Revenue Forecasts, Revenue Estimates, and Tax Expenditure Budgets

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Revenue Forecasts,Revenue Estimates, andTax
Expenditure Budgets

• Troy University
• PA6650- Governmental Budgeting
• Chapter 13

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Three Revenue Prediction Tasks

• Revenue Forecast (or baseline)
• Revenue Estimates (or fiscal notes or scores)
• Tax Expenditures

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Revenue Forecast (baseline)

• Forecast of what revenue will be collected in the
  budget period under the current las
• Office of Tax Analysis in the Department of the
  Treasury (for OMB)
• Congressional Budget Office (for Congress)
• Forecasts can be very objective or very
  subjective depending on technique

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Revenue Forecast (baseline)

• Forecaster should understand the tax, how it is
  administered, and collection procedures
• Should be plotted on a graph against time
• Openness is a virtue
• Approach depends on the task to be served
• Individual revenue sources should be forecast
  separately
• Revenues need to be monitored and checked against
  the forecast

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Revenue Forecast (baseline)

• Different Approaches
• Extrapolation or projections
• Simple, low cost, moving average
• Deterministic modeling
• Multiple Regression
• dependent/independent multiple variables
• Econometric Models
• Set of interdependent equations
• Microdata models
• Small sample from taxpayer data files

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Revenue Forecast (baseline)

• UNIVARIATE PROJECTIONS AND EXTRAPOLATIONS
• Simple plotting
• Moving average
• Other more sophisticated techniques

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Revenue Forecast (baseline)

• DETERMINISTIC MODELING
• Pre-established formula (rule of thumb)
• e.g., link between GDP and personal income tax or
  VAT to GDP
• One variable may help predict the other

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Revenue Forecast (baseline)

• MULTIPLE REGRESSION
• Y is the dependent variable
• Y aX1 bX2 cX3 .
• Sales tax, personal income tax, inflation rate,
  unemployment rate, etc
• Least squares to find a regression line

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Revenue Forecast (baseline)

• ECONOMETRIC MODELS
• Simultaneous system of interdependent equations
• e.g., State income tax and sales tax deductions
• Multiple equations
• Sophisticated

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Revenue Forecast (baseline)

• MICRODATA MODELS
• Taken from a sample of taxpayers
• 10-year baseline of tax records
• Must be careful of tax and policy changes

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Choosing the Method

• Resources available
• Materiality of the forecast
• Availability of historic revenue data
• Availability and probable quality of causal data
• Time period of the forecast
• Explainability of the forecast
• Format
• A look back, the future environment, the
  approach, the forecast

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Forecasts for the Long Term

• Why?
• To guide a city on a major infrastructure program
• To show a credit rating agency long term health
• To let planners know implications of a specific
  project
• To inform the public when on the brink of a
  financial disaster
• To educate the legislature on pending legislation
• Medium term forecasts are 3-5 outyears
• Wrong forecasts sometimes happen

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Revenue Estimating

• Aka scoring (US) and tax costing (UK)
• Difference between receipts under current law and
  receipts under a proposed change in the law (what
  will the fiscal impact be?)
• Static component
• Taxpayers that will not behave differently
• Dynamic component
• Macro- and microeconomic analysis of behavioral
  change when tax law changes

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Tax Expenditure Budgets

• Revenue losses attributable to provisions of the
  federal tax laws which allow a special exclusion,
  exemption, or deduction from gross income or
  which provide a special credit, a preferential
  rate of tax, or a deferral of tax liability
• Compares a normal state with no exclusions to how
  much you are losing from exclusions
• Benchmark and deviations from the norm
• Page 534 Table 13-2

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Conclusion

• Revenue prediction has 3 divisions
• Forecasting collections in future years
• Estimating the impact of proposed changes in tax
  laws
• Calculating revenues currently sacrificed by
  existing tax law
• Mixture of art and science