Long-Term Financial Forecasting for Local Governments

60 Government Finance Review | October 2008

Too many jurisdictions

have found out

the hard way what

can happen in the

absence of a realistic

forecast model.

Cities, counties, and other localgovernment agencies areincreasingly adopting long-term

financial forecasting as a critical com-ponent of their financial managementpractices. Too many governments havefound out the hard way what can hap-pen in the absence of a realistic fore-cast model,one that projects and quan-tifies the impact of potential revenueshortfalls and increased liabilities wellinto the future.Forecasts can be used tocreate a strategic context for evaluatingthe annual budget, to establish a base-line for measuring the long-term effectsof decisions, to test the economiceffects of best-case and worst-casefunding scenarios, and to establish abaseline projection of revenues, expen-ditures, and future cash flows and fundbalances.

An effective forecast model is not abudget, nor is it a Soviet-style “5-yearplan” that remains static and sits on ashelf. It is also not an absolute predic-tion of the future. Instead, a forecastmodel projects a range of possible out-comes, based on a set of known vari-ables and assumptions.As with a weath-er forecast,a financial forecast is alwayssubject to revision based on new infor-mation, and an effective budgeting andplanning process provides a consistentroutine for updating the forecast. If pre-pared and managed properly,a forecastcan also help public officials evaluatethe financial effects of proposed initia-tives, and it can help educate con-

stituents about an organization’s pres-ent and potential financial capabilities.In particular, forecast models thatinclude well-designed charts and tablescan be used as visual aids in public pre-sentations about the organization’sfinances, helping elected officials, citi-zens,and other stakeholders gain a bet-ter understanding of financial issues.

FORECASTING TECHNIQUES

Baseline forecasts are based onrecurring revenues and expenditures,projected at least five years into thefuture. It is recommended they be pro-jected much further out, as far as 20years, depending on known commit-ments and liabilities such as employeebenefit and debt obligations. Proposednew revenues and expenditures thatthe organization has not committed tocan be included in the forecast modelas “optional”variables, the future effectsof which can be measured against thebaseline forecast.

Local governments typically use oneor a mixture of three techniques forforecasting revenues and expenditures:expert judgment and analysis, deter-ministic forecasting, and econometricmodeling. The methods used dependon the type of revenue being forecastedand the availability of historical andcurrent economic data, along withother factors that drive the revenue.

Expert judgment and analysis can beused when data are limited. This

Long-Term Financial Forecasting

for Local Governments

By Christopher J. Swanson

SOLUTIONS

October 2008 | Government Finance Review 61

Exhibit 1: Factors that Influence Revenue

Revenue Source,Type Influence Factors

Property Tax Impact from housing market, home sales,foreclosure activity, assessed valuation trend,population, personal income, unemployment rate

Property Transfer Tax See Property TaxSales Tax Retail/commercial activity, consumer trends, impact of housing market, population growth, impact

of regional economic forces, planned developments, personal income, unemployment rateFranchise Tax Population change, general demand, new development, per unit usage, potential rate increases

(external providers and city rates)Transient Occupancy Tax Hotel/motel development, occupancy rate trends, travel & tourism trendsOther Tax Impact factors affecting other taxesIntergovernmental—Federal Availability of federal grants and reimbursements, legislative and budget actionsIntergovernmental—State For vehicle in lieu fees, similar to factors that affect property and sales taxes; availability

of state grants and reimbursements, legislative and budget actionsLicenses & Permits Similar factors as property and sales taxesFines & Forfeitures Fines and penalty rates; similar to factors that affect property and sales taxesCharges for Service Similar to factors that affect taxes, cost of providing services, and rate schedule for cost recovery

Exhibit 2: Baseline Assumption


method relies on simple trend analysisand requires alternative scenarios tomeasure the broadest range of proba-ble outcomes.For example,a forecast offines and forfeitures might be based onhistorical trends but modified toaccount for expected inflation —assuming fines are adjusted accordingto the Consumer Price Index (CPI) —and population growth.

An organization should develop alter-native favorable and unfavorable (orbest- and worst-case) scenarios in away that represents the broadest rangeof possible forecast outcomes. The pri-mary purpose for creating alternativescenarios is to support sensitivity analy-sis,which attempts to identify what areaof uncertainty makes the most differ-ence in the forecast. Sensitivity analysis

allows for “what-if” testing of variousassumptions and outcomes, and theirlikely impact on the organization’sfinances. Quantifying unfavorable sce-narios, in particular, allows a local gov-ernment or agency to make contin-gency plans that can be implementedearlier and more thoughtfully than thereactionary measures that would likelybe put in place after the day of revenue-shortfall reckoning occurs.

Deterministic and econometric fore-casts are based on one or more corre-lated underlying factors that directlyaffect revenues and, to a lesser case,expenditures. For instance, changes inassessed property values and millagerates, or the amount per $1,000 that isused to calculate property taxes, willdirectly affect property tax revenues.

Commercial and residential develop-ment, along with local economic con-ditions, will affect permit and planningfees, franchise income, and sales taxes.These forecast techniques require notonly availability of historical data butan understanding of the relationshipamong myriad variables such as popu-lation, inflation, local economic activity,tax rates, consumption patterns andconsumer trends, property values, con-struction activity, and so on. Exhibit 1shows examples of key revenue typesand associated forecasting factors.

