Revenue Forecasts,Revenue Estimates, andTax Expenditure Budgets

Troy University

PA6650- Governmental Budgeting

Chapter 13

Three Revenue Prediction Tasks

• Revenue Forecast (or baseline)

• Revenue Estimates (or fiscal notes or scores)

• Tax Expenditures

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

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

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

Revenue Forecast (baseline)• UNIVARIATE PROJECTIONS AND

EXTRAPOLATIONS– Simple plotting– Moving average– Other more sophisticated techniques

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

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

Revenue Forecast (baseline)• ECONOMETRIC MODELS

– Simultaneous system of interdependent equations

• e.g., State income tax and sales tax deductions• Multiple equations• Sophisticated

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

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

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

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

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

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