lttest {urca} | R Documentation |
Likelihood ratio test for no linear trend in VAR
Description
Conducts a likelihood ratio test for no inclusion of a linear trend in a
VAR. That is, the Null hypothesis is for not including a linear trend
and is assigned as 'H2*(r)'. The test statistic is distributed as
\chi^2
square with (p-r)
degrees of freedom.
Usage
lttest(z, r)
Arguments
z |
An object of class ‘ca.jo’. |
r |
The count of cointegrating relationships. |
Details
The count of cointegrating relations should be given as integer and
should be in the interval 1 \leq r < P
.
Value
lttest |
Matrix containing the value of the test statistic and its p-value. |
Author(s)
Bernhard Pfaff
References
Johansen, S. and Juselius, K. (1990), Maximum Likelihood Estimation and Inference on Cointegration – with Applications to the Demand for Money, Oxford Bulletin of Economics and Statistics, 52, 2, 169–210.
Johansen, S. (1991), Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models, Econometrica, Vol. 59, No. 6, 1551–1580.
See Also
ca.jo
and ca.jo-class
.
Examples
data(denmark)
sjd <- as.matrix(denmark[, c("LRM", "LRY", "IBO", "IDE")])
sjd.vecm <- ca.jo(sjd, ecdet = "const", type="eigen", K=2, spec="longrun",
season=4)
lttest(sjd.vecm, r=1)
#
data(finland)
sjf <- as.matrix(finland)
sjf.vecm <- ca.jo(sjf, ecdet = "none", type="eigen", K=2,
spec="longrun", season=4)
lttest(sjf.vecm, r=3)