ca.jo-class function

Representation of class ca.jo

Representation of class ca.jo

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

latin1

Slots

  • 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 V^SkkV^=I\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.

Extends

Class urca, directly.

Methods

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.

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, plotres and urca-class.

Author(s)

Bernhard Pfaff

  • Maintainer: Bernhard Pfaff
  • License: GPL (>= 2)
  • Last published: 2024-05-27

Useful links