Index × rural area | $4.61\phantom{\rule{0.277778em}{0ex}}\left(2.41\right)$ | $2.61\phantom{\rule{0.277778em}{0ex}}\left(4.17\right)$ | $-0.15\phantom{\rule{0.277778em}{0ex}}\left(4.10\right)$ | |||

Index × benefits | $1.40\phantom{\rule{0.277778em}{0ex}}\left(2.56\right)$ | $-4.86\phantom{\rule{0.277778em}{0ex}}\left(5.58\right)$ | $-0.83\phantom{\rule{0.277778em}{0ex}}\left(3.24\right)$ | |||

Index × high income | $0.99\phantom{\rule{0.277778em}{0ex}}\left(3.00\right)$ | $7.80\phantom{\rule{0.277778em}{0ex}}\left(8.81\right)$ | $-1.55\phantom{\rule{0.277778em}{0ex}}\left(3.77\right)$ | |||

Num. obs. | 21,263 | 21,263 | 21,059 | 21,059 | 21,059 | 21,059 |

Num. groups: hid:kkz_rek | 13,325 | 13,325 | 13,192 | 13,192 | 13,192 | 13,192 |

Num. groups: kkz_rek | 388 | 388 | 387 | 387 | 387 | 387 |

Var: hid:kkz_rek (Intercept) | $85.81$ | $85.84$ | $85.40$ | $85.39$ | $85.50$ | $85.55$ |

Var: kkz_rek (Intercept) | $4.30$ | $4.26$ | $4.43$ | $4.35$ | $4.18$ | $4.27$ |

Var: Residual | $267.45$ | $267.43$ | $267.44$ | $267.46$ | $267.32$ | $267.27$ |

## Notes

1 | District boundaries based on the jurisdictional boundaries present on 31 December 2017, provided by the time-series data by INKAR. |

2 | The Research Data Center of the Federal Statistical Office is currently examining the possibility of further re-use of the data. |

3 | While there certainly is a case to be made for the inclusion of additional facets playing into how individuals think about inequality—as is demonstrated by Mijs (2019), who includes a measure of structural beliefs—we opt to focus thoroughly on work-based meritocratic beliefs.As beliefs about work-based and structural factors of inequality are complementary (Mijs 2018), we believe the choice is justified. |

4 | While there is some debate regarding treating scale items as continuous (Schröder and Yitzhaki 2017), it is considered to be feasible when there are more than five categories, as is the case here (Frijters et al. 2004). |

5 |

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Theory | Main Assumption | Mechanism | Anticipated Results |
---|---|---|---|

“Conflict Theory” (Newman et al. 2015) | Individuals hold latent class attitudes that influence their meritocratic beliefs. They are activated when inequality increases. | As inequality increases, it becomes more salient, heightening class consciousness, leading lower-/upper-class individuals to be critical/supportive of inequality. | When inequality is high, meritocratic beliefs decrease among the poor and increase among the affluent. |

“Relative Power Theory” Solt et al. (2016) | Social discourses are influenced by power relations. When inequality increases, discourses change. | As inequality increases, so does the influence of those in power on public discourse, leading to an increase in meritocratic beliefs. | When inequality is high, meritocratic beliefs are high, especially among the poor. |

“Contact Theory” Mijs (2018) | Higher inequality leads to more segregation between social groups, limiting contact. Interactions within a heterogeneous social group foster skepticism toward meritocratic principles. | Rising inequality leads to increased segregation which in turn limits intergroup contact and increases meritocratic beliefs. | When groups are segregated, meritocratic beliefs increase. |

Authors | Country | Spatial Unit | Measure | Findings |
---|---|---|---|---|

Newman et al. (2015) | USA | Counties | Gini | Higher levels of inequality are associated with stronger meritocratic beliefs among the affluent and weaker meritocratic beliefs among the poor. |

Solt et al. (2016) | USA | Counties | Gini | High levels of inequality are associated with stronger meritocratic beliefs, but only for low-income individuals. |

Morris et al. (2022) | England | LSOAS | Gini 80:20 ratio | High levels of inequality are associated with stronger meritocratic beliefs, but only for low-income individuals |

