> 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-population-forecast-and-economic-development-indicators.md). # US Population Forecast & Economic Development Indicators The US Population Forecast & Economic Development Indicators datasets combine demographic projection with economic measurement at ZIP code level across the United States. It covers historical population from 2010 to the present and forward projections through 2035, broken out by age and gender, with upper and lower bounds published alongside every projection. Alongside the demographic view, the dataset carries the economic indicators that help explain why populations move. These include business establishment counts and their growth, labor force participation, employment and unemployment, and county economic output growth measured overall and across the sectors most closely tied to local development, among them real estate, construction and retail trade. Results are available for individual ZIP codes, with a full monthly history retained so that movement can be traced over time. For researchers, analysts and decision-makers, it offers a single dependable basis for anticipating where demand is forming and understanding the economic conditions driving it. --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://knowledge.aterio.io/data-products/us-population-forecast-and-economic-development-indicators.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.