The Global Living Arrangements Database, 1960-2021

Demographic research requires longitudinal data to understand how household compositions evolve over decades across various geographic regions. This database fills a significant gap in the availability of statistical information for examining patterns by age and sex. Prior research has shown that changes in marital status and educational attainment significantly influence domestic living patterns across diverse cultures and economic systems. Scholars have long struggled with the inconsistency of census data when attempting to compare family dynamics between different nations or time periods. These inconsistencies often stem from varying definitions of household membership or the lack of detailed relationship descriptors in historical records. The absence of a centralized repository has hindered the ability of sociologists to perform cross-national comparisons of kinship structures. This absence of evidence motivated the development of a comprehensive repository to harmonize disparate census microdata into a single, accessible framework.

This project establishes a standardized framework for analyzing domestic configurations across 107 distinct nations to improve global demographic understanding. The initiative seeks to bridge the informational void regarding how age and sex intersect with residential choices in both developing and developed economies. Investigators aimed to provide a scalable methodology for examining long-term transformations in family structures that have occurred since the mid-twentieth century. By creating a robust resource, the team intends to support evidence-based decision-making for social services, housing authorities, and healthcare sectors worldwide. The study focuses on the systematic categorization of living arrangements to reveal how education levels correlate with household size and composition. The researchers also sought to empower the scientific community by providing tools that facilitate the creation of custom ego-centered typologies. This goal ensures that the database remains relevant as social norms and family definitions continue to shift in the coming decades.

The team aggregated comprehensive census microdata sourced from Integrated Public Use Microdata Series (IPUMS) International and the European Labour Force Survey (EU-LFS) to build the foundation of the database. A specialized kinship reconstruction algorithm processed over 740 million individual records to identify complex relationships within households that were not explicitly labeled. This computational approach enables the systematic mapping of interfamily connections, such as multi-generational ties and non-traditional domestic units, which were previously obscured. The researchers utilized open-source R code to ensure the methodology remains reproducible and adaptable for future demographic inquiries by other scientists. Data processing involved harmonizing variables across different time periods and geographic regions to ensure longitudinal consistency and comparative accuracy. The algorithm specifically targets the reconstruction of kinship by analyzing the proximity and characteristics of individuals listed within the same dwelling units. This rigorous methodological framework allows for the transformation of raw census entries into a structured, relational database suitable for advanced statistical modeling.

The resulting Global Living Arrangements Database (GLAD) provides a massive repository covering six decades of demographic shifts across 107 countries. Analysis of the 740 million records reveals complex patterns in how individuals organize their domestic lives based on educational attainment and marital status. The database successfully captures kinship dynamics on a global scale, offering a truly international perspective on how household evolution differs between continents. Implementation of the reconstruction algorithm allowed for the identification of specific interfamily relationships within large-scale census datasets that were previously difficult to quantify. These results demonstrate a significant shift in living arrangements, reflecting broader societal changes in marriage rates and the duration of formal education. The availability of open-source code facilitates the generation of diverse typologies that reflect modern social complexities and varying cultural norms. Ultimately, the data provides a clear view of how residential patterns have transformed from 1960 through 2021, highlighting the increasing diversity of household types.

These findings offer a foundational tool for policymakers addressing essential needs in housing, social services, and public health infrastructure. The database serves as a vital instrument for understanding the socio-economic drivers behind changing family structures in diverse global contexts. Future studies can leverage this scalable methodology to explore emerging trends in social service requirements for aging populations or changing workforce dynamics. The integration of IPUMS International and EU-LFS data sets a new standard for global demographic data harmonization and accessibility. This resource will likely catalyze new research into the intersection of education, marital status, and residential stability across different political and economic regimes. By providing a transparent and open-source platform, the authors ensure that the global scientific community can continue to refine these models. The study concludes that such comprehensive data is essential for crafting effective social policies that reflect the actual living conditions of citizens worldwide.