Bill Overview
Title: Made in America Manufacturing Communities Act of 2022
Description: This bill establishes the Manufacturing Communities Support Program to provide financial and technical assistance to support investments in U.S. manufacturing.
Sponsors: Sen. Gillibrand, Kirsten E. [D-NY]
Target Audience
Population: Individuals linked to U.S. manufacturing and associated communities
Estimated Size: 15000000
- The bill aims to invest in U.S. manufacturing, which employs millions of people across various sectors.
- By supporting investments in manufacturing, the bill will impact industrial workers who are directly employed by manufacturing companies.
- The supply chain linked to manufacturing will also see an impact, reaching additional employees and businesses indirectly.
- Local economies that depend on manufacturing industries for employment and revenue will benefit, directly affecting community populations.
- Technical assistance could support small to large manufacturing firms, enhancing their ability to expand operations and workforce.
- Enhanced manufacturing competitiveness may also bolster job creation in associated industries.
- Communities where these manufacturing firms operate will see changes in employment rates and economic growth.
Reasoning
- The policy targets the manufacturing sector, which is a significant part of the U.S. economy, providing direct employment to around 12.8 million Americans as of 2021.
- Given the complex supply chains, beyond direct employment, many more are indirectly affected by changes in manufacturing output.
- While $300 million in year 1 and nearly $2 billion over ten years sounds substantial, the size and scale of manufacturing mean it will have to be strategically allocated to areas and projects that maximize growth and benefit.
- Many areas heavily reliant on manufacturing will experience more tangible impacts, while regions with a diversified economy might see minimal effects.
- Not all manufacturing sectors will receive equal investment. Priority may be given to those who can demonstrate significant economic return or innovation capabilities.
- Given the long-term nature of manufacturing investments, substantial changes in wellbeing might take years to fully materialize and become evident.
Simulated Interviews
Automotive assembly line worker (Detroit, MI)
Age: 45 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 20.0 years
Commonness: 3/20
Statement of Opinion:
- I think funding will help secure more jobs here because our plant has been struggling with outdated equipment.
- New investments might mean training on new technologies, which I am excited about.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 4 |
| Year 2 | 6 | 4 |
| Year 3 | 7 | 4 |
| Year 5 | 8 | 3 |
| Year 10 | 8 | 3 |
| Year 20 | 8 | 3 |
Software engineer (Austin, TX)
Age: 28 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 4/20
Statement of Opinion:
- Indirectly, this could mean more contracts for our company to upgrade systems for manufacturing clients.
- However, I am not sure how much of this budget will affect software specifically.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 5 |
Small business owner (tooling supplier) (Pittsburg, PA)
Age: 39 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 6/20
Statement of Opinion:
- We've been trying to expand, and more financial assistance could help our business grow.
- I'm nervous about whether we'll see direct benefits or if it'll be absorbed by larger players.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 4 |
| Year 20 | 7 | 4 |
Unemployed (Peoria, IL)
Age: 55 | Gender: male
Wellbeing Before Policy: 2
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- I hope this means more openings and training in modern manufacturing jobs might be available soon.
- It's critical for places like Peoria where manufacturing pullback was sharp.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 3 | 2 |
| Year 2 | 4 | 2 |
| Year 3 | 5 | 2 |
| Year 5 | 6 | 2 |
| Year 10 | 6 | 1 |
| Year 20 | 5 | 1 |
Retired (Raleigh, NC)
Age: 63 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 7/20
Statement of Opinion:
- Past efforts to stimulate manufacturing didn't reach far. There's skepticism this will be any different.
- If it works, the community overall might become more vibrant like it used to be.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
Tech startup founder (San Francisco, CA)
Age: 30 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 5.0 years
Commonness: 5/20
Statement of Opinion:
- Manufacturing tech is critical for innovation, and policies like this are encouraging.
- I'd like to see more coordination between different tech firms and traditional manufacturing sectors.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 8 | 7 |
| Year 20 | 7 | 6 |
Logistics manager (Little Rock, AR)
Age: 48 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- Any expansion or investment often means more business for logistics operations like us.
- My worry is that bureaucracy might prevent small logistics firms from actually seeing benefits quickly.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 7 | 5 |
| Year 10 | 7 | 4 |
| Year 20 | 6 | 4 |
Research scientist in materials (Buffalo, NY)
Age: 34 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 4/20
Statement of Opinion:
- I am optimistic about funding for research as it’s key to innovation.
- This could attract more new talent and resources to the lab.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 9 | 5 |
| Year 20 | 8 | 5 |
Economic analyst (Chicago, IL)
Age: 27 | Gender: other
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 5/20
Statement of Opinion:
- Increased funding can reveal trends and improvements in US manufacturing efficiency.
- However, there’s always concern over actual measurable impacts versus policy intentions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 6 | 5 |
| Year 10 | 6 | 5 |
| Year 20 | 5 | 4 |
HR manager for manufacturing firm (Houston, TX)
Age: 52 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 6/20
Statement of Opinion:
- There is potential for extensive workforce training programs that could upskill our workers.
- My concern lies in whether these initiatives will be implemented at the pace that's needed.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 7 | 5 |
| Year 20 | 6 | 4 |
Cost Estimates
Year 1: $300000000 (Low: $250000000, High: $350000000)
Year 2: $250000000 (Low: $200000000, High: $300000000)
Year 3: $250000000 (Low: $200000000, High: $300000000)
Year 5: $200000000 (Low: $150000000, High: $250000000)
Year 10: $100000000 (Low: $80000000, High: $120000000)
Year 100: $0 (Low: $0, High: $100000)
Key Considerations
- The potential economic revitalization of local communities heavily reliant on manufacturing.
- The varying effectiveness of financial and technical support based on regional and sector-specific needs.
- The ability to effectively manage and distribute funding to achieve the desired outcomes.