Search found 358 matches
- Mon Feb 19, 2018 11:38 am
- Forum: Add-in Support
- Topic: Threshold Structural VAR
- Replies: 120
- Views: 40403
The add-in computes average IRF for response variable, conditional on being in the upper or lower regime. The identification is recursive. So order of variables is matter.
Code: Select all
vardecx=lam.@t*varf*lam ' variance in x's due to monetary shock
vardecxtot=lam.@t*varftot*lam ' variance in x's due to all commom factors
Hi Ben, am I right to suppose that your great add-in has this feature that it uses accumulated irfs for variables that are log-differentiated and otherwhise it uses the standard irfs? Yes, you are right. The units on the axes are standard deviation units or % units? standard deviation units because ...
1) the standard deviation I am referring is the standard deviation of FFR, not cholesky decomposition of VAR residual VCMatrix. For instance, you can estimate it by command of @stdevp(ffr) before variable transformation. 2) favar(factor=3,horizon=48,rep=1000,ci=0.9,save=1,vd=1, scale=1, sn=0.07816) ...
Hi Ben, The FAVAR add-in is updated. Now it includes an option to scale the IRF. Please update it. Is that no problem as long as the factors are stationary? Yes, it is no problem. Many researcher estimate VAR model in level variable (not first difference) even though variables are I(1). For example,...
The fed fund rate is observable factor. Other factors are unobservable. Therefore FFR should be compatible with other factors. For example, FFR is used with the factor rotation analysis. Even though FFR is I(1) variable, you cannot difference FFR. Because it is impulse variable. Shock to FFR should ...