ConnecticutElevated
Ranking 27 of 50 states and DC. The score is driven primarily by its cliff severity (92th percentile) and population exposure (65th percentile). 12% of the state's population — 422,196 people — earns in the income range where benefit phase-outs concentrate. TANF is the primary cliff driver. Each dimension below shows its component score, the underlying metrics, and how Connecticut compares to all 50 states and DC.
A score of 78 means cliff conditions are more severe than in 78% of U.S. counties. State policy can shift the overall score by up to 25%. Even communities with low scores have families facing steep cliffs — the score measures how a place compares, not what any individual family experiences. Full methodology →
Population Exposure
How many people earn in the income range where benefit phase-outs concentrate — and who they are. 422,196 people in Connecticut earn in the cliff zone — between 100% and 200% of the federal poverty level — where SNAP, Medicaid, childcare subsidies, and other major programs phase out.
Population by family type across income bands. Use the tabs to see how this splits by working status or program enrollment — families enrolled in more programs face steeper compound cliffs when income rises.
Cliff Severity
How steeply benefits drop when families earn more. The chart below shows the share of each additional dollar lost to benefit reductions and taxes at each wage level. When the line exceeds 100%, a raise leaves the family worse off. TANF creates the largest benefit loss at the cliff point in 100% of Connecticut’s counties.
Rates are averaged over a $2.50/hr raise, matching the Upward Mobility Act’s proposed 50% cap. This chart uses Connecticut’s program rules and local costs. Rates assume full program enrollment — most families are not enrolled in all programs simultaneously. Hover to see which programs drive each peak.
The Upward Mobility Act of 2026 uses this same measure — Marginal Effective Tax Rate — and proposes capping it at 50% for families receiving means-tested benefits.
Economic Vulnerability
Whether the local economy positions families where benefit phase-outs are most likely to trigger — and whether advancement is realistic. The chart below shows what cliff-zone industries actually pay, compared to what each family type needs to earn to clear benefit phase-outs.
Policy Environment
State policies that moderate or amplify cliff severity. Each sub-score runs 0 to 100 — lower means the state does more to mitigate cliffs in that area. The four combine into a multiplier that shifts the overall CLIFF Score by up to 25%. Same for all counties in a state.
Connecticut has taken 20 policy actions addressing benefit cliffs across 5 legislative periods.
2024-2025
- Asset limit removed for SNAP; for SNAP elderly/disabled households with gross income over 200% FPL, asset limit now $4,500
- 100% earned income now disregarded for TANF applicants/recipients receiving assistance in one of the four prior months.
- In 2024, 21-month TANF time limit increased to 36 months.
- WOTC (Work Opportunity Tax Credit) - a federal tax credit ($2400 for hiring a TANF recipient) made available to employers for hiring certain individuals from target groups who have faced...
- Child care eligibility set to 60% of SMI; redetermination eligibility set to 65% of SMI
- At redetermination for child care assistance, families whose income has increased above the state’s initial income threshold ( >60% SMI) but remains at or below the second eligibility threshold (≤...
2022-2023
- TANF time limits increased, asset limits increased
- State EITC increased to 40%
- Increased SNAP income eligibility from 185% to 200%
- Initial TANF gross income eligibility tied to 55% of FPL in 2022; benefit level set to 73% of income eligibility level
2020-2021
- TANF family cap repealed in 2021
- Medicaid eligibility + coverage expanded for kids + pregnant women
- Benefit Cliff calculator tool piloted
- Covered CT established, a Medicaid 1115 waiver program that offers no cost QHP/Medicaid hybrid for adults 18-64 up to 175% of FPL if over Medicaid income limits; includes dental and non-emergency...
2018-2019
- Child care sliding scale improved
- Medicaid eligibility for parent/caretakers set to 160% FPL
- State EITC increased to 30.5%
- Child care asset limit set to $1,000,000
2016-2017
- Joined New England workgroup focused on benefit cliffs
- Established study on benefit cliffs and opportunities to mitigate them
Economic Impact
About 68,394 working families in Connecticut earn in the cliff zone. Based on a 2025 survey of benefit recipients, we estimate roughly 1 in 6 are actively limiting their earnings to protect their benefits — declining raises, refusing hours, or passing up better-paying jobs. Each family foregoes an estimated $2,100 per year. Those lost wages mean less economic activity in local communities — and benefit spending continues because families remain below eligibility thresholds. The total: an estimated $55M per year.
That figure captures only what we can measure. It doesn't capture years of stalled careers, children growing up in financial instability, or families for whom entering the workforce would mean losing more in benefits than they gain in wages.
Estimated annual cost
$55M
Modeled from survey-reported behavioral rates (CSD/Washington University 2025) and Census ACS population data. Click any row for methodology.
68,394 families × 16% avoidance × ~$2,100/yr × multiplier + benefit continuation = $55M
What this excludes: Multi-year career stagnation, health impacts of benefit loss, educational outcomes for children in families navigating benefit phase-outs, and families for whom entering the workforce would mean losing more in benefits than they gain in wages. This estimate captures only the measurable portion — the actual cost to Connecticut is substantially higher. Full methodology →
Geographic Data
Explore cliff severity across Connecticut’s 9 counties and 5 congressional districts. The map is shaded by CLIFF Score by default — use the tabs to switch views. Click any county to inspect, or click a second to compare. Toggle to Congressional to see district-level cliff-zone data.
Composite severity score (0–100) combining exposure, severity, vulnerability, and policy.
Click any county to inspect
| CountyCounty↕ | CLIFF ScoreScore↓ | PopulationPopulation↕ | Cliff Zone %Cliff Zone %↕ | Families at RiskFamilies↕ | Peak METRPeak METR↕ |
|---|---|---|---|---|---|
| South Central Connecticut Planning Region | 32Moderate | 570,598 | 13.6% | 16,768 | 198% |
| Naugatuck Valley Planning Region | 30Moderate | 454,969 | 13.4% | 13,195 | 205% |
| Capitol Planning Region | 25Moderate | 977,290 | 11.5% | 23,832 | 199% |
| Southeastern Connecticut Planning Region | 25Moderate | 279,971 | 13.5% | 7,822 | 199% |
| Northeastern Connecticut Planning Region | 22Moderate | 96,312 | 11.6% | 2,394 | 210% |
| Greater Bridgeport Planning Region | 21Moderate | 329,259 | 13.4% | 10,117 | 198% |
| Lower Connecticut River Valley Planning Region | 13Low | 175,822 | 9.4% | 3,196 | 199% |
| Northwest Hills Planning Region | 13Low | 113,216 | 10.8% | 2,761 | 210% |
| Western Connecticut Planning Region | 11Low | 627,071 | 9.7% | 12,951 | 198% |
Data Explorer
Interactive demographic breakdowns of Connecticut’s cliff-zone population — by race, education, industry, age, and family type. Sourced from Census PUMS microdata.
Who is in Connecticut’s cliff zone?
The chart below shows every person in Connecticut’s cliff zone — the income range where benefit phase-outs from multiple programs overlap — broken down by who they are. Each bar is a 10-point income band (100–109% FPL, 110–119%, etc.). The colored segments show how that income band breaks down by the selected dimension.
Use Color by to switch between race, education, industry, age, family type, and other dimensions. Use Filter to focus on a specific group — single mothers, workers in a particular industry, households with children. The data table below the chart shows exact counts and percentages.
Source: Census ACS PUMS 2020–2024, individual-level records weighted to reflect the full population. This shows who is structurally exposed to cliffs based on where their income falls — not who has actually experienced a benefit loss.
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