panel_fisher#

Purpose#

Computes tests for Granger causality in heterogeneous mixed panels with bootstrap critical values.

Format#

Fisher = Panel_Fisher(data, vnames, pmax, dmax, ic, Nboot)#

Parameters:

data (Txk matrix) – Data to be tested with k individual variables each in a separate column.
vnames (String array) – Variable names.
pmax (Scalar) – Maximum number of lags.
dmax (Scalar) – Maximum integration degree of variables.
ic (Scalar) –
The information criterion used for choosing lags.

1

Akaike.

2

Schwarz.

3

t-stat significance.

Default = 2.
Nboot (Scalar) – Number of bootstrap replications.
Ncross (Scalar) – Number of cross sections.

Returns:

Fisher (Scalar) – Panel Fisher statistics. Prints individual results and bootstrap critical values.

Examples#

new;
library tspdlib;

// Load panel data
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/pdcause.dat");

// Number of bootstrap replications
Nboot = 1000;

// Number of time periods
T = 28;

// Number of cross-sections
Ncross = 9;

// Maximum number of lags
pmax = 3;

// Number of integration
dmax = 1;

// Information criterion;
// 1 = Akaike, 2 = Schwarz
ic = 2;

// Variable names
vnames = "y"$|"x";

Fisher = Panel_Fisher(data, vnames, pmax, dmax, ic, Nboot, Ncross);

Source#

pdcause_fisher.src

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