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Records on 112 million U.S. residential properties
What is Cotality?
Cotality is the new name for CoreLogic, one of the largest real estate and property data providers in the United States. The company maintains parcel level records on more than 112 million U.S. residential properties, sourced and standardized from county assessor offices, recorder offices, and a network of public and proprietary inputs. The data has been a backbone of academic real estate finance and housing research for decades under the CoreLogic name.
What academic researchers should know about Cotality real estate data
On Dewey, Cotality's residential property data covers more than 112 million parcels across the United States, with each record carrying geospatial coordinates, structural characteristics like square footage and year built, ownership history, tax assessments, and the transaction record from purchase and sale events. Coverage flows from county assessor and recorder offices, which means the observation level is the parcel and updates reflect each jurisdiction's filing cadence. The transaction history is what most distinguishes the file: arms length sales, foreclosures, and refinances are linked back to specific properties so researchers can trace pricing and ownership changes over multiple cycles. The structural and locational fields support spatial joins to ZIP code, census tract, and block group geographies for studies that need to bridge property data with demographics, climate exposure, or local economic conditions.
Why academic researchers choose Cotality on Dewey
Cotality has been a standard real estate data source in published academic work for years under its previous name, CoreLogic, particularly in housing finance, urban economics, and the macroeconomics of household debt. The combination of nationwide parcel coverage, deep transaction history, and structural attributes in one file is rare, and it is the reason CoreLogic data shows up in major papers on the housing crisis, mortgage modification, and house price dynamics. Pairing Cotality with ClimateCheck for climate risk ratings, RentHub for rental listings, BrightQuery for firm financials, or SafeGraph for neighborhood foot traffic gives researchers a way to study residential property markets in the context of climate exposure, rental dynamics, employer activity, and neighborhood change.
Cotality academic research ideas and use cases
Housing markets and price dynamics. Cotality's nationwide parcel coverage and transaction history make the data well suited to studying house price dynamics across cycles, regional markets, and individual properties. Atif Mian and Amir Sufi's American Economic Review work on housing and household leverage during the Great Recession drew on CoreLogic transaction and house price data to trace how housing wealth shocks propagated through household consumption and employment.
Mortgage credit and household finance. The mortgage and refinance fields in Cotality's transaction history support research on mortgage origination, default, modification, and refinancing behavior. Peter Ganong and Pascal Noel's American Economic Review paper on liquidity and wealth during the Great Recession used CoreLogic loan level mortgage data to study how mortgage modifications affected default and consumption. Adelino, Schoar, and Severino's Review of Financial Studies work on mortgage origination and defaults during the crisis similarly drew on CoreLogic mortgage records to study which borrowers fueled the boom.
Climate risk and property exposure. With geospatial coordinates on every parcel, researchers can join Cotality data to flood zones, wildfire perimeters, sea level projections, or climate hazard ratings from providers like ClimateCheck. This combination is useful for research on insurance availability and pricing, post disaster property values, and how climate risk capitalizes (or fails to capitalize) into home prices.
Real estate finance and asset pricing. Transaction prices, structural attributes, and ownership history underpin a large literature on residential real estate as an asset class, supporting hedonic price models, repeat sales indices, and studies of price dispersion across markets. The completeness and longitudinal depth of Cotality data is especially useful for designs that require following the same property through multiple sales over decades.
Spatial analysis and urban form. Cotality's geospatial coordinates and structural attributes make the data a building block for spatial analysis, GIS work, and urban form research. Researchers can study density, land use mix, the spatial distribution of housing types, and the geography of construction, demolitions, and tear downs across decades.
Dive deeper with Dewey documentation
Detailed information on onboarding with Dewey, data partner details, and technical documentation on data access.
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