Systems Modeling and Policy Implications of Reducing the Workforce of the US Federal Government

Workforce reductions, such as those implemented by the Department of Government Efficiency, can have far-reaching effects that extend beyond immediate job losses. This study employs a systems-based modeling approach, combining traditional Input-Output (IO) analysis with the inoperability Input-Output Model (IIM), to investigate how staffing cuts impact economic activity and erode institutional functions across interconnected sectors. The study reveals that reductions in federal staff have a significant impact on industries that rely heavily on government contracts and infrastructure, including aerospace, transportation, and high-tech services. These disruptions create ripple effects throughout supply networks and regional economies, resulting in delays, cancellations, and reduced operational capacity. Notably, the extent and pattern of losses identified here align with findings from independent reports, which highlight hidden costs such as declines in productivity, contract terminations, and maintenance backlogs that often offset the expected savings from workforce reductions. Unlike models that only focus on output, the IIM framework captures functional degradation, providing a more accurate breakdown of impacts on various economic sectors. These findings underscore the limitations of cost-cutting measures that overlook systemic interdependencies, highlighting the need for policies that strike a balance between fiscal objectives and institutional resilience. An adaptive, risk-aware approach to workforce planning can help maintain essential services while managing organizational change.