mgls

Purpose

Performs the MGLS unit root test.

Format

{ MZa, MZt, MSB, MPT, cvMZA, cvMZt, cvMSB, cvMPT } = MGLS(y, model[, bwl, varm])
Parameters
  • y (Nx1 matrix) – Time series data to be tested.

  • model (Scalar) –

    Model to be implemented.

    1

    Constant.

    2

    Constant and trend.

  • bwl (Scalar) – Optional, bandwidth for the spectral window. 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
  • MZa (Scalar) – MZalpha test statistic.

  • MZt (Scalar) – MZt test statistic.

  • MSB (Scalar) – MSB test statistic.

  • MPT – MPT test statistic.

  • cvMZa (Scalar) – 1%, 5%, and 10% critical values for MZa.

  • cvMZt (Vector) – 1%, 5%, and 10% critical values for MZt.

  • cvMSB (Vector) – 1%, 5%, and 10% critical values for MSB.

  • cvMPT (Vector) – 1%, 5%, and 10% critical values for MPT.

Examples

new;
cls;
library tspdlib;

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

// With constant
model = 1;
{MZa, MZt, MSB, MPT, cvMZA, cvMZt, cvMSB, cvMPT} = MGLS(y, model);

// With constant and trend
model = 2;
{MZa, MZt, MSB, MPT, cvMZA, cvMZt, cvMSB, cvMPT} = MGLS(y, model);

Source

gls.src

See also

Functions adf(), lmkpss(), dfgls(), erspt()