Impulse Response Functions
Impulse Response Functions
Read the VOX article "Pushing on a String: U.S. Monetary Policy is Less Powerful During Recessions," by Sylvana Tenreyro and Gregory Thwaites, which can be found here: http://voxeu(dot)org/article/monetary-policy-weaker-recessions
This article's main exhibits are impulse response functions. These IRFs are obtained using VARs, but you already have a sense of IRFs in the univariate context from this Lesson's lecture notes, so you can definitely assess the broad takeaways of the article and why the authors may be using IRFs.
To get the ball rolling, start by commenting on the following: How persuasive do you find the use of IRFs? Are IRFs the best way to make the authors' points or would you argue for another way, be it complementary or entirely different? "Getting the ball rolling" is a guide for the first several posters.
Impulse Response Functions
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In forecasting variables and signal processing, the impulse response function refers to the reaction produced by a dynamic system as it responds to the external disturbance. Normally, both univariate and multivariate models, especially the time series models, are usually significantly hard to interpret. To interpret them, they are subjected to forecasting of their variables. The most persuasive method of forecasting is the use of the impulse response function. Forecasting refers to the prior estimation of variable data of a particular series. Forecasting is commonly used in time-series data. In this sense, we can define impulse response function as a forecast for the evolution of the variable that's assumed to be shocked in a period and not disturbed forever after.
The impulse response function is not only persuasive but als...