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 <=q 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)

[Package urca version 1.2-3 Index]