CEA Economic Forecasting Techniques 5

Question 1

Bayesian Model Averaging (BMA) addresses model uncertainty in forecasting by:

Accepted Answer

Weighting forecasts from all candidate models by their posterior model probabilities

Answer

BMA integrates over model uncertainty by combining forecasts weighted by each model's posterior probability, accounting for the fact that the true model is unknown.

Question 2

In long-horizon economic forecasting, which method is generally preferred over ARIMA models?

Accepted Answer

Structural economic models anchored by long-run theory

Answer

At long horizons, theoretical anchors (e.g., purchasing power parity, potential output) matter more than statistical time-series properties, favoring structural models.

Question 3

The concept of 'cointegration' is important in economic forecasting because cointegrated variables:

Accepted Answer

Share a long-run equilibrium relationship that constrains their joint dynamics

Answer

Cointegrated series are individually non-stationary but have a stationary linear combination, which is exploited in Error Correction Models (ECMs) to improve forecasts.

Question 4

Which of the following best describes 'judgmental adjustment' in economic forecasting?

Accepted Answer

Expert modification of model-based forecasts using information not captured by the model

Answer

Judgmental adjustment incorporates soft information (e.g., anticipated policy changes, geopolitical events) that statistical models cannot capture, improving real-world forecast accuracy.

Question 5

In the context of real-time forecasting, 'data vintage' refers to:

Accepted Answer

The specific release of a data series available at a given point in time

Answer

Different vintages of GDP, for example, reflect successive revisions; using the correct vintage is essential for realistic out-of-sample forecast evaluation.

(CEA) Certified Economic Analyst Practice Test

(CEA) Certified Economic Analyst Practice Test

CEA Economic Forecasting Techniques 5