ba.boot: Bootstrap after Bootstrap

In alexanderlange53/svars: Data-Driven Identification of SVAR Models

Bootstrap after Bootstrap

Description

Bootstrap intervals based on bias-adjusted estimators

Usage

ba.boot(x, nc = 1)

Arguments

x	SVAR object of class "sboot"
nc	Integer. Number of processor cores

Value

A list of class "sboot" with elements

true	Point estimate of impulse response functions
bootstrap	List of length "nboot" holding bootstrap impulse response functions
SE	Bootstrapped standard errors of estimated covariance decomposition (only if "x" has method "Cramer von-Mises", or "Distance covariances")
nboot	Number of bootstrap iterations
b_length	Length of each block
point_estimate	Point estimate of covariance decomposition
boot_mean	Mean of bootstrapped covariance decompositions
signrest	Evaluated sign pattern
sign_complete	Frequency of appearance of the complete sign pattern in all bootstrapped covariance decompositions
sign_part	Frequency of bootstrapped covariance decompositions which conform the complete predetermined sign pattern. If signrest=NULL, the frequency of bootstrapped covariance decompositions that hold the same sign pattern as the point estimate is provided.
sign_part	Frequency of single shocks in all bootstrapped covariance decompositions which accord to a specific predetermined sign pattern
cov_bs	Covariance matrix of bootstrapped parameter in impact relations matrix
method	Used bootstrap method
VAR	Estimated input VAR object

References

Kilian, L. (1998). Small-sample confidence intervals for impulse response functions. Review of Economics and Statistics 80, 218-230.

See Also

mb.boot, wild.boot

Examples

# data contains quarterly observations from 1965Q1 to 2008Q3
# x = output gap
# pi = inflation
# i = interest rates
set.seed(23211)
v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" )
x1 <- id.dc(v1)
summary(x1)

# Bootstrap
bb <- mb.boot(x1, b.length = 15, nboot = 300, n.ahead = 30, nc = 1, signrest = NULL)
summary(bb)
plot(bb, lowerq = 0.16, upperq = 0.84)

# Bias-adjusted bootstrap
bb2 <- ba.boot(bb, nc = 1)
plot(bb2, lowerq = 0.16, upperq = 0.84)

alexanderlange53/svars documentation built on Jan. 31, 2023, 7:50 a.m.