To help the Congress understand the nation’s long-term fiscal challenges, CBO produces projections of the economy and federal budget that extend beyond its standard 10-year projection window. The Congressional Budget Office Long-Term model—known as CBOLT—is the main analytical tool that the agency uses to make those projections.
CBOLT was created in the early 2000s to produce long-term projections of Social Security’s finances, and CBO has continually expanded the model’s capabilities and uses since then. Today, CBOLT is used to make long-term projections of the federal budget and economy; the size and composition of the population; the distribution of Social Security benefits and taxes among various groups; the effects of proposed changes to the Social Security system; and the effects of uncertainty about economic, budgetary, and demographic factors. Those projections and others underlie several recurring CBO products, including The Long-Term Budget Outlook, Long-Term Projections for Social Security: Additional Information, Social Security Policy Options, and selected options from Options for Reducing the Deficit.
CBOLT is complex, and this report will not cover all of its aspects in detail. For example, it will not explain how marital status, labor force participation, earnings, the claiming of Social Security auxiliary benefits, or spending for major federal health care programs are projected. Instead, it will focus on several key topics:
- CBOLT’s four components—the demographic model, the microsimulation model, the long-term budget model, and the policy growth model—and how they relate to one another;
- The data used in CBOLT;
- How CBOLT’s demographic model is used to make projections of the population;
- How CBOLT’s microsimulation model works, including how it is used to project demographic characteristics and to estimate the claiming of Social Security benefits;
- How CBOLT is used to produce long-term projections of the overall federal budget; and
- How CBOLT is used to project long-term economic outcomes.