similar to: Cointegration and ECM in Package {urca}

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

Dear R-list member, an update of package 'urca' has been uploaded to CRAN (Mirror: Austria). In the updated release unit root and cointegration tests encountered in applied econometric analysis are implemented. The package is written in 'pure' R and utilises S4 classes. In particular, the Johansen procedure with likelihood ratio tests for the inclusion of a linear trend,

Hello!   I estimate vector error correction model (vecm) model. I have only one cointegratio relationship. I write :   joh.vecm.rls <- cajorls(joh.vecm, r=1) The output estimation is : Call: lm(formula = substitute(form1), data = data.mat) Coefficients:                up.d            expl.d        upd.d           r.d      ect1      -1.34e-01   4.55e+02   6.91e+00   2.43e+03 constant 

Hello, I tried to use urca package (R) for cointegration analysis. The data matrix to be investigated for cointegration contains 8 columns (variables). Both procedures, Phillips & Ouliaris test and Johansen's procedures give errors ("error in evaluating the argument 'object' in selecting a method for function 'summary'" respectiv "too many variables,

Hi - i am looking for a package with which I can perform panel cointegration tests. Old threads suggest plm and urca package, but I don't find suitable tests in these packs. Somebody knows more? best regards, Philipp -- View this message in context: http://r.789695.n4.nabble.com/panel-cointegration-tp4593443p4593443.html Sent from the R help mailing list archive at Nabble.com.

Dear folk, I am stempting to estimate a vector error correction model using a seemingly fractionally integrated multivariate time series. The *fracdiff *package provides tools to estimate degree of fractional integration. But *fracdiff *can't help me to: 1. test equality of two degrees of fractional integration, say d1=d2? 2. estimate a multivariate cointegrating error correction model,

Dear R - helpers, I am using the urca package to estimate cointegration relations, and I would be really grateful if somebody could help me with this questions: After estimating the unrestriced VAR with "ca.jo" I would like to impose the rank restriction (for example rank = 1) and then obtain the restricted estimate of PI to be utilized to estimate the VECM model. Is it possible? It

Hi, Could someone please tell me the R codes for fitting VAR(p) (Vector Auto Regressive) models and doing the Johansen?s cointegration tests. TIA Aditya

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 #

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

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

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

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

Hi, I can plot the ca.jo package to view the cointegrated relationship for each eigen value. Or I can use the normalized eigen vector to reconstruct the cointegrated relationship series. However, since the package can plot that for me, I wonder is there any specific slot/method in the class from where I can invoke to get this relationship instead of doing a duplicated work? Thank you. - adschai

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Hi, I am trying to estimate a VECM without constant using the following code: data(finland) sjf <- finland sjf.reg<-ca.jo(sjf, type = c("eigen"), ecdet = c("none"), K = 2,spec=c("transitory"), season = NULL, dumvar = NULL) cajools(sjf.reg) While the cointegration test does not use a constant, it is used in the cajools which I do not want. I am sure I am

Dear R users, I have the joined txt file in the following direct directory C:// I have written the following lines: library(urca); PIBTUN<-read.table("C:/AF.txt", header=F); ur.df(PIBTUN,type='none',lags=1) but I have obtained the following message: Error in embed(z, lags) : 'x' is not a vector or matrix I don't What's the problem, can you please help me Thank

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,

Hi all R users, I'm trying to replicate the same results that are given in a published article after been granted the same data that the authors use. I'm having problems to determine the cointegration rank of my data set using the Johnasen's trace test. This trace test is already programmed in the package ur.ca and can be found in the function ca.jo(). After I run the ca.jo()

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