coint_egranger

Purpose

Computes the Engle-Granger test of the null hypothesis of no cointegration against the alternative of cointegration.

Format

{ tau, cvADF } = coint_egranger(y, x, model[, pmax, ic])

Parameters:

• y (Nx1 matrix) – Dependent variable.

• x (NxK matrix) – Independent variable.

• model (Scalar) –

  Model to be implemented.

  0	No deterministic components.
  1	Constant only.
  2	Constant and trend.

• pmax – Optional, maximum number of lags for \(\Delta y\) in ADF test. Default = 8.

• ic (Scalar) –

  Optional, the information criterion used for choosing lags. Default = 2.

  1	Akaike.
  2	Schwarz.

Returns:

• tau (Scalar) – Engle & Granger (1987) ADF test.

• cv (Vector) – 1%, 5%, 10% critical values for chosen model.

Examples

library tspdlib;

// Load dataset
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_coint.csv",
                                 ". + date($Date, '%b-%y')");

// Define y and x matrix
y = data[., 1];
x = data[., 2:cols(data)];

// No constant or trend
model = 0;

// Call test
{ tau, cvADF } = coint_egranger(y, x, model);

Source

coint_egranger.src

See also

Functions coint_cissanso(), coint_ghansen(), coint_hatemij(), coint_maki()