R: Likelihood ratio test for restrictions on beta

blrtest {urca} | R Documentation

## Likelihood ratio test for restrictions on beta

### Description

This function estimates a restricted VAR, where the restrictions are base upon \bold{β}, i.e. the cointegration vectors. The test statistic is distributed as χ^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)

### Arguments

`z` | An object of class `ca.jo`.
`H` | The (p \times s) matrix containing the restrictions on \bold{β}.
`r` | The count of cointegrating relationships; inferred from `summary(ca.jo-object)`.

### 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)).

### Value

An object of class `cajo.test`.

### Author(s)

Bernhard Pfaff

### 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))

[Package urca version 1.3-0 Index]