Variable | N | Mean | Std. Dev. | Min | Median | Max |
---|---|---|---|---|---|---|

Meritocratic Beliefs | 21,395 | 81.76 | 19.17 | 0.00 | 83.33 | 100.00 |

District level | ||||||

Dissimilarity index | 21,395 | 0.94 | 0.044 | 0.71 | 0.95 | 1.00 |

Isolation index (poor) | 21,395 | 0.45 | 0.20 | 0.021 | 0.48 | 0.82 |

Isolation index (rich) | 21,395 | 0.35 | 0.22 | 0.027 | 0.32 | 0.88 |

Avg. disposable monthly income p.p. (000 €) | 21,395 | 1.73 | 0.21 | 1.27 | 1.72 | 2.99 |

Population density | 21,395 | 898.46 | 1138.72 | 36.27 | 304.01 | 4668.11 |

Foreign population | 21,395 | 10.10 | 5.67 | 1.90 | 9.02 | 33.60 |

Proportion of SGBII recipients | 21,395 | 9.19 | 4.85 | 1.09 | 8.40 | 23.79 |

Proportion of high-income households | 21,395 | 20.30 | 5.73 | 9.19 | 19.85 | 47.61 |

Region | 21,395 | |||||

West | 16,227 | 76% | ||||

East | 5168 | 24% | ||||

District type | 21,395 | |||||

urban | 13,754 | 64% | ||||

rural | 7641 | 36% | ||||

Individual level | ||||||

OECD equivalized household income (EUR 000) | 21,395 | 1.97 | 1.34 | 0.00094 | 1.71 | 69.41 |

Moved in the past year | 21,395 | |||||

did not move | 21,046 | 98% | ||||

moved | 349 | 2% | ||||

Duration of residence (years) | 21,395 | 13.06 | 12.74 | 1 | 6 | 100 |

Gender | 21,395 | |||||

female | 11,533 | 54% | ||||

male | 9862 | 46% | ||||

Migration background | 21,395 | |||||

none | 16,771 | 78% | ||||

first generation | 3431 | 16% | ||||

second generation | 1193 | 6% | ||||

Age group | 21,395 | |||||

aged under 64 | 16,494 | 77% | ||||

aged 65+ | 4901 | 23% | ||||

University educated | 21,395 | |||||

university degree | 5512 | 26% | ||||

no university degree | 15,883 | 74% | ||||

Unemployed | 21,395 | |||||

not unemployed | 20,399 | 95% | ||||

unemployed | 996 | 5% | ||||

Religion | 21,395 | |||||

not religious | 7198 | 34% | ||||

religious | 14,197 | 66% | ||||

Political attitude | 21,395 | |||||

other | 9473 | 44% | ||||

left-leaning | 7422 | 35% | ||||

right-leaning | 4500 | 21% |

“One Has to Work Hard in Order to Succeed” | ||||||
---|---|---|---|---|---|---|

“Dissimilarity Index” | “Isolation Index (Low Status)” | “Isolation Index (High Status)” | ||||

(I) | (II) | (III) | (IV) | (V) | (VI) | |

District level | ||||||

(Intercept) | 86.78 (4.84) *** | $101.61\phantom{\rule{0.277778em}{0ex}}\left(8.99\right)$ *** | $77.89\phantom{\rule{0.277778em}{0ex}}\left(0.86\right)$ *** | $78.98\phantom{\rule{0.277778em}{0ex}}\left(1.18\right)$ *** | $79.42\phantom{\rule{0.277778em}{0ex}}\left(0.80\right)$ *** | $79.20\phantom{\rule{0.277778em}{0ex}}\left(0.97\right)$ *** |

Index | $-9.97\phantom{\rule{0.277778em}{0ex}}\left(5.14\right)$ | $-25.49\phantom{\rule{0.277778em}{0ex}}\left(9.55\right)$ ** | $-0.99\phantom{\rule{0.277778em}{0ex}}\left(1.50\right)$ | $-3.27\phantom{\rule{0.277778em}{0ex}}\left(2.40\right)$ | $-5.36\phantom{\rule{0.277778em}{0ex}}\left(1.52\right)$ *** | $-4.37\phantom{\rule{0.277778em}{0ex}}\left(2.33\right)$ |

