IMF Working Papers

What Are Empirical Monetary Policy Shocks? Estimating the Term Structure of Policy News

ByJonathan J. Adams, Philip Barrett

June 27, 2025

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Format: Chicago

Jonathan J. Adams, and Philip Barrett. "What Are Empirical Monetary Policy Shocks? Estimating the Term Structure of Policy News", IMF Working Papers 2025, 128 (2025), accessed 12/7/2025, https://doi.org/10.5089/9798229015233.001

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Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

Empirical monetary policy shocks (EMPS) contain information about monetary policy both today and in the future. We define the term structure of monetary policy news as the marginal impact of an EMPS on the policy residual at each horizon. Policy news at different horizons has different effects, so knowing the term structure is necessary in order to use an EMPS to evaluate theory. We develop an IV method to estimate this term structure. We find that EMPS in the literature do not represent textbook policy surprises. Instead, they represent a mix of information about policy at many horizons, and this mix varies depending on how the EMPS is identified. We use the estimated term structures to construct synthetic forward guidance and surprise shocks, and estimate their macroeconomic effects. Surprise interest rate hikes are contractionary with little effect on prices, while long-term forward guidance is deflationary.

Subject: Econometric analysis, Economic theory, Estimation techniques, Financial institutions, Futures, Inflation, Neoclassical theory, Prices, Vector autoregression

Keywords: Estimation techniques, Forward Guidance, Futures, Inflation, monetary policy news, monetary policy shock, Monetary Policy Shocks, Neoclassical theory, Policy news, surprise interest rate hike, Term Structure, textbook policy surprise, Vector autoregression