> For the complete documentation index, see [llms.txt](https://knowledge.aterio.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://knowledge.aterio.io/data-products/us-housing-forecast.md). # US Housing Forecast Aterio's Housing Dataset serves as an extensive repository not only furnishing current housing data but also offering crucial insights into future housing requirements, particularly for 2030, informed by population growth patterns. Emphasizing the differentiation between owner-occupied and renter-occupied residences, alongside an evaluation of vacancy rates, it additionally encompasses rental vacancy rates, facilitating a thorough examination of rental market dynamics. This dataset aids researchers, analysts, and decision-makers, serving as an indispensable resource for making informed decisions within the dynamic real estate and housing sectors. Meticulously curated through the amalgamation of data from the U.S. Census Bureau, research by Columbia University and NASA, Department of Housing and Urban Development records, County Clerk Applications, and refined through the application of machine learning algorithms for prediction, this dataset proves invaluable to stakeholders seeking to analyze and proactively anticipate shifts in housing demand and supply trends. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://knowledge.aterio.io/data-products/us-housing-forecast.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.