coint_ghansen#
Purpose#
Computes the tests for the null of no cointegration against the alternative of cointegration with a structural break in the mean.
Format#
- { ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model[, bwl, ic, pmax, varm, trimm])#
- Parameters:
y (Nx1 matrix) – Dependent variable.
x (NxK matrix) – Independent variable.
model (Scalar) –
Model to be implemented.
1
Level shift (C)
2
Level shift with trend (C/T)
3
Regime shift (C/S)
4
Regime and trend shift
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
TBadf (Scalar) – Break point using OLS.
Zamin (Scalar) – Za test statistic
TBza (Scalar) – Break point for using Za statistic.
Ztmin (Scalar) – Zt test statistic
TB_zt (Scalar) – Break point using Zt 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#
new;
cls;
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)];
// Level shift
model = 1;
// Call test
{ ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model);
Source#
coint_ghansen.src
See also
Functions coint_cissanso()
, coint_egranger()
, coint_hatemij()
, coint_maki()