bc_test_cond: Conditional Granger-causality test of Breitung and Candelon...

In grangers: Inference on Granger-Causality in the Frequency Domain

Description

Inference on the conditional Granger-causality spectrum is provided by the parametric test of Breitung and Candelon (2006).

Usage

bc_test_cond(x, y, z, ic.chosen = "SC", max.lag = min(4, length(x) -
  1), plot = F, type.chosen = "none", p = 0, conf = 0.95)

Arguments

x	univariate time series.
y	univariate time series (of the same length of x).
z	univariate time series (of the same length of x).
ic.chosen	estimation method parameter ic to be passed to function VAR of package vars. Defaults to ”SC” (Schwarz criterion). Alternatives are c(''AIC'',''HQ'',''SC'',''FPE'').
max.lag	maximum number of lags lag.max to be passed to function VAR. Defaults to min(4, length(x) - 1).
plot	logical; if TRUE, it returns the plot of conditional Granger-causality spectrum. Defaults to FALSE.
type.chosen	parameter type to be passed to function VAR.
p	parameter p to be passed to function VAR. It corresponds to the number of lags of the second VAR model. Defaults to 0.
conf	prescribed confidence level. It defaults to 0.95.

Details

bc_test_cond calculates the test of Breitung and Candelon (2006) on the conditional Granger-causality of a time series x (effect variable) on a time series z (conditioning variable) respect to a time series y (cause variable). It requires package vars.

Value

frequency: frequencies used by Fast Fourier Transform.

n: time series length.

confidence_level: prescribed confidence level.

significant_frequencies: frequencies at which the test is significant..

F-test: computed F-test at each frequency.

F-threshold: F-threshold at each frequency under prescribed confidence level.

roots: roots of the estimated VAR model.

delays: delays of the estimated VAR model.

The result is returned invisibly if plot is TRUE.

Author(s)

Matteo Farne', Angela Montanari, [e-mail]

References

Breitung, J., Candelon, B., 2006. Testing for short- and long-run causality: A frequency-domain approach. Journal of Econometrics. 132, 2, 363–378.

Farne', M., Montanari, A., 2018. A bootstrap test to detect prominent Granger-causalities across frequencies. <arXiv:1803.00374>, Submitted.

See Also

VAR.

Examples

	RealGdp.rate.ts<-euro_area_indicators[,1]
	m3.rate.ts<-euro_area_indicators[,2]
	hicp.rate.ts<-euro_area_indicators[,4]	
	cond_bc<-bc_test_cond(RealGdp.rate.ts,m3.rate.ts,hicp.rate.ts,ic.chosen="SC",max.lag=2)

Example output

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

grangers documentation built on June 3, 2019, 5:05 p.m.