Impulse response function
Computes the impulse response coefficients of a VAR(p) (or transformed
VECM to VAR(p)) or a SVAR for n.ahead steps.
## S3 method for class 'varest' irf(x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ...) ## S3 method for class 'svarest' irf(x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ...) ## S3 method for class 'vec2var' irf(x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ...) ## S3 method for class 'svecest' irf(x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ...)
x |
Object of class ‘ |
impulse |
A character vector of the impulses, default is all variables. |
response |
A character vector of the responses, default is all variables. |
n.ahead |
Integer specifying the steps. |
ortho |
Logical, if |
cumulative |
Logical, if |
boot |
Logical, if |
ci |
Numeric, the confidence interval for the bootstrapped errors bands. |
runs |
An integer, specifying the runs for the bootstrap. |
seed |
An integer, specifying the seed for the |
... |
Currently not used. |
The impulse response coefficients of a VAR(p) for n.ahead steps
are computed by utilising either the function Phi() or
Psi(). If boot = TRUE (the default), confidence
bands for a given width specified by ci are derived from
runs bootstrap. Hereby, it is at the users leisure to set a
seed for the random number generator.
The standard percentile interval is defined as:
CI_s = [s_{α/2}^*, s_{1 - α/2}^*] \quad ,
with s_{α/2}^* and s_{1 - α/2}^* are the
α/2 and 1 - α/2 quantiles of the bootstrap
distribution of Ψ^* or Φ^* depending whether
ortho = TRUE. In case cumulative = TRUE, the confidence
bands are calculated from the cumulated impulse response
coefficients.
A list of class ‘varirf’ with the following elements is
returned:
irf |
A list with matrices for each of the impulse variables containing the impulse response coefficients. |
Lower |
If |
Upper |
If |
response |
Character vector holding the names of the response variables. |
impulse |
Character vector holding the names of the impulse variables. |
ortho |
Logical, if |
cumulative |
Logical, if |
runs |
An integer, specifying the number of bootstrap runs. |
ci |
Numeric, defining the confidence level. |
boot |
Logical, if |
model |
Character, containing ‘ |
Bernhard Pfaff
Efron, B. and R. J. Tibshirani (1993), An Introduction to the Bootstrap, Chapman \& Hall, New York.
Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.
Lütkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.
data(Canada)
## For VAR
var.2c <- VAR(Canada, p = 2, type = "const")
irf(var.2c, impulse = "e", response = c("prod", "rw", "U"), boot =
FALSE)
## For SVAR
amat <- diag(4)
diag(amat) <- NA
svar.a <- SVAR(var.2c, estmethod = "direct", Amat = amat)
irf(svar.a, impulse = "e", response = c("prod", "rw", "U"), boot =
FALSE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.