README
Data Underlying the Publication: “From Flux to Capital: Distinguishing Patterns of Income and Wealth Segregation in the Netherlands”

1. Introductory Information
Dataset title:
Data Underlying the Publication: From Flux to Capital: Distinguishing Patterns of Income and Wealth Segregation in the Netherlands

Authors:
Javier San Millán, Clémentine Cottineau‐Mugadza, Maarten van Ham
Department of Urbanism, Faculty of Architecture and the Built Environment, TU Delft, The Netherlands

Contact information:
Javier San Millán
Email: j.sanmillantejedor@tudelft.nl
Department of Urbanism, TU Delft
Julianalaan 134, 2628 BL Delft, The Netherlands

Related publication:
San Millán, J., Cottineau‐Mugadza, C., & van Ham, M. (2025). From Flux to Capital: Distinguishing Patterns of Income and Wealth Segregation in the Netherlands. Population, Space and Place, 31:e70127. https://doi.org/10.1002/psp.70127

License:
Creative Commons Attribution 4.0 International (CC BY 4.0)

Description of the dataset:
This dataset contains indicators of household-level income and wealth inequality and residential segregation in the Netherlands. It derives from restricted, geo-coded register microdata provided by Statistics Netherlands (CBS) and used in the analyses published in the referenced article.
It includes:
- Household-level measures of income and wealth inequality for 2022, adjusted per household member, distinguishing financial and real estate wealth.
- Residential segregation indices (Rank-Ordered Information Theory Index, ROITI, and its spatial extension SROITI) for income and wealth from 2011–2022 at multiple spatial scales (micro: 500 m; macro: 4000 m).
- Demographic indicators for 500 m × 500 m grid cells covering the entire Dutch territory (2022).
- Income and wealth percentiles (1–100) and thresholds per capita and per adult.
- Wealth distribution by asset type (real estate and financial) and by migration background of household head (born in the Netherlands / abroad).

Purpose of the dataset:
To provide reproducible and accessible summary indicators that allow researchers to explore patterns of income and wealth inequality and segregation in the Netherlands.

File naming conventions:
- Files beginning with 01_ were created inside the secure CBS Remote Access (RA) environment.
- Files beginning with 02_, 03_, and 04_ are reproducible R scripts run outside the CBS RA environment.
- CSV files correspond to aggregated or derived indicators exported from CBS for public sharing.

File List and Structure:
01_*.R – Scripts executed in the CBS Remote Access environment using full-population microdata.
02_main_analysis.R – Performs main analyses on exported datasets.
03_visualization.R – Reproduces figures and maps presented in the article.
04_Gini.R – Computes Gini coefficients for income, total wealth, financial wealth, and real estate wealth.
inequality_household_2022.csv – Income and wealth inequality indicators at household level.
segregation_indicators_2011_2022.csv – ROITI and SROITI indices for income and wealth, by year and functional urban area.
demographics_grid_500m_2022.csv – Demographic and socioeconomic data for CBS grid cells.
wealth_percentiles_2022.csv – Wealth and income percentile thresholds per capita and per adult.
wealth_distribution_detailed_2022.csv – Wealth distribution by type and migration background.

2. Methodological Information
Data source:
Statistics Netherlands (CBS) register microdata (2011–2022) accessed via CBS Remote Access.
CBS Open Data for grid-cell demographics (500 m × 500 m).

Methods for data generation and processing (see the published paper for references):
- Income and wealth are computed per household and adjusted per capita.
- Wealth is decomposed into financial (deposits, investments, shares) and real estate (property) components.
- Segregation indices are computed using the Rank-Ordered Information Theory Index (ROITI; Reardon & Bischoff 2011) and its spatial variants (Yao et al. 2019).
- Spatial units: 100 m × 100 m CBS grid cells aggregated to 500 m and 4000 m local environments using Gaussian kernel decay.
- Functional Urban Areas follow OECD–EU definition (Dijkstra et al. 2019).
- Gini coefficients computed using ineq R package.

Software used:
R version 4.3.2 with tidyverse, sf, seg, ineq, data.table, ggplot2.

Quality assurance:
CBS data is validated through cross-source verification with tax registers and land registry.
Derived data checked for consistency and confidentiality compliance.

3. Data Specific Information
Tabular data format: CSV (UTF-8).
Column names: descriptive headers.
Units: euros (€) per household member for income/wealth; segregation indices range 0–1.
Missing data: empty cells (NA).
Coordinate system: ETRS89 / UTM zone 31N (EPSG:25831).

4. Sharing and Access Information
License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
Restrictions: Raw CBS microdata not publicly available; only derived data provided.

Recommended citation:
San Millán, J., Cottineau‐Mugadza, C., & Van Ham, M. (2025). From Flux to Capital: Distinguishing Patterns of Income and Wealth Segregation in the Netherlands. Population, Space and Place, 31(8), e70127.
San Millán, J. (2025). Data Underlying the Publication: From Flux to Capital: Distinguishing Patterns of Income and Wealth Segregation in the Netherlands. TU Delft. DOI: 10.4121/2cdc29ea-eac0-4859-b878-7b6b870b3197

Keywords:
Income inequality; Wealth inequality; Residential segregation; Economic geography; Spatial data; The Netherlands; CBS microdata; Functional Urban Areas.
