coint_pouliaris

Purpose

Computes residual based tests for cointegration with asymptotic critical values.

Format

{ Zt, Za, cvZt, cvZa } = coint_pouliaris(y, x, model[, bwl, varm])

Parameters:

• y (Nx1 matrix) – Dependent variable.

• x (NxK matrix) – Independent variable.

• model (Scalar) –

  Model to be implemented.

  0	None
  1	Constant only
  2	Constant and trend

• bwl (Scalar) – Optional, bandwidth length for long-run variance computation. Default = round(4 * (T/100)^(2/9)).

• varm (Scalar) –

  Optional, long-run consistent variance estimation method. Default = 1.

  1	iid.
  2	Bartlett.
  3	Quadratic Spectral (QS).
  4	SPC with Bartlett (Sul, Phillips & Choi, 2005)
  5	SPC with QS
  6	Kurozumi with Bartlett
  7	Kurozumi with QS

Returns:

• Zt (Scalar) – Phillips & Ouliaris (1989) Zt test

• Za (Scalar) – Phillips & Ouliaris (1989) Za test

• cvZt (Scalar) – 1%, 5%, 10% critical values for Zt test statistic.

• cvZa (Scalar) – 1%, 5%, 10% critical values for Za test statistic.

Examples

new;
cls;
library tspdlib;

// Load dataset
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_coint.csv",
                          "Y1 + Y2 + Y3 + Y4 + date($Date, '%b-%y')");


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

// No constant or trend
model = 0;

// Call test
{ Zt, Za, cvZt, cvZa } = coint_pouliaris(y, x, model);

Source

coint_pouliaris.src