chili
2014-Jun-19 17:21 UTC
[R] Restrict a SVAR A-Model on Matrix A and Variance-Covariance-Matrix
Hello folks! I'm using R-Package {vars} and I'm trying to estimate an A-Model. I have serious problems regarding the restrictions. 1) My A-Matrix needs (!) to have the following form: # 1 NA NA NA # 0 1 NA NA # 0 0 1 NA # 0 0 0 1 That is done in R by: A_Matrix <- diag(4) # main diagonal = 4 restrictions A_Matrix [1, 2] <- NA # A_Matrix [1, 3] <- NA # A_Matrix [1, 4] <- NA # A_Matrix [2, 3] <- NA # A_Matrix [2, 4] <- NA # A_Matrix [3, 4] <- NA # off diagonal = 6 restrictions 2) The Variance-Covariance-Matrix of the structural residuals needs (!) to be looking like: # # var(X1) 0 0 0 # 0 var(X2) 0 0 # 0 0 var(X3) 0 # 0 0 0 var(X4) Since cov(xy)=cov(yx) there are 6 more restrictions. So in total I would have 4+6+6=16 restrictions. The SVAR would be just identified. My problem is that I don't know how to implement this Variance-Covariance-Matrix within R and {vars}. My Code so far is: # Prediction SVAR - A-Model (B-Matrix = NULL) # restrictions: # 1) Amat = A_Matrix # 2) ???? VAR.est <- VAR(data.ts, p = 4, type = "none") SVAR.A.est <- SVAR(x=VAR.est, estmethod = "direct", Amat = A_Matrix , Bmat = NULL, hessian = TRUE, lrtest = TRUE) #-------------------------------------------------------------------- I know, that {vars} restrict the Variance-Covariance-Matrix by default to an identity-matrix but I wondered if I can't restrict it by myself since the way I need (!) to do that is quite common. Thank you for any comments. I'm quite desperate right now :/ -- View this message in context: http://r.789695.n4.nabble.com/Restrict-a-SVAR-A-Model-on-Matrix-A-and-Variance-Covariance-Matrix-tp4692387.html Sent from the R help mailing list archive at Nabble.com.
chili
2014-Jun-20 09:27 UTC
[R] {vars} SVAR A-Model: Restrictions on Matrix A and Variance-Covariance-Matrix
Thanks to Dennis Murphy I was able to improve mein R-Code: 1) A-Matrix: A_Matrix <- diag(4) # 4 restrictions A_Matrix[upper.tri(A_Matrix)] <- NA # 6 further restrictions 2) Variance-Covariance-Matrix Xmat <- cbind(X1, X2, X3, X4) vs <- apply(Xmat, 2, var) VC_Matrix<- diag(vs) # final 6 restricions That worked fine so far. Now, is there any chance to implement the VC_Matrix it into my SVAR-estimation? -- View this message in context: http://r.789695.n4.nabble.com/vars-SVAR-A-Model-Restrictions-on-Matrix-A-and-Variance-Covariance-Matrix-tp4692387p4692424.html Sent from the R help mailing list archive at Nabble.com.