The US federal government spent about $9.5 billion on employee compensation for work not performed during 2025, as the Donald Trump administration pursued an aggressive effort to reduce the size of the federal workforce, according to a new Government Accountability Office (GAO) assessment.
The figure reflects a sharp increase in the use of paid administrative leave following initiatives associated with the Department of Government Efficiency (DOGE), which was established as part of the administration’s drive to reduce government spending and staffing. According to the GAO assessment, spending on paid administrative leave rose by 435% between 2023 and 2025, reaching levels more than six times those recorded in 2023.
A significant portion of the expenditure was linked to the Deferred Resignation Program (DRP), a federal initiative introduced in January 2025 to encourage government employees to leave their positions. Under the programme, employees who accepted the offer could resign while continuing to receive their salaries and benefits for a period extending through September 30, 2025.
The programme was part of the administration’s broader effort to reduce the federal workforce. The government had initially projected that around 200,000 employees would accept the offer. However, the GAO estimated that 144,312 employees ultimately opted for the deferred resignation arrangement, according to data cited in reports on the assessment. About $6.7 billion of the $9.5 billion in administrative leave costs was associated with employees who participated in the programme.
The use of administrative leave reached its highest point in July 2025. During that month, federal agencies reported around three million leave workdays, of which approximately 2.5 million were attributed to employees participating in the Deferred Resignation Program.
The findings come as the Trump administration has continued to defend its efforts to reduce the federal workforce, arguing that the initial costs of the restructuring would eventually be outweighed by savings from having fewer employees on government payrolls.
Scott Kupor, director of the Office of Personnel Management, disputed the way the GAO figures were being interpreted. He argued that the $9.5 billion represented a one-time cost associated with reducing the size of the federal government and said the workforce reduction would generate approximately $40 billion in annual savings. He said the GAO assessment did not adequately account for the longer-term financial benefits claimed by the administration.
The federal workforce declined substantially during 2025. Federal data cited by ABC News showed that the number of federal workers fell by roughly 216,000 during the year, while nearly 140,000 employees accepted the buyout offer. The administration has continued to characterize the reductions as part of a broader attempt to make government operations more efficient and reduce taxpayer costs.
At the same time, the workforce reductions have generated additional costs and operational challenges. Some federal agencies have subsequently moved to bring back employees or contractors for certain roles, while other departments have continued restructuring and relocating personnel outside Washington.
The administration has also claimed that DOGE initiatives have produced hundreds of billions of dollars in savings. However, independent assessments and outside analysts have questioned the scale of those savings and the methods used to calculate them. The latest GAO findings add to the debate over whether the costs associated with reducing the federal workforce should be considered separately from the potential long-term savings.
The $9.5 billion figure therefore represents a significant expense incurred during the administration’s 2025 workforce restructuring. While officials have described the spending as an upfront cost intended to achieve longer-term reductions in government expenditure, the GAO assessment highlights the substantial amount paid in administrative leave as agencies implemented the workforce changes.
