FEDERAL RESERVE BANK OF ST. LOUIS: How Combining Recursive and Rolling Forecasts Boosts Accuracy (Explained)

This episode dives into a Federal Reserve Bank of St. Louis research paper that examines how to make economic forecasts more accurate, particularly in an environment of structural change. We break down how combining "recursive" (using all available data) and "rolling" (using only recent data) forecasting methods can significantly improve prediction quality. Learn about this innovative strategy and share your feedback at [email protected], or read the full paper at https://fedinprint.org/item/fedlwp/9611/original. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Improving Forecast Accuracy by Combining Recursive and Rolling - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2008.028 Keywords: forecasting, macroeconomics, structural change, central banking, model averaging, forecast accuracy