pretty_irf: pretty_irf

In martinbaumgaertner/varexternal: Vector autoregression with external instruments

pretty_irf

Description

Estimates the asymptotic covariance matrix

Usage

pretty_irf(
  data,
  shock_names,
  pretty_names = NULL,
  cum = F,
  confidence_type = "msw",
  manual_color = NULL,
  legend = F,
  title = NULL,
  same_scale = T,
  shock_sign = "positive"
)

Arguments

data	list of var$irf objects from SVARIV
shock_names	instrument names
pretty_names	vector of pretty names for y-axis
cum	logical. Cumulative? BEWARE: Possible mistake here
confidence_type	vector of confidence types
manual_color	specify colors per Instrument. Input is a named vecor with shock_names and the corresponding color (hex)
legend	logical. inculde or exclude legends
title	vector of headings for each column
same_scale	logical value. Should all columns use the same scale?

Value

ggplot wrapper

Examples

p           = 24     #Number of lags in the VAR model
confidence  = confidence=c(0.6,0.9,0.95)    #Confidence Level for the standard and weak-IV robust confidence set
NWlags      = 0;  # Newey-West lags(set it to 0 to compute heteroskedasticity robust std errors)
norm        = 1; # Variable used for normalization
scale       = 1; # Scale of the shock
horizons    = 20; #Number of horizons for the Impulse Response Functions(IRFs)
colnames(oil)<-c("a","b","c","d","year","month")
ydata<-oil[,1:3]
z<-oil[,4]

VAR<-SVARIV(ydata,z,p,confidence,NWlags,norm,scale,horizons,instrument_name="test")
sh.col<-      c("#E41A1C")
names(sh.col)<-c("test")
pretty_irf(data=list(VAR$irfs),shock_names="test",pretty_names=c("a","b","c"),manual_color=sh.col,title="subheading")

martinbaumgaertner/varexternal documentation built on April 27, 2022, 1:31 a.m.