Policy Impact Analysis - 117/HR/8661

Bill Overview

Title: Guaranteeing Unemployment Assistance and Reducing Deception Act

Description: This bill addresses state unemployment insurance programs. Among other provisions, the bill directs the Department of Labor to establish new program performance standards (including measures that address equity and assistance in fraud recovery) and award performance bonuses to states for their excellent performance or substantial improvement with respect to these performance standards.

Sponsors: Rep. Horsford, Steven [D-NV-4]

Target Audience

Population: Individuals who receive or seek unemployment benefits

Estimated Size: 6000000

Reasoning

Simulated Interviews

software engineer (Los Angeles, CA)

Age: 34 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • I hope the policy will make the unemployment benefits process more transparent and fair.

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 7
Year 10 8 7
Year 20 8 7

factory worker (Detroit, MI)

Age: 45 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 4/20

Statement of Opinion:

  • Anything that helps reduce fraud is good. More honest benefits distribution is needed.

Wellbeing Over Time (With vs Without Policy)

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

marketing specialist (Houston, TX)

Age: 29 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 10.0 years

Commonness: 7/20

Statement of Opinion:

  • Equity in unemployment benefits is critical. I hope the policy addresses this need.

Wellbeing Over Time (With vs Without Policy)

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

construction worker (Seattle, WA)

Age: 52 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 5/20

Statement of Opinion:

  • I'm skeptical that these changes will reach someone about to retire like me.

Wellbeing Over Time (With vs Without Policy)

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

barista (New York, NY)

Age: 24 | Gender: other

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 6/20

Statement of Opinion:

  • It's crucial that support systems adapt to the gig economy and part-time workers.

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 6
Year 10 7 6
Year 20 6 6

nurse (Memphis, TN)

Age: 60 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 6/20

Statement of Opinion:

  • I am retired, but I see how this policy could help those still in the workforce.

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

restaurant manager (Phoenix, AZ)

Age: 38 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 9/20

Statement of Opinion:

  • Efficiency in processing claims would greatly help people like me relying on partial benefits.

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 6
Year 10 7 6
Year 20 6 6

caretaker (Chicago, IL)

Age: 48 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • Policies that improve fairness and reduce fraud ensure those truly in need get help.

Wellbeing Over Time (With vs Without Policy)

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

student (Boulder, CO)

Age: 19 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 0.0 years

Commonness: 10/20

Statement of Opinion:

  • I'm mostly unaffected for now but might rely on such programs in the future.

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 6 6

mechanic (Rural Alabama)

Age: 50 | Gender: other

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 3/20

Statement of Opinion:

  • Real change would mean getting timely assistance, especially in rural areas.

Wellbeing Over Time (With vs Without Policy)

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

Cost Estimates

Year 1: $500000000 (Low: $400000000, High: $600000000)

Year 2: $520000000 (Low: $420000000, High: $620000000)

Year 3: $540000000 (Low: $430000000, High: $650000000)

Year 5: $580000000 (Low: $460000000, High: $700000000)

Year 10: $650000000 (Low: $520000000, High: $750000000)

Year 100: $0 (Low: $0, High: $0)

Key Considerations