similar to: Constraining coefficients to be equal in svar

Hello! I'm doing a svar and when I make the estimation the next error message appears: In SVAR(x, Amat = amat, Bmat = bmat, start = NULL, max.iter = 1000, : The AB-model is just identified. No test possible. Could you help me to interpret it please. Also I have the identification assumption that one of my shocks is exogenous relative to the contemporaneous values of the other variables

Hello, I'd like to simulate data according to an SVAR model in order to demonstrate how other techniques (such as arima) yield biased estimates. I am interested in a 2 variable SVAR with 2 lags (in the notation of the vars vignette, K = 2, P = 2, where B = I_K). I'm using the {vars} package outlined here: http://cran.r-project.org/web/packages/vars/vignettes/vars.pdf I thought that the

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 #

How to determine restricted variable in SVAR and SVEC? There are some values which set to be zero and others set to be NA.. How to determine values that set to be 0? Thanks Regards, Arif _________________________________________________________________ Facebook. k-basics.aspx?ocid=PID23461::T:WLMTAGL:ON:WL:en-id:SI_SB_2:092009 [[alternative HTML version deleted]]

Dear Sir/Madam, I have used ca.jo in urca package to identify the cointegration and cajorls to estimate the vecm. Althought both return the coefficients for long run relationship (or ect1 in cajorls), I am unable to find the standard error and t statistics. I spend some weeks to search around. I did find some similar enquiries before and answer provided Prof. Pfaff is to use vec2var. However,

Folks, What is the best way to simulate values from a fitted "VAR {vars}" model. Also I have tried to use SVAR for a cointegration fit of y~x (just two univariate time-series) but I can't figure out how to set up the "A" matrix so that x_t can be used as a contemporaneous predictor of y_t. Thanks much for your time, KW -- [[alternative HTML version deleted]]

Hello! I'm using the blrtest() function in the urca package to test cointegration relationships. Unfortunately, the hypothesis (restrictions on beta) specifies the same restriction on all cointegration vectors. Is there any possibility to specify different restrictions on the cointegration vectors? Are there any other packages in R using cointegration tests? Thanks and best regards. Dennis

Whether can any R package run Full modified OLS (Phillips and Hansen 1990 ), DOLS (Stock and Watson 1993) and ADL model (Pesaran and Shin 2001) for cointegrated VAR model? I cannot find any useful order in VAR and SVAR package. Thanks. Eric Wang [[alternative HTML version deleted]]

Hi, I would like to estimate a VAR of the form: Ay_t = By_t-1 + Cy_t-2 + ... + Dx_t + e_t Where A is a non-diagonal matrix of coefficients, B and C are matricies of coefficients and D is a matrix of coefficients for the exogenous variables. I don't think the package {vars} can do this because I want to include contemporaneous cross-variable impacts. So I want y1_t to affect y2_t and I

Dear all, I have a question. How to get the standard errors of alpha and beta when using "ca.jo" to test cointergration? In the paper by Bernhard Pfaff and Kronberg im Taunus “VAR, SVAR and SVEC Models: Implementation Within R Package” pp.24-25. The standard errors are listed on the table 5 following the code: R> vecm.r1 <- cajorls(vecm, r = 1) I tried this in my Mac R, but

Dear R Core Team, I am using package {urca} to do cointegration and estimate ECM model, but I have the following two problems: (1) I use ca.jo() to do cointegration first and can get the cointegration rank, alpha and beta. The next step is to test some restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest(). But none of them can add restrictions on all the cointegration

Hello, Is there a way to get a single TRUE or FALSE statement from comparing two vectors? For example, c(1,2,3) == c(1,2,3) produces TRUE TRUE TRUE where I would like it to produce only TRUE for use in an if statement. Likewise, when two vectors are not exactly identical (in all elements) I would like a single FALSE result, as opposed to c(1,2,3) == c(1,2,5) TRUE TRUE FALSE Any ideas?

Hi R-users, I would like to ask question related to error output. If an error comments come out, then the program will automatically stop. I want to ask , how I can still continue the program even though there is an error comment? var=VAR(Canada,p=3,type="const") for (j in 1:nrow(com)) { mat=ma { for (i in 1:ncol(com)) { y=which(mat==com[j,i]) mat[y]=NA }

Hello, I am using urca package to run cointegration. I would like to find the standard error in the (normalized, Johansen) cointegration relationship. How can I do it? As far as I know, The function "cajorls" in the "urca" package provides the normalized cointegrating relationships. Nevertheless, it does not provide the standard deviation of the coefficient for each

Hello, I'm running a very long for loop that usually takes hours. For my own piece of mind, it would be nice if I could check periodically and see which iteration the loop is on. A line of code that told R to print the iteration number every 100 or 200 iterations would be perfect. Does anyone know something like this? I've never known how to print anything within a for loop before the

Hi, I am trying to test the cointegration among 5 time series, grouped in pairs. I would like to save in a table the cointegration vectors for the 10 tests. I used the urca package, but I dont know how to extract the data only for the cointegration vector. Thanks in advance for help ! Eduardo

Dear All, I am looking for a cointegration relationship between Spot and Future Price of commodites. The problem i am facing follows: 1. After estimating by Engle-Grranger Method, i found that the residuals are stationary at their level I (o), which is required to fulfill the cointegration test. But the autocorrelation problem arises, as DW statistics is signficantly low 0.50-0.88 for various

Hi all, I am looking for low cost online education in statistics. I am thinking of taking online classes on time series analysis and cointegration, etc. Of course, if there are free video lectures, that would be great. However I couldn't find any free video lectures at upper-undergraduate and graduate level which formally going through the whole timeseries education... That's why I would

I understand that Rcmdr needs the tcltk package in order to run. However, when I attempt to using the library (Rcmdr) command, I get the message below. I have attempted to start X in R as well as using starting it from the Utilities folder on my Mac to no avail. I can't figure out if there is an issue with X11 or with R itself (I just updated to 1Is there a terminal command I can use

I'm tring the functions to check the cointegration of a matrix. I'm using **Phillips & Ouliaris Cointegration Test** The function in *tseries* package is **po.test** and **ca.po** in *urca* The results with **URCA** are: > ca.po(prices, demean='none') ######################################## # Phillips and Ouliaris Unit Root Test #