similar to: Standard Error for Cointegration Results

Displaying 20 results from an estimated 700 matches similar to: "Standard Error for Cointegration Results"

2009 Sep 02
0
Cointegration/urca package
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 
2011 Jan 13
2
standard errors in johansen test
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
2012 Aug 10
1
Interper output from cajorls and VECM
Hi all R users, I'm finding it a bit hard to interpret the output from the cajorls and VECM function. I'm trying to model a VECM model with cointegration rank of 6, and therefore I get the varibles ECT1, ECT2... ECT6 in my output. Are these representing the estimates for my loading matrix or also denoted the "alpha" matrix? Thanks in advanced Emil -- View this message in
2011 Apr 29
1
question of VECM restricted regression
Dear Colleague I am trying to figure out how to use R to do OLS restricted VECM regression. However, there are some notation I cannot understand. Please tell me what is 'ect', 'sd' and 'LRM.dl1 in the following practice: #OLS retricted VECM regression data(denmark) sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")] sjd.vecm<-
2008 Mar 20
1
Cointegration no constant
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
2011 Nov 06
1
VAR and VECM in multivariate time series
Hello to everyone! I am working on my final year project about multivariate time series. There are three variables in the multivariate time series model. I have a few questions: 1. I used acf and pacf plot and find my variables are nonstationary. But in adf.test() and pp.test(), the data are stationary. why? 2.I use VAR to get a model. y is the matrix of data set and I have made a once
2012 Jan 15
0
A question about cointegration - How can we find the standard deviation in the cointegration relationship ?
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
2005 Nov 19
3
cointegration rank
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
2006 Jun 29
1
Cointegration Test in R
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
2007 Jun 02
0
Question regarding Johansen's cointegration testing
Hi, I have a couple of questions about johansen's test, in general: 1. I was able to obtain error correction term (ect) from cajorls$rlm$model properly. According the my ca.jo object on 2-variate series, the test suggests that the integration rank is 1. Which means that my ect should be stationary. However, I did test stationariy on ect and it shows non-stationarity and my acf still shows
2007 Jul 09
1
ca.jo
Dear R users; I'm using ca.jo for a VECM model. Is there a way that I can get sd/p-value to see whether coefficients estimated are statistical significant? Thank you Yours, Yihsu [[alternative HTML version deleted]]
2005 Dec 20
0
Help with ca.jo and cajools (Johansen's Cointegration)
I am trying to run a conintegration analysis. I am a former user of S-Plus and understand the output of the coint and VECM output, but I am having trouble understanding the equivalent output in R. Here is what I ran > coint=ca.jo(data,constant=T,K=2,spec="longrun") > summary(coint) The first portion of the output that I did not understand [,1] [,2] [,3] y1
2004 Mar 25
1
S+Finmetrics cointegration functions
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
2009 Oct 08
2
Determine restricted variable in SVAR and SVEC?
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]]
2009 Jul 26
0
Version 0.7 of package tsDyn, nonlinear time series
Hi Version 0.7 of package tsDyn presented at useR! 2009 is now on CRAN, extended with several new features. The package tsDyn is aimed at estimating nonlinear time series models which exhibit regime specific properties. The regime switching dynamics can either be described by smooth transition (STAR and LSTAR) or threshold effects (SETAR). The package furthermore offers nonlinear models
2009 Jul 26
0
Version 0.7 of package tsDyn, nonlinear time series
Hi Version 0.7 of package tsDyn presented at useR! 2009 is now on CRAN, extended with several new features. The package tsDyn is aimed at estimating nonlinear time series models which exhibit regime specific properties. The regime switching dynamics can either be described by smooth transition (STAR and LSTAR) or threshold effects (SETAR). The package furthermore offers nonlinear models
2012 May 03
0
MLE for estimating the parameters of the TVECM in R
Dear Mr. Matthieu Stigler i so excited for your package 'tsDyn'. firstly introduce myself, i student at Gadjah Mada University,Indonesia. i'am new user of R and applying it for solving Bi-Variate ( interest rate and inflation ) with threshold vector error correction model. now, i writing my final examination about threshold vector error correction model and i use refference from paper
2004 Mar 26
0
Package update: 'urca' version 0.3-3
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,
2012 Aug 21
1
Trace values in the function ca.jo()
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()
2012 Mar 07
1
VECM simulation
Dear members, I estimated a vector error correction model (VECM) using the "ca.jo" function in package "urca". I need to simulate the estimated model using R. I am aware how to simulate a VAR(p) model. Since the VECM is in difference form, I can't modify the VAR simulation codes to VECM. May one help me in this regard please? Thanks Mamush [[alternative HTML version