Avg. monthly income (EUR 000) | $-0.31\phantom{\rule{0.277778em}{0ex}}\left(1.47\right)$ | $0.48\phantom{\rule{0.277778em}{0ex}}\left(1.50\right)$ | $-1.11\phantom{\rule{0.277778em}{0ex}}\left(1.51\right)$ | $-1.40\phantom{\rule{0.277778em}{0ex}}\left(1.55\right)$ | $1.62\phantom{\rule{0.277778em}{0ex}}\left(1.59\right)$ | $1.79\phantom{\rule{0.277778em}{0ex}}\left(1.67\right)$ |

Population density | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ |

Foreign population | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.04\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(0.07\right)$ |

Basic security benefits (>12.3%) | $1.34\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ * | $4.29\phantom{\rule{0.277778em}{0ex}}\left(11.98\right)$ | $1.26\phantom{\rule{0.277778em}{0ex}}\left(0.59\right)$ * | $0.66\phantom{\rule{0.277778em}{0ex}}\left(2.45\right)$ | $1.57\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ ** | $2.01\phantom{\rule{0.277778em}{0ex}}\left(0.90\right)$ * |

High-income households (>24%) | $-0.73\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $7.23\phantom{\rule{0.277778em}{0ex}}\left(11.53\right)$ | $-0.97\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $-1.62\phantom{\rule{0.277778em}{0ex}}\left(1.16\right)$ | $-0.89\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ | $-0.07\phantom{\rule{0.277778em}{0ex}}\left(1.03\right)$ |

Region: East | $2.08\phantom{\rule{0.277778em}{0ex}}\left(0.68\right)$ ** | $2.03\phantom{\rule{0.277778em}{0ex}}\left(0.68\right)$ ** | $1.85\phantom{\rule{0.277778em}{0ex}}\left(0.68\right)$ ** | $1.52\phantom{\rule{0.277778em}{0ex}}\left(0.74\right)$ * | $1.83\phantom{\rule{0.277778em}{0ex}}\left(0.65\right)$ ** | $1.80\phantom{\rule{0.277778em}{0ex}}\left(0.69\right)$ ** |

Rural Areas | $-0.99\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ * | $-28.52\phantom{\rule{0.277778em}{0ex}}\left(9.42\right)$ ** | $-0.87\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ | $-2.21\phantom{\rule{0.277778em}{0ex}}\left(1.02\right)$ * | $-1.21\phantom{\rule{0.277778em}{0ex}}\left(0.49\right)$ * | $-1.44\phantom{\rule{0.277778em}{0ex}}\left(0.82\right)$ |

Individual level | ||||||

Household income (EUR 000) | $0.00\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $-3.75\phantom{\rule{0.277778em}{0ex}}\left(2.71\right)$ | $0.00\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $0.24\phantom{\rule{0.277778em}{0ex}}\left(0.23\right)$ | $0.01\phantom{\rule{0.277778em}{0ex}}\left(0.11\right)$ | $-0.29\phantom{\rule{0.277778em}{0ex}}\left(0.26\right)$ |

Moved in the past year | $-0.27\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ | $-0.23\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ | $-0.28\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ | $-0.30\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ | $-0.25\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ | $-0.23\phantom{\rule{0.277778em}{0ex}}\left(1.08\right)$ |

Duration of residence (years) | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.01\right)$ |

Male | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.86\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.86\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.85\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** | $0.86\phantom{\rule{0.277778em}{0ex}}\left(0.24\right)$ *** |

First generation migrant | $4.64\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.60\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.63\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.60\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.62\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** | $4.61\phantom{\rule{0.277778em}{0ex}}\left(0.40\right)$ *** |

Second generation migrant | $4.56\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.54\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.56\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.53\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.56\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** | $4.55\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ *** |

Aged 65+ | $2.21\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** | $2.20\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** | $2.21\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** | $2.20\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** | $2.21\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** | $2.19\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ *** |

