ablrtest | R Documentation |
This function estimates a restricted VAR, where the restrictions are
based upon \bold{\alpha}
, i.e. the loading vectors and
\bold{\beta}
, i.e the matrix of cointegration vectors. The test
statistic is distributed as \chi^2
with (p-m)r + (p-s)r
degrees of
freedom, with m
equal to the columns of the restricting matrix
\bold{A}
, s
equal to the columns of the restricting matrix
\bold{H}
and p
the order of the VAR.
ablrtest(z, H, A, r)
z |
An object of class |
H |
The |
A |
The |
r |
The count of cointegrating relationships; |
The restricted \bold{\alpha}
matrix, as well as \bold{\beta}
is
normalised with respect to the first variable.
An object of class cajo.test
.
Bernhard Pfaff
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.
ca.jo
, alrtest
, blrtest
,
cajo.test-class
, ca.jo-class
and
urca-class
.
data(denmark)
sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
sjd.vecm <- ca.jo(sjd, ecdet = "const", type="eigen", K=2, spec="longrun",
season=4)
HD1 <- matrix(c(1, -1, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 1), c(5,3))
DA <- matrix(c(1,0,0,0, 0, 1, 0, 0, 0, 0, 0, 1), c(4,3))
summary(ablrtest(sjd.vecm, H=HD1, A=DA, r=1))
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