Policy Impact Analysis - 117/S/4197

Bill Overview

Title: SWAMP Act of 2022

Description: This bill prohibits new construction, major renovation, leasing, or renewing a lease of certain executive agency headquarters in the District of Columbia metropolitan area and establishes a competitive bidding process for the relocation of such headquarters. The General Services Administration (GSA) must (1) establish a process to allow an executive agency to request the GSA to issue a solicitation for the relocation of its headquarters or allow the GSA to issue such a solicitation without a request, if necessary; (2) allow any state to respond to a solicitation with a proposal for the relocation of the agency's headquarters; and (3) in consultation with the executive agency, select a state for the relocation of the agency's headquarters using a competitive bidding procedure based on certain considerations.

Sponsors: Sen. Ernst, Joni [R-IA]

Target Audience

Population: Employees and associated individuals with federal executive agencies in DC

Estimated Size: 3000000

Reasoning

Simulated Interviews

federal employee (Washington, DC)

Age: 39 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 7/20

Statement of Opinion:

  • If my agency moves, I might have to relocate my family, which would be stressful and costly.
  • There is potential for career growth if I move with the agency to a new location.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 6
Year 2 5 6
Year 3 6 6
Year 5 7 6
Year 10 7 6
Year 20 6 6

IT contractor for federal agencies (Arlington, VA)

Age: 45 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 2.0 years

Commonness: 6/20

Statement of Opinion:

  • Many of my contracts are local; if agencies move, I could lose significant business.
  • The uncertainty is concerning, as I might need to compete for new contracts in other states.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 7
Year 2 6 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 7 7

Administrative assistant at a startup (Los Angeles, CA)

Age: 29 | Gender: other

Wellbeing Before Policy: 8

Duration of Impact: 0.0 years

Commonness: 10/20

Statement of Opinion:

  • The policy doesn't really affect my current life or job.
  • I can see how it could benefit some local economies across the country.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 8 8
Year 5 8 8
Year 10 8 8
Year 20 8 8

Real estate developer (Austin, TX)

Age: 52 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • If an agency relocates to Texas, it could drive property demand and business for my development projects.
  • I'm actively exploring partnerships to attract agency relocations.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 8 6
Year 5 8 6
Year 10 9 6
Year 20 9 6

Analyst at a federal agency (New York, NY)

Age: 34 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 1.0 years

Commonness: 8/20

Statement of Opinion:

  • Our agency hasn't shown any intent to relocate, so I'm not too concerned.
  • If relocation were an issue, I might consider changing jobs instead of moving.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 8 8
Year 5 8 8
Year 10 8 8
Year 20 8 8

Cafeteria manager in a federal building (Washington, DC)

Age: 41 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 3.0 years

Commonness: 4/20

Statement of Opinion:

  • If a large agency relocates, I could lose a significant portion of my customers.
  • I'm concerned about the future of my business if this trend continues.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 4 5
Year 2 5 5
Year 3 5 5
Year 5 5 5
Year 10 5 5
Year 20 5 5

State government official (Richmond, VA)

Age: 55 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • I see this as an opportunity to boost our state's economy and job market.
  • We are preparing proposals to attract federal offices to our area.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 8 7
Year 3 8 7
Year 5 8 7
Year 10 9 7
Year 20 9 7

Graduate student in urban planning (Chicago, IL)

Age: 26 | Gender: female

Wellbeing Before Policy: 9

Duration of Impact: 5.0 years

Commonness: 6/20

Statement of Opinion:

  • I'm curious to see how these relocations might reshape cities.
  • This could be a major case study for the future of urban planning.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 9 9
Year 2 9 9
Year 3 9 9
Year 5 9 9
Year 10 9 9
Year 20 9 9

Federal employee in IT field (Seattle, WA)

Age: 38 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 7/20

Statement of Opinion:

  • Since I work remotely, HQ relocations don't concern me much.
  • Having HQs in more diverse locations can be an advantage for diversity.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 7 7

Professor of Public Policy (Atlanta, GA)

Age: 60 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 4/20

Statement of Opinion:

  • The relocations present a fascinating policy case with broad economic implications.
  • I expect to publish research on this massive relocation strategy.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 7 7

Cost Estimates

Year 1: $50000000 (Low: $30000000, High: $80000000)

Year 2: $40000000 (Low: $25000000, High: $60000000)

Year 3: $35000000 (Low: $20000000, High: $50000000)

Year 5: $30000000 (Low: $18000000, High: $45000000)

Year 10: $25000000 (Low: $15000000, High: $40000000)

Year 100: $10000000 (Low: $5000000, High: $15000000)

Key Considerations