Transmission Channel Analysis in Dynamic Models

TL;DR

This paper introduces Transmission Channel Analysis (TCA), a framework that decomposes effects in dynamic models into transmission channels using graph theory and potential outcomes, aiding policy evaluation.

Contribution

The paper develops a novel TCA framework that decomposes effects into channels without extra assumptions, linking graph theory and potential outcomes.

Findings

TCA effectively decomposes policy shock effects into channels.

Impulse response functions are sufficient for transmission effect computation.

Empirical application demonstrates TCA's policy evaluation utility.

Abstract

We propose a framework for analysing transmission channels in a large class of dynamic models. 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 through transmission channels, thereby providing a quantitative assessment of the strength of various well-defined 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 demonstrate the empirical relevance of TCA for policy evaluation by decomposing the effects of policy shocks arising from a variety of popular macroeconomic models.