No university degree | $3.42\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.38\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.44\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.41\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.38\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** | $3.35\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ *** |

Unemployed | $0.99\phantom{\rule{0.277778em}{0ex}}\left(0.62\right)$ | $0.96\phantom{\rule{0.277778em}{0ex}}\left(0.62\right)$ | $0.98\phantom{\rule{0.277778em}{0ex}}\left(0.62\right)$ | $0.92\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ | $1.00\phantom{\rule{0.277778em}{0ex}}\left(0.62\right)$ | $0.96\phantom{\rule{0.277778em}{0ex}}\left(0.63\right)$ |

Religious | $0.29\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.26\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.31\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.32\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.27\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ | $0.26\phantom{\rule{0.277778em}{0ex}}\left(0.32\right)$ |

Left-leaning | $-2.37\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.37\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.38\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.38\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.36\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** | $-2.36\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ *** |

Right-leaning | $0.76\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.79\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.77\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * | $0.78\phantom{\rule{0.277778em}{0ex}}\left(0.35\right)$ * |

Interaction terms | ||||||

Index × income | $3.92\phantom{\rule{0.277778em}{0ex}}\left(2.82\right)$ | $-0.60\phantom{\rule{0.277778em}{0ex}}\left(0.50\right)$ | $0.59\phantom{\rule{0.277778em}{0ex}}\left(0.46\right)$ | |||

Index × rural area | $29.64\phantom{\rule{0.277778em}{0ex}}\left(10.13\right)$ ** | $3.63\phantom{\rule{0.277778em}{0ex}}\left(2.40\right)$ | $0.76\phantom{\rule{0.277778em}{0ex}}\left(2.79\right)$ | |||

Index × benefits | $-3.05\phantom{\rule{0.277778em}{0ex}}\left(12.65\right)$ | $1.10\phantom{\rule{0.277778em}{0ex}}\left(4.22\right)$ | $-1.36\phantom{\rule{0.277778em}{0ex}}\left(2.25\right)$ | |||

Index × high income | $-8.57\phantom{\rule{0.277778em}{0ex}}\left(12.30\right)$ | $1.87\phantom{\rule{0.277778em}{0ex}}\left(3.03\right)$ | $-2.70\phantom{\rule{0.277778em}{0ex}}\left(2.80\right)$ | |||

Num. obs. | 21,395 | 21,395 | 21,395 | 21,395 | 21,395 | 21,395 |

Num. groups: hid:kkz_rek | 13,412 | 13,412 | 13,412 | 13,412 | 13,412 | 13,412 |

Num. groups: kkz_rek | 400 | 400 | 400 | 400 | 400 | 400 |

Var: hid:kkz_rek (Intercept) | $85.37$ | $85.42$ | $85.33$ | $85.40$ | $85.43$ | $85.49$ |

Var: kkz_rek (Intercept) | $4.17$ | $3.94$ | $4.28$ | $4.23$ | $3.94$ | $4.00$ |

Var: Residual | $267.93$ | $267.84$ | $267.96$ | $267.93$ | $267.85$ | $267.79$ |

“One Has to Work Hard in Order to Succeed” | ||||
---|---|---|---|---|

‘Rural’ | ‘Urban’ | |||

(VII) | (VIII) | (IX) | (X) | |

District level | ||||

(Intercept) | 73.25 (6.73) *** | $69.52\phantom{\rule{0.277778em}{0ex}}\left(7.84\right)$ *** | $103.10\phantom{\rule{0.277778em}{0ex}}\left(7.14\right)$ *** | $106.60\phantom{\rule{0.277778em}{0ex}}\left(9.54\right)$ *** |

Index | $1.73\phantom{\rule{0.277778em}{0ex}}\left(7.03\right)$ | $5.73\phantom{\rule{0.277778em}{0ex}}\left(8.30\right)$ | $-26.66\phantom{\rule{0.277778em}{0ex}}\left(7.57\right)$ *** | $-30.39\phantom{\rule{0.277778em}{0ex}}\left(10.13\right)$ ** |

