QVAR {ConnectednessApproach} | R Documentation |
Quantile vector autoregression
Description
Estimation of a QVAR using equation-by-equation quantile regressions.
Usage
QVAR(x, configuration = list(nlag = 1, tau = 0.5, method = "fn"))
Arguments
x |
zoo data matrix |
configuration |
model configuration |
nlag |
Lag length |
tau |
quantile between 0 and 1 |
method |
See methods for rq in quantreg package. Default is "fn". |
Value
Estimate QVAR model
Author(s)
David Gabauer
References
White, H., Kim, T. H., & Manganelli, S. (2015). VAR for VaR: Measuring tail dependence using multivariate regression quantiles. Journal of Econometrics, 187(1), 169-188.
Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach. Economics Letters, 204, 109891.
Examples
data("dy2012")
fit = QVAR(dy2012, configuration=list(nlag=1, tau=0.5))
[Package ConnectednessApproach version 1.0.3 Index]