DC Swamp Draining May Spark Recessionary Pain For Region

President-elect Donald Trump plans to make Elon Musk “secretary of cost-cutting” to lead the Department of Government Efficiency (DOGE) in slashing $2 trillion from the federal budget—about a third of what the bloated federal government spent in the latest fiscal year. This once-in-a-generation initiative will cut thousands of federal workers and reduce or even eliminate the vast cancerous bureaucracy with a new small government led by capable leaders.

Musk wrote in an X post on Sunday night that this shock-and-awe approach will have “obstacles overcoming the Kafkaesque nature of the rules governing this vast bureaucracy and ensuring that maniacally dedicated small-government revolutionaries join this administration. ” 

Musk was responding to Vivek Ramaswamy’s X post, “We won & now have a once-in-a-century opportunity to radically downsize the size, scope, and mission of the federal government. And the top obstacle to our success won’t even be the Democrats.” 

Indeed, the obstacles are overcoming the Kafkaesque nature of the rules governing this vast bureaucracy and ensuring that maniacally dedicated small-government revolutionaries join this administration! https://t.co/ObfnIeuTXa

— Elon Musk (@elonmusk) November 11, 2024

Trump is less than three months away from implementing his plan to ‘Make America Great Again’… and thousands of federal workers across DC, Northern Virginia, and Baltimore region have been put on notice for potential job loss.

A recent report by the Washington Post showed that approximately 15% of the 2.19 million civilian full-time federal employees in the US (data from 2023), or about 328,500, live in Northern Virginia, suburban Maryland, and even a touch of West Virginia. 

The other 85% work elsewhere around the country. 

More recent figures show that figure is as high as 373,000 in the Virginia, DC, and Maryland region. These job cuts could spark economic turmoil and reshape the DC landscape—or the beginnings of draining the swamp.