urca (version 1.3-4)

blrtest: Likelihood ratio test for restrictions on beta

Description

This function estimates a restricted VAR, where the restrictions are base upon \(\bold{\beta}\), i.e. the cointegration vectors. The test statistic is distributed as \(\chi^2\) with \(r(p-s)\) degrees of freedom, with \(s\) equal to the columns of the restricting matrix \(\bold{H}\).

Usage

blrtest(z, H, r)

Value

An object of class cajo.test.

Arguments

z

An object of class ca.jo.

H

The \((p \times s)\) matrix containing the restrictions on \(\bold{\beta}\).

r

The count of cointegrating relationships;
inferred from summary(ca.jo-object).

Author

Bernhard Pfaff

Details

Please note, that in the case of nested hypothesis, the reported p-value should be adjusted to \(r(s1-s2)\) (see Johansen, S. and K. Juselius (1990)).

References

Johansen, S. (1988), Statistical Analysis of Cointegration Vectors, Journal of Economic Dynamics and Control, 12, 231--254.

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, alrtest, ablrtest, bh5lrtest, bh6lrtest, cajo.test-class, ca.jo-class and urca-class.

Examples

data(denmark)
sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
sjd.vecm <- ca.jo(sjd, ecdet="const", type="eigen", K=2, spec="longrun",
season=4)
HD0 <- matrix(c(-1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1), c(5,4))
summary(blrtest(sjd.vecm, H=HD0, r=1))