Aterio logo

Population Projections for the US, 2025-2030

Sergio Toro

Chief Executive at aterio.io

Create a free account and get access to the full article

It takes 1 minute to sign up and get access to the best content on the block.

At Aterio, we focus on data-driven decision-making for real estate investments. We employ advanced methodologies to forecast population growth from 2025 and 2030 at a ZIP code level, offering invaluable insights for the real estate market investors. This blog explains our approach and explains why the applications of population forecasting are useful in the realms of investment, development, urban planning, and corporate strategy.

The Basics for Our Population Forecasts:

At Aterio, we apply data from diverse sources to include accurate and dependable population forecasts. Our methodology comprises the following core elements:

  • Historical Data: With official historical data, we identify past trends and patterns that shape our model from Census information.
  • Population Estimates: We use population estimates for 2025 and 2030 sourced from trustworthy entities such as NASA and Columbia University, which gives our forecasts a robust foundation.
  • Our Adjustments: Our added value resides on Aterio’s model that refines these estimates. This model takes additional data, which allows us to recognize indicators of economic development, analyze migratory patterns, and add precision to our forecasts.

Population Forecasts Strategic Advantage

For Investors

Investors can use population forecasts to find places with early growth potential. When the population goes up, there's usually more demand for homes, services, and conveniences. By investing in areas expected to have more people, investors can aim for higher profits.

For Developers

Finding the best places for real estate development is crucial for developers. Population forecasting helps them choose where to build homes, stores, and infrastructure. With these forecasts, developers can easily match their projects with expected high demand.

For Urban Planning Authorities

City planners and local governments can leverage population forecasts to inform licensing and zoning decisions. By understanding demographic trends, urban planning authorities can plan infrastructure projects and service provision for sustainable urban growth.

For Financial Institutions and Corporations

Financial institutions and corporate enterprises can employ population forecasts to sense the market demand for their offerings. A deep understanding of where populations are shifting enables precise market expansion strategies and resource allocation, fostering competitive business operations.

Some Data

According to our estimates, the range of population change differs extensively by state. While the US population is expected to grow 7.34% between 2020 and 2030, these are the states that present the most projected growth and the ones with the less growth (in some cases even decreasing their population)

Top 5 States (including DC) with the most population growth, 2020-2030:

  1. North Dakota ND: 23.29%
  2. District of Columbia DC: 20.38%
  3. Texas TX: 17.08%
  4. Utah UT: 15.85%
  5. Colorado CO: 15.42%

Bottom 5 States (including DC) with the least population growth, 2020-2030:

  1. Connecticut (CT): -0.08%
  2. Illinois (IL): -0.83%
  3. Maine (ME): -1.21%
  4. Vermont (VT): -2.17%
  5. West Virginia (WV): -2.46%

In Conclusion

Population forecasting to 2030 represents a powerful instrument for stakeholders spanning diverse industries. At our institution, we provide accurate ZIP code-level population forecasts by combining data sources and adjusting them with our model. Whether you're an investor, developer, urban planner, or corporation, our population forecasting helps you make better, more informed, data-driven decisions. Clickhere to view our forecasts.

Disclaimer: Our population forecasts are founded upon publicly available data and models, and must be employed as an information resource and not investment advise. Results may fluctuate contingent on unforeseen variables.