fourier_kpss#

Purpose#

Computes the KPSS stationarity test with flexible Fourier form structural breaks.

Format#

{ KPSSk, f, cv } = fourier_kpss(y, model[, fmax, bwl, varm])#
Parameters:

  • y (Nx1 matrix) – Dependent variable.

  • model (Scalar) –

    Model to be implemented.

    1

    Constant

    2

    Constant and trend

  • fmax (Scalar) – Optional, maximum number of single Fourier frequency (upper bound is 5). Default = 5.

  • bwl (Scalar) – Optional, bandwidth for 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:

  • KPSSk (Scalar) – KPSS(k) statistic.

  • f (Scalar) – Number of single frequency.

  • cv (Vector) – 1%, 5%, 10% critical values for the chosen model

Examples#

library tspdlib;

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

// With constant
model = 1;

// Call test
{ KPSSk, f, cv } = Fourier_KPSS(y, model);

Source#

fourier_kpss.src

See also

Functions fourier_adf(), fourier_gls(), fourier_lm()

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