Replication Package for: Investor Learning about Monetary-Policy Transmission and the Stock Market

This replication package contains the data, code, and instructions to reproduce all results in the paper "Investor Learning about Monetary-Policy Transmission and the Stock Market" by Daniel Andrei and Michael Hasler, forthcoming in the Journal of Financial Economics.

Paper Abstract: We model how investor learning about monetary-policy transmission impacts asset prices. In an asset-pricing model, investors learn from realized inflation surprises how effectively monetary policy steers future inflation. Downward revisions in perceived effectiveness raise expected inflation persistence, increasing return volatility and risk premia. These effects intensify when policy deviates significantly from neutral or monetary-transmission uncertainty is high. We estimate the model using U.S. macro and policy data from 1954 to 2023. The resulting dynamics align with observed patterns in equity returns and volatility. Empirical tests support the model's core prediction: investor learning turns central-bank credibility into a priced risk factor.

This package contains all the data and code necessary to reproduce the figures and tables in the paper and its internet appendix. The data include U.S. macroeconomic time series (real GDP, CPI, Federal funds rate, output gap) from 1954 to 2023, sourced from FRED and NIPA, as well as financial market data. The code includes a Mathematica notebook for solving the theoretical model and other Matlab scripts for the maximum likelihood estimation and all empirical tests. A README file is included with detailed, step-by-step instructions for replication.