FEDERAL RESERVE BANK OF ST. LOUIS: Does Money Supply Really Predict Inflation? (Explained)

This episode dives into a Federal Reserve Bank of St. Louis research paper asking a crucial question: Do monetary aggregates actually help forecast inflation? We break down the paper's novel approach using neural networks and kernel regression to evaluate money's predictive power for US inflation in the early 2000s, explaining the findings in plain English. For more details, find the original paper at https://fedinprint.org/item/fedlwp/10440/original, and we welcome your feedback and discussion at [email protected]. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Does Money Matter in Inflation Forecasting? - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2009.030 Keywords: Inflation, Money Supply, Forecasting, Macroeconomics, Central Banking, Neural Networks