coint_tsongetal

Purpose

Test of the null of cointegration allowing for structural breaks of unknown form in deterministic trend by using the Fourier form.

Format

{ CIfols, FFols, CIfdols, FFdols, cv, Fols, Fdols } = coint_tsongetal(y, x, model[, bwl, kmax, varm, q])
Parameters:
  • y (Nx1 matrix) – Dependent variable.
  • x (NxK matrix) – Independent variable.
  • model (Scalar) –

    Model to be implemented.

    1 Level shift model with Fourier
    2 Level & trend shift model with Fourier
  • bwl (Scalar) – Optional, bandwidth length for long-run variance computation. Default = round(4 * (T/100)^(2/9)).
  • kmax (Scalar) – Optional, maximum number of Fourier frequency. Default = 5.
  • 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
  • q (Scalar) – Optional, number of leads and lags for DOLS estimation. Default = int(4 * (t/100)^(2/9)).
Returns:
  • CIols (Scalar) – CI test based on OLS estimation.
  • FFols (Scalar) – Optimal Fourier frequency based on OLS estimation.
  • CIDols (Scalar) – CI test based on DOLS estimation
  • FFdols (Scalar) – Optimal Fourier frequency based on DOLS estimation.
  • Fols (Scalar) – F-stat for Fourier terms significance based on OLS.
  • Fdols (Scalar) – F-stat for Fourier terms significance based on DOLS.
  • cv (Scalar) – 1%, 5%, 10% critical values for the model chosen.

Examples

new;
cls;
library tspdlib;

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


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

// Level shift
model = 1;
{ CIfols, FFols, CIfdols, FFdols, cv_fourier, Fols, Fdols } = coint_tsongetal(y, x, model);

Source

coint_tsongetal.src