lm_1break#

Purpose#

Computes the minimum LM unit root test with one structural break.

Format#

{ lm_tstat, tb, lags, lambda, cv } = LM_1break(y, model[, pmax, ic, trimm])#

Parameters:

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

1

Break in level.

2

Break in level 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.
trimm (Scalar) – Optional, trimming rate. Default = 0.10.

Returns:

lm_tstat (Scalar) – Minimum test statistic.
tb (Scalar) – Location of break.
lags (Scalar) – Number of lags selected by chosen information criterion.
lambda (Scalar) – Break fraction (tb/T).
cv (Vector) – 1%, 5%, and 10% critical values for lm_1break() \(\tau\)-stat..

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;
{ LM_min, tb1, p, lambda, cv } = LM_1break(y, model);

// Break in level and trend
model = 2;
{ LM_min, tb1, p, lambda, cv } = LM_1break(y, model);

Source#

lm_1br.src

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