pp#

Purpose#

Computes the Phillips and Perron unit root test (Perron, P., & Ng, S. (1996)).

Format#

{ Zt, Za, cvZt, cvZa } = PP(y, model[, bwl, varm])#
Parameters:
  • y (Nx1 matrix) – Time series data to be tested.

  • model (Scalar) –

    Model to be implemented.

    0

    No constant or trend.

    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:
  • Zt (Scalar) – Phillips and Perron Zt test statistic.

  • Za (Scalar) – Phillips and Perron Za test statistic.

  • cvZt (Vector) – 1%, 5%, and 10% critical values for PP \(Zt\)-stat.

  • cvZa (Vector) – 1%, 5%, and 10% critical values for PP \(Zt\)-stat.

Examples#

library tspdlib;

// Load date file
y = loadd(__FILE_DIR $+ "TSe.dat");

// No deterministic component
model = 0;
{ Zt, Za, cvZt, cvZa } = PP(y, model);

Source#

pp.src

See also

Functions adf(), lmkpss()