kss#

Purpose#

Computes the KSS unit root test.

Format#

{ kss_t, p, cv } = kss(y, model[, pmax, ic])#

Parameters:

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

0

Zero mean & no trend

1

Constant included.

2

Constant and trend.
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:

kss_t (Scalar) – KSS tau-statistic
p (Scalar) – Chosen number of lags.
cv (Vector) – 1, 5, and 10 percent critical values for KSS tau-stat based on response surfaces.

Examples#

library tspdlib;

// Load date file
y = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/TSe.dat");

// Run model with constant
model = 1;

// Run test
stat = kss(y, model);

Source#

kss.src

0	Zero mean & no trend
1	Constant included.
2	Constant and trend.

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