gls_2breaks¶

Purpose¶

Computes the GLS unit root test with two structural break.

Format¶

{ ADFGLS_min, p, PT_min, MZa_min, MZt_min, MSB_min, MPT_min, s2, tb1_min, tb2_min, lambda1, lambda2, cvPT, cvMPT, cvMZt, cvDFGLS, cvMSB, cvMZa } = gls_2breaks(y, model[, pmax, ic])¶

Parameters:

y (Nx1 matrix) – Time series data to be tested.
model (Scalar) –
Model to be implemented.

0

Level shift.

1

Trend shift.

2

Level and trend shift.
pmax (Scalar) – Optional, the maximum number of lags for \(\Delta y\). Default = 8.
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 3.

1

Akaike.

2

Schwarz.

3

t-stat significance.

Returns:

GLStau (Scalar) – ADF-GLS statistic.
p (Scalar) – Number of lags for ADF-GLS statistic.
PT (Scalar) – PT statistic.
Mza (Scalar) – MZalpha statistic.
Mzt (Scalar) – MZt statistic.
MSB (Scalar) – MSB statistic.
MPT (Scalar) – MPT statistic.
s2 – Long-run variance based on autoregressive spectral estimate.
tb1 (Scalar) – Location of the first break.
tb2 (Scalar) – Location of the second break.
lambda1 (Scalar) – Fraction of the first break (tb/T)
lambda2 (Scalar) – Fraction of the second break (tb/T)
cvPT (Vector) – 1%, 5%, and 10% critical values for the PT statistic.
cvMza (Vector) – 1%, 5%, and 10% critical values for the MZalpha statistic.
cvMzt (Vector) – 1%, 5%, and 10% critical values for the MZt statistic.
cvMSB (Vector) – 1%, 5%, and 10% critical values for the MSB statistic.
cvMPT (Vector) – 1%, 5%, and 10% critical values for the MPT statistic.

Examples¶

library tspdlib;

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

// Break in level
model = 1;
call gls_2breaks(y, model);

// Break in level and trend
model = 2;
call gls_2breaks(y, model);

Source¶

gls_2br.src

0	Level shift.
1	Trend shift.
2	Level and trend shift.

1	Akaike.
2	Schwarz.
3	t-stat significance.