JOURNAL ARTICLE

Understanding the Relationship Between Changes to Federal Fiscal Policy and Near‐Term Real GDP Growth.

  • Published In: Public Budgeting & Finance, 2025, v. 45, n. 1. P. 57 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Nelson, Jaeger; Wilson, Matthew 3 of 3

Abstract

We introduce two measures which highlight the relationship between changes in federal fiscal policy and economic growth. First, we conduct a growth decomposition exercise to compute the short‐run direct effects of changes in policy on real GDP growth, which we call the Federal Fiscal Impulse (FFI). Second, we build on this measure to develop the Federal Fiscal Impulse Index (FFII) which interprets changes in the components of fiscal policy relative to the growth rate of real GDP over recent history. Finally, we project these measures through 2026 using CBO's June 2024 baseline and discuss the measures' benefits and limitations. Summary: We introduce two measures which describe the relationship between changes in federal fiscal policy and economic growth: Federal Fiscal Impulse (FFI) and the Federal Fiscal Impulse Index (FFII).Changes in federal fiscal policies represented unusually large portions of GDP growth in recent years, driven primarily by transfers to individuals and grants to state and local governments.In CBO's most recent projections, FFI and FFII return to their historical levels from 2024 to 2026.While these measures are informative about the relationship between economic growth and the role of federal fiscal policy over time, they are not designed to reflect the comprehensive economic effects of any particular change in fiscal policy. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Public Budgeting & Finance. 2025/03, Vol. 45, Issue 1, p57
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0275-1100
  • DOI:10.1111/pbaf.12391
  • Accession Number:183857855
  • Copyright Statement:Copyright of Public Budgeting & Finance is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.