Municipal revenue forecasting: A practical guide

Why municipal revenue forecasting is different

Municipal revenue does not behave like corporate revenue. A company may forecast sales, subscriptions, contracts, or customer demand. A municipality often needs to forecast a mix of property taxes, fees, permits, intergovernmental revenue, grants, charges for services, fines, investment income, and other local sources.

Each source may follow a different pattern. Property tax revenue may depend on assessed value, millage rates, collection rates, exemptions, and timing. Permit revenue may move with construction activity. State aid or intergovernmental revenue may depend on policy decisions outside the municipality’s control. Charges for services may depend on population, usage, rates, and local behavior.

That means municipal revenue forecasting needs more than a single growth percentage. It needs context.

• What revenue source is being forecast?
• What has happened historically?
• What assumptions are being made?
• What external factors could affect the source?
• How sensitive is the forecast to small changes?
• How will the forecast affect reserves, staffing, capital planning, or debt service?

Start with historical actuals

Historical actuals are the best starting point for most municipal revenue forecasts. They show what actually happened, not what was budgeted or hoped for.

A forecast should begin by looking at several years of actual revenue by source. One year may be unusual. Two years may show a short-term trend. A longer lookback can help finance teams identify patterns, volatility, and outliers.

For example, a municipality reviewing permit revenue might look at ten years of actuals and ask whether recent growth reflects a durable trend or a temporary construction cycle. A finance team reviewing investment income might separate normal yield changes from one-time market conditions.

Historical actuals help answer an important question: Is our future assumption reasonable compared with what has actually happened?

• Review at least several years of actual revenue where available
• Separate recurring revenue from one-time revenue
• Identify unusual years before calculating growth rates
• Compare actuals to budgeted expectations
• Look for timing patterns and volatility
• Document why the future may differ from the past

Separate revenue sources before forecasting

A common forecasting mistake is treating total revenue as one number. Total revenue may be useful for a high-level view, but it can hide the behavior of individual sources.

Property tax revenue, permit revenue, grant revenue, investment income, and service charges may each move for different reasons. Forecasting them separately gives finance teams more control over assumptions and makes the final forecast easier to explain.

For example, a 3% total revenue growth assumption may seem reasonable at first glance. But if property tax revenue is stable, permit revenue is declining, and grant revenue includes one-time money, the combined number may hide risk.

A better approach is to forecast major sources individually, then roll them up into a total view.

• Forecast major recurring revenue sources separately
• Identify one-time or non-recurring revenue
• Treat volatile sources carefully
• Document the driver behind each assumption
• Roll individual forecasts into a total revenue view

Understand the drivers behind property tax revenue

For many municipalities, property tax revenue is one of the most important revenue sources. It is also often misunderstood because it depends on several drivers, not just one.

Important drivers may include assessed taxable value, millage rate, exemptions, new growth, collection rate, abatements, tax caps, and local policy choices.

A useful forecast separates these drivers where possible. This allows finance leaders to explain whether projected property tax growth is coming from new taxable value, rate changes, improved collection, or another factor.

This matters because different drivers have different implications. Revenue growth from new taxable value may tell a different story than revenue growth from a rate increase. A lower collection rate may affect cash flow even if the levy itself looks stable.

• Assessed taxable value
• Millage or tax rate
• Collection rate
• New construction or taxable growth
• Exemptions and abatements
• Policy limits or tax caps
• Timing of collections

Use assumptions carefully

Every forecast contains assumptions. The important question is whether those assumptions are visible, reasonable, and easy to explain.

Assumptions may include growth rates, collection rates, inflation, state aid expectations, fee changes, permit activity, economic conditions, or timing of receipts.

A strong forecast does not bury assumptions in a spreadsheet. It makes them clear enough that another person can understand how the forecast was built.

Good assumptions are:

• Specific enough to review
• Connected to historical actuals where possible
• Updated when conditions change
• Documented in plain language
• Separated by revenue source
• Tested under more than one scenario

Build scenarios instead of relying on one forecast

A single forecast line can make the future look more certain than it is. Municipal finance leaders know that conditions can change. Revenue may come in higher or lower than expected. Inflation may pressure expenditures. Permit activity may slow. State aid may change. Collection rates may shift.

Scenario planning helps finance teams show what could happen under different assumptions.

Common scenarios might include:

• Baseline scenario
• Lower revenue growth scenario
• Higher expenditure growth scenario
• Stress case
• Delayed grant or intergovernmental revenue scenario
• Reduced permit or fee activity scenario

Use sensitivity analysis to explain uncertainty

Sensitivity analysis helps show how changes in assumptions affect future results. Instead of presenting one rigid projection, finance teams can show a range of possible outcomes.

For example, a municipality might model reserve balances under different revenue growth and expenditure growth assumptions. The baseline may show reserves staying above the policy floor. A lower revenue scenario may show reserves approaching the floor in later years. A stress case may show the need for earlier review.

This does not mean the forecast predicts exactly what will happen. It means the forecast helps leaders understand exposure.

A sensitivity view can help explain:

• How much the forecast depends on revenue growth
• Whether reserves remain healthy under lower-growth assumptions
• Which years may need closer review
• Whether policy thresholds are at risk
• How much flexibility exists before tradeoffs are needed

Document the forecast in plain language

A forecast is more useful when people understand it. Finance teams should document assumptions, major drivers, known risks, and scenario differences in plain language.

This documentation does not need to be long. It needs to be clear.

For each major forecast, consider documenting:

• The revenue sources included
• The historical period reviewed
• The assumptions used
• The reason for those assumptions
• Known one-time items
• Major risks or uncertainties
• How the forecast affects reserves or other planning areas

Common mistakes to avoid

Municipal revenue forecasting becomes less useful when the assumptions are hidden or when all revenue sources are treated the same.

Common mistakes include:

• Using one growth rate for all revenue
• Treating one-time revenue as recurring
• Ignoring historical volatility
• Failing to separate budget from actuals
• Presenting one forecast as certain
• Ignoring collection timing
• Forecasting revenue without showing reserve impact
• Failing to document assumptions

How Aurelius Civic supports municipal revenue forecasting

Aurelius Civic is designed to help municipal finance teams move from static forecasts to clearer planning views.

The platform supports forecasting work by helping teams:

• Compare future assumptions against historical actuals
• Model revenue and reserve scenarios
• Show sensitivity ranges instead of one rigid forecast
• Normalize key financial drivers for comparison
• Connect forecasts to reserve health
• Explain assumptions in a more defensible way