bc_test_uncond {grangers}

Unconditional Granger-causality test of Breitung and Candelon (2006)

Description

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

Usage

bc_test_uncond(x, y, 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).

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_uncond⁠ calculates the test of Breitung and Candelon (2006) on the unconditional Granger-causality of a time series ⁠x⁠ (effect variable) respect to a time series ⁠y⁠ (cause variable). It requireNamespaces 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]
	uncond_bc<-bc_test_uncond(RealGdp.rate.ts,m3.rate.ts,ic.chosen="SC",max.lag=2)