Abstract
Subcounty housing unit counts are important for studying geo-historical patterns of (sub)urbanization, land-use change, and residential loss and gain. The most commonly used subcounty geographical unit for social research in the United States is the census tract. However, the changing geometries and historically incomplete coverage of tracts present significant obstacles for longitudinal analysis that existing datasets do not sufficiently address. Overcoming these barriers, we provide housing unit estimates in consistent 2010 tract boundaries for every census year from 1940 to 2010 plus 2019 for the entire continental US. Moreover, we develop an “urbanization year” indicator that denotes if and when tracts became “urbanized” during this timeframe. We produce these data by blending existing interpolation techniques with a novel procedure we call “maximum reabsorption.” Conducting out-of-sample validation, we find that our hybrid approach generally produces more reliable estimates than existing alternatives. The final dataset, Historical Housing Unit and Urbanization Database 2010 (HHUUD10), has myriad potential uses for research involving housing, population, and land-use change, as well as (sub)urbanization.
Highlights
Background & SummarySocial and environmental researchers have long aimed to improve how they analyze and understand changes to the built environment
In the United States, investigators frequently rely on multi-decadal, small-area housing unit data from the US Census Bureau to estimate the historical pace and extent ofurbanization, analyze past geographies of housing loss and gain, categorizeurban land types, examine urban morphology, and project future patterns of population growth, development, and land use[1–8]
Our dataset fills a distinct niche left by existing data products—notably, HISDAC-US, National Historical Geographic Information System (NHGIS), and Longitudinal Tract Database (LTDB)— that attempt to estimate historic subcounty housing units
Summary
Background & SummarySocial and environmental researchers have long aimed to improve how they analyze and understand changes to the built environment. In the United States, investigators frequently rely on multi-decadal, small-area housing unit data from the US Census Bureau to estimate the historical pace and extent of (sub)urbanization, analyze past geographies of housing loss and gain, categorize (sub)urban land types, examine urban morphology, and project future patterns of population growth, development, and land use[1–8]. Such efforts, have long been hindered by problems with historical data availability and compatibility. Though rasters offer some noteworthy advantages, vector-polygons—namely, census tracts—are much more frequently used in social and demographic research
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