Avg. monthly income (EUR 000) | $-1.31\phantom{\rule{0.277778em}{0ex}}\left(3.96\right)$ | $-0.86\phantom{\rule{0.277778em}{0ex}}\left(4.02\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(1.54\right)$ | $-0.27\phantom{\rule{0.277778em}{0ex}}\left(1.58\right)$ |

Population density | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.00\right)$ |

Foreign population | $-0.16\phantom{\rule{0.277778em}{0ex}}\left(0.18\right)$ | $-0.20\phantom{\rule{0.277778em}{0ex}}\left(0.18\right)$ | $-0.01\phantom{\rule{0.277778em}{0ex}}\left(0.08\right)$ | $-0.01\phantom{\rule{0.277778em}{0ex}}\left(0.08\right)$ |

Basic security benefits (>12.3 %) | $2.02\phantom{\rule{0.277778em}{0ex}}\left(0.94\right)$ * | $-3.56\phantom{\rule{0.277778em}{0ex}}\left(17.78\right)$ | $0.63\phantom{\rule{0.277778em}{0ex}}\left(0.70\right)$ | $-5.76\phantom{\rule{0.277778em}{0ex}}\left(18.87\right)$ |

High-income households (>24%) | $0.56\phantom{\rule{0.277778em}{0ex}}\left(1.10\right)$ | $28.79\phantom{\rule{0.277778em}{0ex}}\left(19.44\right)$ | $-1.42\phantom{\rule{0.277778em}{0ex}}\left(0.66\right)$ * | $-9.52\phantom{\rule{0.277778em}{0ex}}\left(14.35\right)$ |

Region: East | $1.00\phantom{\rule{0.277778em}{0ex}}\left(1.25\right)$ | $0.81\phantom{\rule{0.277778em}{0ex}}\left(1.27\right)$ | $1.40\phantom{\rule{0.277778em}{0ex}}\left(0.97\right)$ | $1.39\phantom{\rule{0.277778em}{0ex}}\left(0.98\right)$ |

Individual level | ||||

Household income (EUR 000) | $-0.36\phantom{\rule{0.277778em}{0ex}}\left(0.28\right)$ | $-5.50\phantom{\rule{0.277778em}{0ex}}\left(5.28\right)$ | $0.07\phantom{\rule{0.277778em}{0ex}}\left(0.12\right)$ | $-2.50\phantom{\rule{0.277778em}{0ex}}\left(3.69\right)$ |

Moved in the past year | $1.39\phantom{\rule{0.277778em}{0ex}}\left(1.84\right)$ | $1.37\phantom{\rule{0.277778em}{0ex}}\left(1.85\right)$ | $-1.08\phantom{\rule{0.277778em}{0ex}}\left(1.34\right)$ | $-1.07\phantom{\rule{0.277778em}{0ex}}\left(1.34\right)$ |

Duration of residence (years) | $-0.01\phantom{\rule{0.277778em}{0ex}}\left(0.02\right)$ | $-0.01\phantom{\rule{0.277778em}{0ex}}\left(0.02\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.02\right)$ | $-0.00\phantom{\rule{0.277778em}{0ex}}\left(0.02\right)$ |

Male | $0.82\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ * | $0.83\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ * | $0.88\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ ** | $0.88\phantom{\rule{0.277778em}{0ex}}\left(0.30\right)$ ** |

First-generation migrant | $4.13\phantom{\rule{0.277778em}{0ex}}\left(0.76\right)$ *** | $4.15\phantom{\rule{0.277778em}{0ex}}\left(0.76\right)$ *** | $4.80\phantom{\rule{0.277778em}{0ex}}\left(0.47\right)$ *** | $4.79\phantom{\rule{0.277778em}{0ex}}\left(0.47\right)$ *** |

Second-generation migrant | $3.97\phantom{\rule{0.277778em}{0ex}}\left(1.29\right)$ ** | $3.94\phantom{\rule{0.277778em}{0ex}}\left(1.29\right)$ ** | $4.74\phantom{\rule{0.277778em}{0ex}}\left(0.66\right)$ *** | $4.74\phantom{\rule{0.277778em}{0ex}}\left(0.66\right)$ *** |

