CEA Economic Forecasting Techniques 4

Question 1

The Hodrick-Prescott (HP) filter is commonly applied in macroeconomic forecasting to:

Accepted Answer

Separate a time series into trend and cyclical components

Answer

The HP filter minimizes deviations from a smooth trend, weighted by a smoothing parameter λ, to extract the business cycle component.

Question 2

Dynamic Factor Models (DFMs) are advantageous for macroeconomic forecasting primarily because they:

Accepted Answer

Extract a small number of common factors from a large dataset of economic indicators

Answer

DFMs reduce hundreds of economic series to a handful of latent factors, efficiently summarizing co-movement and improving forecast accuracy.

Question 3

In a GARCH(1,1) model applied to economic forecasting, what does the model primarily capture?

Accepted Answer

Time-varying volatility clustering in financial or economic time series

Answer

GARCH models capture the empirical regularity that large shocks to an economic series tend to be followed by further large shocks (volatility clustering).

Question 4

Which evaluation metric is most appropriate when forecast errors are heteroskedastic and large outliers should not be penalized excessively?

Accepted Answer

Mean Absolute Error (MAE)

Answer

MAE weights all errors equally regardless of size, making it more robust to outliers than RMSE, which squares errors and amplifies large deviations.

Question 5

An economic forecaster notices that residuals from a regression model are positively autocorrelated. The most appropriate corrective action is to:

Accepted Answer

Add lagged dependent or independent variables to capture omitted dynamics

Answer

Positive serial correlation in residuals typically signals missing lag structure; adding lags removes the autocorrelation and improves forecast accuracy.

(CEA) Certified Economic Analyst Practice Test

(CEA) Certified Economic Analyst Practice Test

CEA Economic Forecasting Techniques 4