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