ca.jo-class | R Documentation |

This class contains the relevant information by applying the Johansen procedure to a matrix of time series data.

`x`

:Object of class

`"ANY"`

: A data matrix, or an object that can be coerced to it.`Z0`

:Object of class

`"matrix"`

: The matrix of the differenced series.`Z1`

:Object of class

`"matrix"`

: The regressor matrix, except for the lagged variables in levels.`ZK`

:Object of class

`"matrix"`

: The matrix of the lagged variables in levels.`type`

:Object of class

`"character"`

: The type of the test, either`"trace"`

or`"eigen"`

.`model`

:Object of class

`"character"`

: The model description in prose, with respect to the inclusion of a linear trend.`ecdet`

:Object of class

`"character"`

: Specifies the deterministic term to be included in the cointegration relation. This can be either "none", "const", or "trend".`lag`

:Object of class

`"integer"`

: The lag order for the variables in levels.`P`

:Object of class

`"integer"`

: The count of variables.`season`

:Object of class

`"ANY"`

: The frequency of the data, if seasonal dummies should be included, otherwise NULL.`dumvar`

:Object of class

`"ANY"`

: A matrix containing dummy variables. The row dimension must be equal to`x`

, otherwise NULL.`cval`

:Object of class

`"ANY"`

: The critical values of the test at the 1%, 5% and 10% level of significance.`teststat`

:Object of class

`"ANY"`

: The values of the test statistics.`lambda`

:Object of class

`"vector"`

: The eigenvalues.`Vorg`

:Object of class

`"matrix"`

: The matrix of eigenvectors, such that*\hat V'S_{kk}\hat V = I*.`V`

:Object of class

`"matrix"`

: The matrix of eigenvectors, normalised with respect to the first variable.`W`

:Object of class

`"matrix"`

: The matrix of loading weights.`PI`

:Object of class

`"matrix"`

: The coeffcient matrix of the lagged variables in levels.`DELTA`

:Object of class

`"matrix"`

: The variance/covarinace matrix of`V`

.`GAMMA`

:Object of class

`"matrix"`

: The coeffecient matrix of`Z1`

.`R0`

:Object of class

`"matrix"`

: The matrix of residuals from the regressions in differences.`RK`

:Object of class

`"matrix"`

: The matrix of residuals from the regression in lagged levels.`bp`

:Object of class

`"ANY"`

: Potential break point, only set if function`cajolst`

is called, otherwise`NA`

.`test.name`

:Object of class

`"character"`

: The name of the test,*i.e.*‘Johansen-Procedure’.`spec`

:Object of class

`"character"`

: The specification of the VECM.`call`

:Object of class

`"call"`

: The call of function`ca.jo`

.

Class `urca`

, directly.

Type `showMethods(classes="ca.jo")`

at the R prompt for a
complete list of methods which are available for this class.

Useful methods include

`show`

:test statistic.

`summary`

:like show, but critical values, eigenvectors and loading matrix added.

`plot`

:The series of the VAR and their potential cointegration relations.

Bernhard Pfaff

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.

`ca.jo`

, `plotres`

and `urca-class`

.

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