PREPARING THE BASELINE FORECAST

The first step in establishing the base-line forecast for a recurring revenuetype is to collect historical data for

Exhibit 3:Trend Analysis

trend analysis. While historical trendsare not necessarily predictive, they doestablish a base for future projections.In Exhibit 2, historic sales tax receiptsfor the fictional city of Springfield arebroken out by business category, allow-ing for greater insight into revenuesources and trends. In this case, whileoverall sales tax receipts are on a down-ward trend, certain components suchas service stations and food stores con-tinue to show positive growth.

TREND AND CORRELATIONANALYSIS

Once historical data have been gath-ered, they can be further analyzed byusing trend and correlation analysis. Intrend analysis,metrics such as per capi-ta, percentage of annual growth, and

percentage of total revenue indices pro-vide further understanding of realgrowth rates and help identify recurringand non-recurring elements that can befactored into the forecast. (See Exhibit3 for a per capital trend analysis.)Correlation analysis can be used to ana-lyze relationships among major rev-enue sources such as property andsales taxes, in comparison with residen-tial and commercial development, eco-nomic cycles, population growth, infla-tion, and so forth (see Exhibit 4).

In Exhibit 3, Springfield’s sales tax revenues are illustrated in nominal andper capita values. Once per capitatrends are established, those numberscan then be compared with inflation toprovide a clearer understanding of realgrowth versus nominal growth rates, as

shown in Exhibit 4. Both examples arebased on the sales tax revenue datafrom Exhibit 2.The correlation analysisshows that while Springfield’s receiptsare relatively flat between fiscal 2007and 2008, they in fact are falling whencompared with CPI inflation growth forthe same period.

ALTERNATIVE SCENARIOS

Once the baseline forecast is estab-lished, alternative scenarios can be pre-pared that depict favorable and unfavor-able variations on the baseline scenario.The degree to which the baseline andalternative scenario differ will dependon how much the revenue type tends tovary, historically, and the organization’sdegree of confidence that the baselineforecast is accurate. As variability


Exhibit 4: Correlation Analysis


Exhibit 5: Sensitivity Analysis, Baseline Scenario

Exhibit 6: Sensitivity Analysis, Unfavorable Scenario

increases, and as confidence decreases,the distance between baseline and alter-native positive and negative scenariosshould increase to capture the full rangeof probable outcomes.

The baseline scenario shown inExhibit 5 illustrates a positive gapbetween revenues and expenditures,resulting in an increasing fund balanceover time. This scenario was construct-ed using an interactive forecastingmodel, which allows various assump-tions and budget options to be activat-ed, instantaneously demonstrating posi-tive or negative impacts on projectedfund balances, as shown in Exhibit 6.

In the interactive forecasting modelillustrated in this article, the projectedfund balance is used as a proxy for theorganization’s financial health and sol-

vency. Organizations also need to ana-lyze historical trends in their fund bal-ances, using measures such as unre-served fund balance as a percentage ofannual appropriations, and comparehistorical and projected balances withthe organization’s minimum policyrequirements.The unreserved fund bal-ance,or fund balance available,is a crit-ical benchmark for evaluating an orga-nization’s ability to meet unexpectedfunding shortfalls and is often used asone way of measuring solvency.

EXPENDITURE FORECASTING

Expenditure forecasting is similar torevenue forecasting.To create the base-line expenditure forecast, first identifyrecurring expense types, and then ana-lyze historical trends for expendituresthat are related to labor and those that

are not. Common expense typesinclude: salaries and wages, employeebenefits, materials and supplies, profes-sional and contract services,minor cap-ital (office equipment),capital projects,debt, and other operating expenses.

The baseline forecast should bebased on existing and recurring stafflevels, operating expenditures, andother expenses the government oragency has already committed to,including capital programs, debt, andcontractual commitments such asemployee compensation and benefits.The latter example illustrates the needfor longer-term forecasting to measurefuture impact, as employee retirementand health-care benefits are the fastest-growing components of most govern-ment budgets.


Exhibit 7: Expenditure Forecast, Restrained Spending Scenario


Alternative expenditure forecasts canreflect spending levels that mirrorpotential increased department mis-sions (i.e.,“augmented”scenarios basedon what departments might spend ifadditional resources were available).They can also reflect restrained or con-tingent spending plans that could beimplemented in response to reducedresources. Exhibit 7 shows the way arestrained spending plan improves theimpact on fund balance from the unfa-vorable revenue scenario from Exhibit6.This forecast model can also factor initemized spending options, in additionto or in place of an organization-wideexpenditure scenario.

CONCLUSION

Long-term financial forecasts are notabsolute predictions of the future, butprojections of possible future statesbased on known assumptions.The bestforecasts are based on a solid under-standing of historical trends combinedwith a range of future scenarios derivedfrom a detailed analysis of known fac-tors that can affect revenues and spend-ing. Longer forecasting horizons canreveal structural imbalances that arenot yet apparent,giving an organizationtime to take corrective action in aproactive way, thus optimizing the useof public funds over the long term.Interactive forecasting models not only

help organizations analyze trends andidentify possible future financial states,but they also help communicate finan-cial issues to key constituents. ❙

CHRISTOPHER J. SWANSON is the founderof Government Finance Research Group(GFRG), a financial management consultingfirm specializing in financial planning, costanalysis, econometric modeling, benchmark-ing, and optimization modeling for local gov-ernments throughout the United States.GFRG designed and developed theMuniCast interactive financial forecastingmodel. Swanson can be contacted at 949-412-6078 or [email protected].

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Long-Term Financial Forecasting for Local Governments

Economy & Finance