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Abstract

We propose a framework for the analysis of transmission channels in a large class of dynamic models. To this end, we formulate our approach both using graph theory and potential outcomes, which we show to be equivalent. Our method, labelled Transmission Channel Analysis (TCA), allows for the decomposition of total effects captured by impulse response functions into the effects flowing along transmission channels, thereby providing a quantitative assessment of the strength of various transmission channels. We establish that this requires no additional identification assumptions beyond the identification of the structural shock whose effects the researcher wants to decompose. Additionally, we prove that impulse response functions are sufficient statistics for the computation of transmission effects. We also demonstrate the empirical relevance of TCA for policy evaluation by decomposing the effects of various monetary policy shock measures into instantaneous implementation effects and effects that likely relate to forward guidance.
Original languageEnglish
PublisherCornell University - arXiv
Number of pages53
DOIs
Publication statusPublished - 29 May 2024

Publication series

SeriesarXiv.org
Number2405.18987
ISSN2331-8422

JEL classifications

  • c32 - "Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models"
  • c54 - Quantitative Policy Modeling
  • e52 - Monetary Policy
  • e60 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook: General

Keywords

  • transmission channel
  • policy evaluation
  • impulse response function
  • structural vector autoregression
  • DSGE
  • macroeconomic shocks

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