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This article was checked for accuracy as of September 19, 2024. Learn more about our commitments to accuracy and your mortgage education in our editorial guidelines.
Updated: September 19, 2024
Texas is emerging as a hotspot for Generation Z home buyers.
225,420 Gen Z members became home buyers in 2022, representing 4.85% of all home buyers nationwide. This Homebuyer.com housing market study highlights the areas where Gen Z buyers are concentrating and purchasing homes.
The study, “The Favorite ZIP Codes for Gen Z Home Buyers,” uses data from the FFEIC and the Home Mortgage Disclosure Act (HMDA) to identify and rank U.S. ZIP codes where Gen Z buyers purchased homes in 2022.
For this study, we define “Generation Z” as individuals born after 1999.
Our analysis focuses on identifying the top 10 ZIP codes that attract the most Gen Z home buyers. Additionally, we provide an overview of the ZIP codes ranked 11 through 50 to offer a broader perspective on Gen Z preferences. The study also includes insights into mortgage financing, with local down payment averages and purchase prices.
Scroll to the bottom for our complete methodology, where we outline our research process.
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We gathered data from the FFEIC website, specifically the Snapshot National Loan Level Dataset for 2022. These Snapshot files contain national HMDA datasets filed by U.S. mortgage lenders as of April 30, 2023. The data is modified to protect applicant and borrower privacy. The study focuses on home buyers of 1-4 unit residential properties in the 50 states and the District of Columbia. It does not include home buyers of second homes or investment properties. Home buyers with one-time construction loans and other open-ended mortgages in first-lien positions, such as a home equity line of credit (HELOC), are also excluded.
We examined data for home buyers between 18 and 24 in 2022. For each U.S. census tract, we calculated metrics, including the number of buyers, the average loan amount, and the average property value. Then, we mapped the census tracts to their corresponding ZIP codes.
Our analysis used complex database queries that combined data from the Loan Application Register and U.S. Census Bureau. These queries efficiently sifted through large datasets exceeding 30 GB to extract the necessary information.
We removed outlier data, primarily from mortgage applications that were either withdrawn by applicants or denied due to incompleteness, if they fell outside typical and expected ranges. Less than one-half of one percent of HMDA data was excluded due to outlier removal.
To ensure accuracy, we relied on the reliability of the HMDA data and the precision of our database queries. The data extraction, filtering, and analysis process ensured the robustness of our results.
Homebuyer conducted this research to help home buyers make informed housing decisions. If you found our research helpful, please share this article with proper attribution.
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For follow-up information and usage rights for our research, please email our team at hello@homebuyer.com.
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