Randy Feenstra
U.S. Representative · IA-4 · Republican
Statements and posts
234 press releases, floor remarks and posts since Jan 3, 2025.
Activity, last 12 weeks
0123+
Pick a week or a day to set the dates below. One count per message: copies of one post on X and Bluesky count once, and reposts aren’t counted. Shading is scaled to Feenstra’s own volume over the last 12 months (a typical active day = 1). Aug 17, 2026 – Nov 2, 2026.
3 statements, Jul 7, 2025 – Jul 13, 2025
Newest first-
Press release
Official
Today, U.S. Rep. Randy Feenstra (R-Hull) introduced legislation – the Livestock Indemnity Program Improvement Act – to make needed updates to the Livestock Indemnity Program (LIP) so that Iowa cattle and livestock producers receive a fair…
“When severe storms strike or animal disease spreads, Iowa cattle producers deserve a fair price for deceased livestock.”
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Press release
Official
Feenstra Applauds Trump Administration’s National Farm Security Action Plan
This initiative will help keep American farmland in the hands of American farmers, protect our agricultural research and supply chains from China, and defend American agriculture from the threat of foreign animal disease.
“I thank President Trump and Secretary Rollins for rolling out the National Farm Security Action Plan and standing with Iowa farmers and producers.”
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Press release
Official
Feenstra Celebrates President Trump Signing “One, Big, Beautiful Bill” into Law
On Friday July 4th, U.S. Rep. Randy Feenstra (R-Hull) released the following statement after attending the signing ceremony for President Trump’s “One, Big, Beautiful Bill.”
“It was an honor to be at the White House and watch President Trump sign into law the ‘One, Big, Beautiful Bill.’ This legislation is the largest tax cut for Iowa families, farmers, workers, seniors, and small businesses in history.”
Sources: members’ press releases from their official websites (since the 119th Congress began (Jan 3, 2025)), the Congressional Record (since Aug 2026), and Bluesky posts. Quotes are shown only when they match the archived source text word for word; topics are AI-read and mentions are matched from the text.