RAND Budget Model

Budget decisions made in Washington have a profound impact on lives across America. They shape our communities, drive our economy, and define who we are as a nation.

The RAND von Furstenberg Family Budget Model Initiative is helping policymakers and the public understand how much can change with every line in the budget. We’re not just examining the costs of federal policy decisions. We’re showing in unprecedented detail how those decisions will impact real people, real businesses, and real communities.

• How the United States can realistically reduce its debt and avoid trillions of dollars in interest payments.
• What changes to the tax code would mean for corporate balance sheets and family budgets.
• How federal legislation will affect people’s lives city by city, household by household.

This level of analysis has never been done before. What sets our effort apart is the breadth of our scope, the transparency of our approach, and the strength of RAND’s commitment to objectivity. Our approach provides new ways to understand federal spending and tax policy, using artificial intelligence and machine learning in an open way. It builds on our long history of modeling some of the most complex and consequential policy problems we face.

The United States collects and spends trillions of dollars in taxes every year. The tools we have built so far include:

• A tax code analysis tool that maps the entire U.S. tax code to identify the effects of any changes on individuals, businesses, and federal revenue.
• A spending analysis tool that shows where federal dollars go, contract by contract, and how policy proposals would affect individual communities.
• Forecasting tools that highlight not just the costs of proposed legislation, but also any areas of uncertainty and risk.

We intend to make these models open-source and broadly available. We continue to expand our capabilities—to provide greater and more meaningful insights, to benefit the American public, and to reframe debates around the most pressing policy issues.