This document discusses various budgeting techniques and analytical models for forecasting revenues and making financial decisions. It identifies key factors to consider when forecasting revenues, such as focusing on large revenue sources and historical data. It then compares and contrasts different forecasting models, including status quo, extrapolation, multiple regression, judgmental, Delphi, time-series, and econometric models. Finally, it outlines several financial decision making tools like cost-benefit analysis, cost effectiveness analysis, discounting, rate of return, payback method, breakeven analysis, productivity analysis, and multiple regression analysis.

1. Budgeting Techniques and
Analytical Models
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Chapter 6

2. CHAPTER 6 LEARNING OBJECTIVES
After studying the material in this chapter students will:
• identify key factors to consider when forecasting revenues
• compare and contrast forecasting models
• Status Quo
• Extrapolation
• Judgmental
• Delphi
• Time-Series
• Multiple Regression
• Econometric
• compute cost-benefit and cost effectiveness analysis
• debate the value of various financial decision making tools
• Discounting
• Lease/purchase
• Rate of return
• Payback method
• Breakeven analysis
• Productivity analysis
• Multiple regression analysis

3. Key Factors to Consider When Forecasting
Revenues
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 Revenue should be projected separately- Each
revenue source is distinct and has its own set of
nuances.
 Focus efforts on the large revenue sources- like
property taxes, small revenue sources do not have a
great impact on the budget.
 Historical data is the key to success-Revenue
projections do not tend to change dramatically over
time. As a result, data and financial records should be
closely examined. Once this data is examined,
projections can be made after adjustments are made for
other factors in the environment such as demographic
shifts and economic development. Further, it is
important that the analyst pay attention to items that
may not reoccur. For example, the government may
receive a grant for five years that is not renewable.

4.  Underestimate rather than overestimate budgets-
Although budgets are based on solid economic factors, the
ramification of budget deficits can be very political in nature.
State and local elected officials do not want to explain
budget deficits to voters because the repercussions could
be felt in the next election cycle. Therefore, estimates should
be somewhat conservative.
 Good Judgment-While a state or local government’s tax
base may seem stable, it is important that estimators keep
an eye on other nearby jurisdictions that may have an
impact on their revenue estimates. Further, estimators may
receive estimates from other sources that are not inline with
their estimates.
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5. Types of Forecasts
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 Status Quo Model: This model assumes that the future will look
a lot like the present and works well in stable governments.
The major advantage of the model is that it is simple and easy to
administer. The major disadvantage is that any shift in economic
conditions will compromise the validity of the model.
 Extrapolation Model: This model uses current trends (time-
series data) in revenue and expenditures to explain future
revenue and expenditure trends. Extrapolations can use
constant increments, constant percentage changes, simple
growth models using the average annual compounding formula,
or linear or nonlinear time trends in which revenue for the budget
year is estimated as an arithmetic function of time (R=a + bt).
For example, if property tax receipts have increased an average
of 2% over the last five years, the model would assume that they
would increase 2% during the forecasted year as well.

6.  Multiple Regression Model: A regression model is a more
complex time series model that estimates revenue using several
independent variables such as the unemployment rate and income
levels. The advantage of this model is that it is relatively simple to
estimate each revenue source separately.
 Judgmental Model: Relies on the experience of subject experts.
 Delphi Model: Experts discuss forecasts with a moderator; each
participant is asked the same question. This method allows for the
views of the minority to be heard with the goal as consensus.
 Time Series Model: Goal is to break down the budget into four
components 1) long term trend, 2) seasonal variation, 3) cyclical
variation, and 4) irregular variation
 Econometric Models: Measures past relationships among
variables as consumer spending, household income, tax
rates, interest rates, employment, and uses those variables to
forecast how changes in some variables will affect the future
course of others. 6

7. Financial Decision Making Tools
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 Cost Benefit Analysis: Compares the cost to the benefit of the
program
 Cost Effectiveness Analysis: Assumes there are benefits and
concentrates on spending the least amount of funds to achieve the
objective.
 Discounting to Present Value: Considers the value of the dollar
today relative to some other period in time.
 Rate of Return: Technique solves for the profit on the investment.
 Payback Method: Examines the time needed to recover the
investment.
 Breakeven Analysis: The point at which the revenue equals the
expenses of the project.
 Productivity Analysis: Measures input to output
 Multiple Regression Analysis: Predicting income by manipulating
variables