Maine

The Department of Government Efficiency (DOGE) is estimated to have terminated 180 federal contracts and grants in Maine, producing $599.8M in claimed savings - $440 per resident and 0.5% of all DOGE cuts nationally. On these numbers, Maine ranks #44 by total estimated savings and #19 per capita, giving readers a concrete sense of how deeply the DOGE wind-down touches the state relative to the rest of the country.

The mix skews toward grants: 30 contract terminations account for $134.8M (22.5%), while 150 grant terminations account for $465.0M (77.5%). That split matters, contract terminations hit procurement-exposed businesses and installations, while grant terminations flow through universities, nonprofits, state agencies, and research institutions, so the two categories land on very different parts of Maine's economy.

Context from FY2025 USASpending.gov puts the DOGE numbers in scale: Maine received $12.4K in federal contracts and $4.6K in grants last fiscal year out of $22.0B in total federal spending. The estimated $599.8M in DOGE cuts represents a proportional share of that baseline, an upper-bound estimate, since DOGE's own API does not publish state-level attribution and actual terminations may be concentrated in specific counties, agencies, or programs rather than distributed evenly across the state.

A word on how to read these state figures. The Department of Government Efficiency publishes its savings claims as national totals at doge.gov, and its public API does not say which state any single terminated contract or grant belongs to. To put a number on each state, we distribute those national terminations in proportion to how much federal money the state actually drew during fiscal year 2025, using contract and grant obligations reported on USASpending.gov, the spending-transparency system the U.S. Treasury has operated since the DATA Act of 2014. Federal outlays exceeded $7.0 trillion in fiscal year 2025 (CBO Monthly Budget Review), and states with larger contract and grant bases absorb a larger modeled share of any wind-down. That makes every figure on this page an upper-bound estimate rather than a confirmed count: real terminations cluster in particular counties, agencies, and programs instead of spreading evenly. Our methodology lays out the exact distribution math and the source vintage so the estimate can be checked and reproduced.