pd_cause¶
Purpose¶
Computes tests for Granger causality in heterogeneous mixed panels with bootstrap critical values.
Format¶
-
pd_stat =
pd_cause(data, Ncross, test[, pmax, dmax, ic, Nboot, vnames])¶ - Parameters:
data (Txk matrix) – Data to be tested with k individual variables each in a separate column.
Ncross (Scalar) – Number of cross sections.
test (String) –
The panel data causality test to be implemented.
”fisher”
Fisher test.
”zhnc”
Panel Zhnc statistic.
”surwald”
Panel SUR Wald statistic.
pmax (Scalar) – Optional, maximum number of lags. Default = 8.
dmax (Scalar) – Optional, maximum integration degree of variables. Default = 1.
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 1.
1
Akaike.
2
Schwarz.
3
t-stat significance.
Default = 2.
Nboot (Scalar) – Optional, Number of bootstrap replications. Default = 1000.
vnames (String array) – Variable names.
- Returns:
cause_stat (Dataframe) – Panel causation statistics. Prints individual results and bootstrap critical values.
Examples¶
library tspdlib;
// Load data
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/pdcause.dat");
// Number of cross-sections
N = 9;
/*
** Run Fisher test
*/
test = "fisher";
// Call test
cause_stat = pd_cause(data, N, test);
/*
** Run Zh and Zn test
*/
test = "zhnc";
// Call test
cause_stat = pd_cause(data, N, test);
/*
** Run SURwald test
*/
test = "surwald";
// Call test
cause_stat = pd_cause(data, N, test);
Source¶
pd_cause.src
See also
Functions granger(), panel_fisher(), panel_zhnc(), panel_surwald()