coint_hatemij#

Purpose#

Computes the test of the null hypothesis of no cointegration against the alternative of cointegration with two regime shifts.

Format#

{ ADF_min, TB1adf, TB2adf, Zt_min, TB1zt, TB2zt, Za_min, TB1za, TB2za, cvADFZt, cvZa } = coint_hatemiJ(y, x[, model, bwl, ic, pmax, varm, trimm])#
Parameters:

  • y (Nx1 matrix) – Dependent variable.

  • x (NxK matrix) – Independent variable.

  • model (Scalar) –

    Optional, model to be implemented. Default = 3.

    3

    Regime shift (C/S)

  • bwl (Scalar) – Optional, bandwidth length for long-run variance computation. Default = round(4 * (T/100)^(2/9)).

  • ic (Scalar) –

    Optional, the information criterion used for choosing lags. Default = 3.

    1

    Akaike.

    2

    Schwarz.

    3

    t-stat significance

  • pmax (Scalar) – Optional, maximum number of lags for \(\Delta y\) in ADF test. Default = 8.

  • 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

  • trimm (Scalar) – Optional, trimming rate. Default = 0.10.

Returns:

  • ADFmin (Scalar) – ADF test statistic

  • TB1adf (Scalar) – First break point using ADF statistic.

  • TB2adf (Scalar) – Second break point using ADF statistic.

  • Ztmin (Scalar) – Zt test statistic

  • TB1zt (Scalar) – Break point using Zt statistic.

  • TB2zt (Scalar) – Break point using Zt statistic.

  • Zamin (Scalar) – Za test statistic

  • TB1za (Scalar) – First break point for using Za statistic.

  • TB2adf – Second break point using Za statistic.

  • cvADFZt (Scalar) – 1%, 5%, 10% critical values for ADF and Zt test statistics.

  • cvZa (Scalar) – 1%, 5%, 10% critical values for Za test statistics.

Examples#

library tspdlib;

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

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

T = rows(data);

// Call test
{ADF_min, TB1adf, TB2adf, Zt_min, TB1zt, TB2zt, Za_min, TB1za, TB2za, cvADFZt, cvZa } =
    coint_hatemiJ(y, x);

Source#

coint_hatemij.src

See also

Functions coint_cissanso(), coint_egranger(), coint_ghansen(), coint_maki()

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