The MuniScore Methodology

A transparent, percentile-based financial health rating for U.S. municipalities. Four factors. Nine metrics. One score.

0–100
Score Scale
4
Factors
9
Metrics
14,857
Municipalities
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01.

Score composition

Anatomy of a MuniScore

The MuniScore is the weighted average of four factor scores. Each factor captures a different dimension of financial health, from the local economy to long-term debt obligations.

The weights reflect each factor's reliability: reserves (40%) are the most stable and universally reported indicator; a single-year operating margin (10%) can swing on one-time events.

72MuniScore
Economy25%
Budgetary Performance10%
Reserves & Flexibility40%
Debt & Obligations25%
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02.

The framework

4 Factors, 9 Metrics

Each factor measures a distinct dimension of financial health. The weight distribution reflects that fund balance reserves are the most reliable indicator, while a single-year operating margin can swing on one-time items.

1
Economy
25% weight · Census ACS

Economic health of the community. A strong tax base and employed population support revenue and reduce social service demand.

  • Median Household IncomeHigher ▲
  • Unemployment RateLower ▼
  • Poverty RateLower ▼
  • Bachelor's Degree+Higher ▲
2
Budgetary Performance
10% weight · Income Statement

Is the municipality living within its means? Lowest weight because single-year results can swing on one-time items like asset sales or grant timing.

  • Operating MarginHigher ▲
3
Reserves & Flexibility
40% weight · Balance Sheet + IS

The financial cushion. Highest weight because fund balance is the most stable, universally reported indicator. GFOA recommends a minimum ~16.7% of expenditure.

  • Unreserved FB / ExpenditureHigher ▲
  • Total FB / ExpenditureHigher ▲
4
Debt & Long-Term Obligations
25% weight · LTO / Reconciliation

Long-term commitments relative to revenue capacity. Uses TGF revenue as denominator, following S&P, Moody's, and GFOA methodology.

  • Debt BurdenLower ▼
  • Pension & OPEB BurdenLower ▼
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03.

Scoring engine

From Raw Data to Score

Three steps transform financial data into a MuniScore.

1

Score Each Metric

Compare each raw value against the national distribution of peers from the same fiscal year and sector. Map to a 0–100 score using percentile breakpoints with linear interpolation.

2

Average Into Factors

Each factor score is the simple average of its available metric scores. If a metric can’t be computed, it’s excluded from the average — not counted as zero.

3

Weight Into MuniScore

The overall MuniScore is the weighted average of the four factor scores (25/10/40/25). If a factor is missing, its weight redistributes to the remaining financial factors.

Percentile-to-Score Mapping

10
P10
25
P25
50
P50 (Median)
75
P75
90
P90
Example: If a city's operating margin is 10.96% and the P75 for cities in that fiscal year is also 10.96%, it scores 75. Values between breakpoints are linearly interpolated. For “lower is better” metrics (debt, unemployment), the scale is inverted.
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Per-Year Distributions

A city running a deficit during COVID-era 2020 is compared against other 2020 cities, not against a boom year.

Per-Sector Distributions

School districts typically have lower reserves but higher pension burdens than cities. Per-sector scoring ensures apples-to-apples comparisons.

MetricCity P50County P50School P50
Operating Margin5.4%7.2%3.4%
Total FB / Expenditure56.7%61.0%31.9%
Debt / TGF Revenue30.9%19.4%51.0%
NPL+OPEB / Revenue34.0%20.8%57.4%
04.

Fair comparisons

Scored Against Real Peers

Every score is computed against municipalities of the same type and same fiscal year — not a one-size-fits-all benchmark.

Without sector segmentation, a school district at the median for its peers would score below 50 against the all-sector distribution. Per-sector scoring prevents this systematic bias.

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05.

Data completeness

Confidence Badges & Missing Data

Not every municipality has complete data for all 9 metrics. MuniScore handles this through dynamic weight redistribution: when a factor can't be scored, its weight is proportionally redistributed among the remaining financial factors.

A MuniScore requires Economy plus at least 2 financial factors. About 76% of municipalities (11,000+) meet this threshold. ~75% of scored municipalities receive High confidence.

High
7–9
Comprehensive
Moderate
5–6
Reliable
Low
3–4
Use caution
Insufficient
<3
Not enough data
  • Single-ACFR Rule

    All financial metrics must come from the same fiscal year. We never combine a 2024 balance sheet with a 2018 debt schedule.

  • BS+IS Required

    Both balance sheet and income statement must be present to compute financial factors. About 70% of municipalities have both.

  • Fund Consistency

    Within each factor, all metrics use the same fund — General Fund preferred, Total Governmental Funds as fallback. Never mixed.

  • Weight Redistribution

    Missing financial factor weights redistribute proportionally among remaining financial factors, never to Economy. If both Budget and Reserves are missing, score is unavailable.

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Comprehensive Annual Financial Reports

Audited financial statements filed with the Federal Audit Clearinghouse. Digitized and standardized for FY2016–2024.

14,857 munis12.7M line items9 fiscal years

Census American Community Survey

Economic data from the Census Bureau's 5-year ACS at place, MSA, and state levels. Automatic 3-tier fallback.

116K records3-tier fallback2016–2023
06.

Transparency

Data Sources

MuniScore draws on two primary public data sources. All underlying data is audited or produced by federal agencies — no proprietary or estimated inputs.

Financial data comes from CAFRs filed with the Federal Audit Clearinghouse. Economic data comes from the U.S. Census Bureau's American Community Survey.

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07.

Philosophy

Design Principles

Relative, Not Absolute

A score of 50 always means “at the median of peers.” No arbitrary fixed thresholds. More robust to shifts in the overall fiscal environment.

Fully Transparent

Every metric, weight, and data source is documented. Users see which metrics were computed and which were unavailable. No black-box adjustments.

No Per Capita Metrics

Population data is unreliable for many entity types. Financial metrics use revenue or expenditure as denominators, following major rating agencies.

Single-Year Snapshots

No growth or trend metrics — many municipalities have non-consecutive fiscal years, making year-over-year calculations unreliable.

Graceful Degradation

Missing data handled through weight redistribution, not zero-filling. Confidence badges communicate data completeness honestly.

Industry-Informed

Inspired by S&P, Moody’s, GFOA, and the Lincoln Institute — adapted for digitized CAFR data at scale.

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See It in Action

Explore Municipal Financial Data with Ease.

Browse MuniScores for 14,857 municipalities. Compare financial health across cities, counties, and school districts.