Aged 65+ | $1.70\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ ** | $1.71\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ ** | $2.44\phantom{\rule{0.277778em}{0ex}}\left(0.46\right)$ *** | $2.43\phantom{\rule{0.277778em}{0ex}}\left(0.46\right)$ *** |

No university degree | $3.22\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ *** | $3.21\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ *** | $3.38\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ *** | $3.37\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ *** |

Unemployed | $-0.04\phantom{\rule{0.277778em}{0ex}}\left(1.02\right)$ | $-0.03\phantom{\rule{0.277778em}{0ex}}\left(1.02\right)$ | $1.46\phantom{\rule{0.277778em}{0ex}}\left(0.79\right)$ | $1.44\phantom{\rule{0.277778em}{0ex}}\left(0.79\right)$ |

Religious | $-0.08\phantom{\rule{0.277778em}{0ex}}\left(0.55\right)$ | $-0.09\phantom{\rule{0.277778em}{0ex}}\left(0.55\right)$ | $0.47\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ | $0.47\phantom{\rule{0.277778em}{0ex}}\left(0.39\right)$ |

Left-leaning | $-1.09\phantom{\rule{0.277778em}{0ex}}\left(0.50\right)$ * | $-1.10\phantom{\rule{0.277778em}{0ex}}\left(0.50\right)$ * | $-3.07\phantom{\rule{0.277778em}{0ex}}\left(0.38\right)$ *** | $-3.06\phantom{\rule{0.277778em}{0ex}}\left(0.38\right)$ *** |

Right-leaning | $0.56\phantom{\rule{0.277778em}{0ex}}\left(0.57\right)$ | $0.57\phantom{\rule{0.277778em}{0ex}}\left(0.58\right)$ | $0.87\phantom{\rule{0.277778em}{0ex}}\left(0.44\right)$ * | $0.88\phantom{\rule{0.277778em}{0ex}}\left(0.44\right)$ * |

Interaction terms | ||||

Index × income | $5.59\phantom{\rule{0.277778em}{0ex}}\left(5.72\right)$ | $2.65\phantom{\rule{0.277778em}{0ex}}\left(3.81\right)$ | ||

Index × benefits | $6.05\phantom{\rule{0.277778em}{0ex}}\left(19.12\right)$ | $6.65\phantom{\rule{0.277778em}{0ex}}\left(19.61\right)$ | ||

Index × high income | $-30.37\phantom{\rule{0.277778em}{0ex}}\left(20.87\right)$ | $8.62\phantom{\rule{0.277778em}{0ex}}\left(15.23\right)$ | ||

Num. obs. | 7641 | 7641 | 13,754 | 13754 |

Num. groups: hid:kkz_rek | 4724 | 4724 | 8688 | 8688 |

Num. groups: kkz_rek | 202 | 202 | 198 | 198 |

Var: hid:kkz_rek (Intercept) | $80.91$ | $80.84$ | $87.51$ | $87.57$ |

Var: kkz_rek (Intercept) | $5.34$ | $5.45$ | $2.63$ | $2.72$ |

Var: Residual | $260.17$ | $260.18$ | $272.22$ | $272.18$ |

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## Share and Cite

**MDPI and ACS Style**

Oetke, N.; Norkus, M.; Goebel, J.
Assessing the Effects of District-Level Segregation on Meritocratic Beliefs in Germany. *Soc. Sci.* **2023**, *12*, 376.
https://doi.org/10.3390/socsci12070376

**AMA Style**

Oetke N, Norkus M, Goebel J.
Assessing the Effects of District-Level Segregation on Meritocratic Beliefs in Germany. *Social Sciences*. 2023; 12(7):376.
https://doi.org/10.3390/socsci12070376

**Chicago/Turabian Style**

Oetke, Nicole, Maria Norkus, and Jan Goebel.
2023. "Assessing the Effects of District-Level Segregation on Meritocratic Beliefs in Germany" *Social Sciences* 12, no. 7: 376.
https://doi.org/10.3390/socsci12070376