Abstract
Private wealth, as well as its distribution and intergenerational transmission have become much-debated issues. However, existing evidence remains fragmented, context-dependent, and sometimes contested. This data descriptor introduces the Graduate Center (GC) Wealth Project data warehouse, a collection of databases covering multiple countries and time periods, designed to address these challenges. The data warehouse consolidates most existing evidence on private wealth and undertakes a significant data harmonization effort. We supplement each data point with extensive metadata on methodology. The data warehouse features an extensive collection of information on the household wealth levels and balance sheets, along with distributional statistics from a wide range of sources. Moreover, it draws together data on wealth transfer tax revenues, and tax features such as rates, exemption thresholds, and tax schedules. The broad range of data sources in the warehouse allows users to assess the degree of heterogeneity of estimates, and how methodological choices affect measurement outcomes. The new data series and policy indicators also allow extending quantitative analysis of wealth and public policy.
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Data availability
The data warehouse is available on Zenodo (https://doi.org/10.5281/zenodo.18601154) in comma-separated csv format (file name: warehouse_meta_v1_2_SciDatar1.csv) as well as dta format (file name: warehouse_meta_v1_2_SciDatar1.dta). To review all original raw data sources, users are advised to consult the supplementary source tables (Table S1, S2 and S3). These tables are also available on the Zenodo repository (file names: Supplementary Table S1.xlsx, Supplementary Table S2.xlsx, and Supplementary Table S3.xlsx). We cannot provide the microdata from the HFCS and the LWS. The HFCS data is collected by the European Central Bank (ECB) and provided to researchers through scientific user files by the ECB. The data from the Luxembourg Wealth Study is made available to researchers through the LISSY remote execution system of the Luxembourg Income Study Cross-National Data Center. We construct aggregated secondary data from the existing micro data sets that were legally obtained from the data providers. The secondary data sets are made available with the other source data sets.
Code availability
The replication codes are located in the “Code” subfolder of the Github repository. The main repository features detailed guidance on running the replication code and additional necessary files. This includes the tables that are required to obtain the data provided in the data warehouse from raw data sources (source-specific conceptual grids, conversion tables for historical currencies). Download links for the original source data sets that are used as inputs for the replication code are also provided.
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Acknowledgements
The project underwent approximately five years of development before its launch, in July 2023, and many individuals contributed to varying degrees, during multiple stages, and to different sections of the project. First, the project would not exist without the continuous, reliable, and professional support of the Stone Center, including its director Janet Gornick, and the staff, Carolyn Fisher, Mei-Ling Israel, Jennifer Kitses, Veronica Ordaz, and Saraya McPherson. We also acknowledge the support from the Law Department of the University of Roma Tre, including the director Antonio Carratta, as well as the admin staff Giuseppina Santilli, Alessia Cantarella, Riccardo D’Alfonso, Alessio Fiorentini, Federico Melograno, and Michele Sancioni. The professional organizational and communication support from Ylenia Sina is also acknowledged. Facundo Alvaredo, Charlotte Bartels, Yonatan Berman, Miles Corak, Philipp Erfurth, Josep Espasa Reig, Giacomo Gabbuti, Janet Gornick, Demetrio Guzzardi, Elena Granaglia, Joe Hasell, Roberto Iacono, Rama Dasi Mariani, Leslie McCall, Branko Milanovic, Teresa Munzi, Jörg Neugschwender, Brian Nolan, Juan Palomino, Piotr Paradowski, Alberto Pozzolo, Marco Ranaldi, Antonio Scialà, and Philippe Van Kerm provided invaluable feedback at different stages of development of the project. Regarding the Wealth Topography database, Goncalo Costa conceptualized the database and initiated the data-gathering effort. We thank Ana Rojas Silvero for providing essential support in collecting and systematizing raw data sources on household balance sheets. Our thanks also go to Marco Ranaldi, Yaoqi Lin, and Pranabes Probeshika Dutta for their support with the initial data gathering. For the Wealth Inequality Trends section, Ercio Muñoz carried out the foundational work by gathering the initial dataset. We are indebted to Tony Shorrocks for sharing Credit Suisse data. Early contributions from Carolyn Fisher and Ian Haberman were important in completing and optimizing the structure of the methodological tables, as well as providing details for specific sources. Thanks also to Philipp Erfurth for his valuable feedback during the early stages of the process. Irene Toma, joined the project in 2025 leading the data and conceptual expansion in the context of low and lower-middle income countries. Mei Li, Nolan Lyons, Yue Pan, Alex Parton, Sarah Russo, Jack Shea, and Tsu Zhu contributed to the EIG Taxes section trough outstanding research assistance. Martino Kuntze, Ali Jehanzaib, and Ghulam Shabir, did excellent work in supporting the systematization of data in relevant sources and debugging of the EIG taxes database. Josemaria Loria, Margherita Di Chiacchio, and Samuele Guerrini made further valuable contributions to the EIG Taxes section as research assistants. This work was financially supported by the Stone Center on Socio-Economic Inequality at The Graduate Center, City University of New York (CUNY).Salvatore Morelli acknowledges financial support from the grant PRIN2022 (Prot. 2022HLKRTJ) - “Wealth, income, and consumption inequality after COVID-19 - CUPF53D23003070001.
