erspt

Purpose

Computes ERS point optimal unit root test.

Format

{ Pt, lrv, cvPT } = ERSpt(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
  • Pt (Scalar) – Point statistic

  • lrv (Scalar) – Long-run variance estimate.

  • cvPt (Vector) – 1%, 5%, and 10% critical values for Pt.

Examples

new;
cls;
library tspdlib;

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

// With constant
model = 1;

// Call test
{ Pt, lrv, cvPt } = ERSpt(y, model);

Source

gls.src

See also

Functions adf(), kpss()