Forecasting & Revenue Estimation Flashcards
7 cards from real CBA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Forecasting & Revenue Estimation flashcards as text
Which forecasting method uses historical data patterns and trends to project future revenues without relying on causal relationships?
Answer: Time series analysis
Time series analysis extracts patterns such as trends, seasonality, and cycles from historical data to project future values without modeling causal factors.
A budget analyst is preparing a five-year revenue forecast and wants to account for the relationship between GDP growth and tax receipts. Which technique is most appropriate?
Answer: Econometric regression
Econometric regression models quantify the statistical relationship between economic indicators like GDP and dependent variables such as tax receipts.
When using exponential smoothing for revenue forecasting, a smoothing factor (α) closer to 1.0 will:
Answer: Give more weight to recent observations
A smoothing factor near 1.0 places nearly all weight on the most recent observation, making the forecast highly responsive to recent changes.
Which of the following best describes a consensus-based qualitative forecasting method that iterates anonymous expert opinions until convergence?
Answer: Delphi method
The Delphi method gathers anonymous expert judgments in successive rounds, sharing summarized results each round until the group reaches consensus.
A revenue estimate based on the assumption that current policy and economic conditions remain unchanged is called a:
Answer: Current services baseline
A current services baseline projects revenues and expenditures assuming existing laws, regulations, and economic conditions continue without change.
Which measure best quantifies the average absolute difference between forecasted and actual revenue values, expressed in the same units as the data?
Answer: Mean Absolute Error (MAE)
Mean Absolute Error (MAE) averages the absolute differences between forecasted and actual values, keeping units identical to the original data.
Seasonal adjustment in revenue forecasting is used primarily to:
Answer: Isolate and remove recurring periodic fluctuations
Seasonal adjustment removes recurring periodic fluctuations (e.g., higher tax receipts in April) so that underlying trends and cycles can be analyzed more clearly.