Policy Impact Analysis - 117/S/5219

Bill Overview

Title: Restaurant Revitalization Tax Credit Act

Description: This bill allows certain restaurants affected by the COVID-19 pandemic a credit against payroll tax liability up to 100% of the wages paid to their employees, not to exceed $25,000 in any calendar quarter.

Sponsors: Sen. Cardin, Benjamin L. [D-MD]

Target Audience

Population: Global restaurant industry workers

Estimated Size: 15000000

Reasoning

Simulated Interviews

Restaurant Manager (New York, NY)

Age: 45 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 10/20

Statement of Opinion:

  • I think this tax credit could really help us keep staff that we were considering letting go.
  • It might not solve all our problems but it is a step in the right direction.

Wellbeing Over Time (With vs Without Policy)

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

Bartender (Kansas City, MO)

Age: 32 | Gender: male

Wellbeing Before Policy: 4

Duration of Impact: 3.0 years

Commonness: 15/20

Statement of Opinion:

  • If my employer gets a tax credit, they might be able to afford putting me back on full time.
  • It's tough right now, anything would help honestly.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 6 5
Year 5 6 5
Year 10 5 4
Year 20 5 4

Restaurant Owner (Miami, FL)

Age: 50 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • This relief could help us reinvest in some much-needed renovations.
  • It's a relief to have some acknowledgment but I hope the roll-out is smooth.

Wellbeing Over Time (With vs Without Policy)

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

Waiter (Los Angeles, CA)

Age: 27 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 1.0 years

Commonness: 20/20

Statement of Opinion:

  • I don't think our restaurant will benefit much since we bounced back pretty fast.
  • It doesn't affect me directly.

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 6 6

Chef (Austin, TX)

Age: 62 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 0.0 years

Commonness: 4/20

Statement of Opinion:

  • I see this as beneficial for smaller or struggling operations, but not for ours.
  • We didn't really need much help during the pandemic as we adapted quickly.

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 7 7

Restaurant Owner (Chicago, IL)

Age: 39 | Gender: female

Wellbeing Before Policy: 3

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • Every bit helps, but it might not be enough to cover our debt.
  • I'm hopeful but cautious with my optimism.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 4 3
Year 2 5 4
Year 3 6 4
Year 5 7 5
Year 10 7 6
Year 20 6 5

Line Cook (Seattle, WA)

Age: 29 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 1.0 years

Commonness: 12/20

Statement of Opinion:

  • The tax credit would likely pass over my establishment since our operations remained functional.
  • I'm glad it's going to help others though.

Wellbeing Over Time (With vs Without Policy)

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

Cafeteria Worker (Dallas, TX)

Age: 60 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 2.0 years

Commonness: 18/20

Statement of Opinion:

  • If our cafeteria gets this type of credit, maybe they'll increase our hours.
  • It would definitely improve things for me if implemented.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 6 5
Year 3 6 5
Year 5 6 5
Year 10 5 4
Year 20 4 4

Restaurant Supplier (Phoenix, AZ)

Age: 48 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 6/20

Statement of Opinion:

  • While it's aimed at restaurants, it might indirectly benefit us through higher demand from healthier businesses.
  • The right policies become catalysts for a lot of positive chain reactions.

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 6 6
Year 20 6 6

Barista (Boston, MA)

Age: 22 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 3.0 years

Commonness: 14/20

Statement of Opinion:

  • A lot hinges on us getting this credit - it could mean keeping my job here.
  • It's a stressful situation, thankfully this helps.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 6 5
Year 5 6 5
Year 10 5 4
Year 20 4 3

Cost Estimates

Year 1: $4000000000 (Low: $3000000000, High: $5000000000)

Year 2: $4000000000 (Low: $3000000000, High: $5000000000)

Year 3: $4000000000 (Low: $3000000000, High: $5000000000)

Year 5: $3800000000 (Low: $2800000000, High: $4800000000)

Year 10: $3500000000 (Low: $2500000000, High: $4500000000)

Year 100: $2500000000 (Low: $1500000000, High: $3500000000)

Key Considerations