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All authors contributed equally to the article and the dataset. The author ordering is random using the American Economic Association’s Author Randomization tool. The register entry confirmation code is RstOC1m7lbWE. Salvatore Morelli, the GC Wealth Project Director, coordinates the large team between New York and Rome and guides and oversees the development, expansion, and refinement of the data warehouse as well as the associated research projects. The development of methodological tables to supplement the inequality trends series was carried out by Salvatore Morelli, with the support of others as detailed below. Giacomo Rella led the development of the Wealth Topography database, and worked on the conceptualization, the design of the data architecture, the national accounting mapping, the automation of data gathering, and the design of the detailed metadata complementing the database. Max Longmuir followed Giacomo Rella in the development of the Wealth Topography database and worked on the conceptualization, the design of the data architecture, the national accounting mapping, the automation of data gathering, and the design of the detailed metadata complementing the database. Severin Rapp is now leading the Topography section and overseeing the future expansion of the section. Frincasco Di Biase carried out the foundational work by gathering the initial dataset for the Wealth Inequality Trends section. He also assisted in the development of methodological tables to supplement the inequality trends series. Franziska Disslbacher oversaw the development of the Wealth Inequality Trends database in 2022 and part of 2023, and contributed to the establishment of automation processes. She contributed to the creation of the estimates of the wealth inequality trends series using cross-national survey databases. She also assisted in the development of methodological tables to supplement the inequality trends series, and worked on the completion and optimization the structure of the methodological tables. Moreover, she provided details for specific sources. Matteo Targa took over Franziska’s role in 2023 and developed a quality management routine for the Wealth Inequality Trends database. He contributed to the creation of the estimates of wealth inequality trends series using cross-national survey databases. Matteo is responsible for the management, update, expansion, and streamlining process of the inequality trends section. He also assisted in the development of methodological tables to supplement the Inequality Trends section. Adam Rego Johnson had a pivotal role in establishing compilation standards and manuals for the Wealth Inequality Trends database. He also contributed significantly through editing, proofreading, and classifying the methodological tables. Adam played an important role in the reference management and the creation of the Digital Library of Research on Wealth Inequality and the Data Sources Library. Twisha Asher collected and classified tax policy specifications and researched a wealth of data on wealth transfer taxation and shaped the Estate, Inheritance, and Gift (EIG) Taxes section fundamentally. She also played a decisive role in supporting the design and documentation of the EIG database structure. Moreover, she continued to streamline the data collection and improve the code that assembles the database in collaboration with others. Twisha Asher also supervised research assistants working on wealth transfer taxation. She helped with completing and optimizing the structure of the methodological tables in the Wealth Inequality Trends database, and provided details for specific sources. Ignacio Flores had a crucial role in supervising the overall architecture of the data warehouse. His oversight was vital for the integration of different elements of the data warehouse, such that the data is cohesively and logically structured. He also helped to improve the code that assembles the EIG Taxes database, and streamlined the data collection in collaboration with others. Ignacio Flores also contributed to the creation of the estimates of wealth inequality trends series using cross-national survey databases. Ignacio has been further contributing to the project with the design of a new website visualization architecture. Manuel Schechtl made important contributions to the the EIG Taxes section, assuming oversight of the EIG database from December 2022 through July 2024. Manuel Schechtl contributed to improving the code that assembles the database and streamlining the data collection, and supervised research assistants working on wealth transfer taxation. Francesca Subioli started to work with Manuel on the supervision and the development of the tax section (early 2023), which she is leading together with Luca since 2024. She improved the coding structure, implemented a completely new and more efficient architecture of the EIG section, and laid the groundwork for the future database expansion. She also supervised research assistants working on wealth transfer taxation. Luca Giangregorio started to work with Manuel and Francesca in late 2023 on the supervision and the development of the tax section. Both Luca and Francesca carried out substantial improvements in the the coding structure of the EIG tax section, implemented a completely new and more efficient architecture of the database, and laid the groundwork for the future database expansion. e also supervised research assistants working on wealth transfer taxation.
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Longmuir, M., Disslbacher, F., Rapp, S. et al. Wealth Composition, Distribution, and Transmission: The Graduate Center Wealth Project Data Warehouse. Sci Data (2026). https://doi.org/10.1038/s41597-026-07105-6
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DOI: https://doi.org/10.1038/s41597-026-07105-6
