g

Display combined graphs, with impulse responses of one variable to all shocks shown in one graph.

m (default)

Display multiple graphs, with impulse response to each shock shown in separate graphs.

t

Tabulate the impulse responses.

a

Accumulate the impulse responses.

imp=arg (default=“chol”)

Type of factorization for the decomposition: unit impulses, ignoring correlations among the residuals (“imp=unit”), non-orthogonal, ignoring correlations among the residuals (“imp=nonort”), Cholesky with d.f. correction (“imp=chol”), Cholesky without d.f. correction (“imp=mlechol”), Generalized (“imp=gen”), structural (“imp=struct”), or user specified (“imp=user”).

The structural factorization is based on the estimated structural VAR. To use this option, you must first estimate the structural decomposition; see Var::svar.

For user-specified impulses, you must specify the name of the vector/matrix containing the impulses using the “fname=” option.

The option “imp=mlechol” is provided for backward compatibility with EViews 3.x and earlier.

fname=name

se=arg

Standard error calculations: “se=a” (analytic), “se=mcarlo” (Monte Carlo), “se=boot” (bootstrap).

If selecting Monte Carlo or bootstrap, you must specify the number of replications with the “rep=” option.

Note the following:

(1) Analytic standard errors are currently not available for (a) VECs and (b) structural decompositions identified by long-run restrictions. The “se=a” option will be ignored for these cases.

(2) Monte Carlo standard errors are currently not available for (a) VECs and (b) structural decompositions. The “se=mcarlo” option will be ignored for these cases.

(3) VECs only compute bootstrap standard errors so this option will be ignored.

rep=integer

Number of Monte Carlo or bootstrap replications to be used in computing the standard errors. Must be used with the “se=mcarlo” and “se=boot” options.

bs=arg (default = “hp”)

Bootstrap method: “sp” (standard percentile), “hp” (Hall’s percentile), “hs” (Hall’s studentized), “ku” (Killian’s unbiased).

dbsrep (default = 499)

Number of double bootstrap replications. Must be used with the “bs=hs” and “bs=ku” options unless the “fdb” option is specified, in which case this option will be ignored.

fdb

Approximate the double bootstrap computation using fast double bootstrap routines.

cilevels=arg (default = “0.95”)

Confidence interval coverage: space limited list of numbers between 0 and 1.

uselines

Use lines instead of shading for confidence intervals.

matbys=name

Save responses ordered by shocks (impulses) in a named matrix. The first column is the response of the first variable to the first shock, the second column is the response of the second variable to the first shock, and so on. The response and shock orderings correspond to the ordering of variables in the VAR.

matbyr=name

Save responses ordered by response series in a named matrix. The first column is the response of the first variable to the first shock, the second column is the response of the first variable to the second shock, and so on. The response and shock orderings correspond to the ordering of variables in the VAR.

smat=name

Save responses ordered by shocks (impulses) in a named matrix (akin to the “matbys=” option). The shocks and responses are ordered according to the user-specified order given by the “@ shock_series” and “@ ordering_series” specifications.

rmat=name

Save responses ordered by response series in a named matrix (akin to the “matbyr=” option). The shocks and responses are ordered according to the user-specified order given by the “@ shock_series” and “@ ordering_series” specifications.

cimat=name

Save matrix consisting of confidence intervals (lower-upper pairs for each impulse-response combination).

rcimat=name

Save matrix consisting of impulse responses and associated confidence intervals (lower-upper pairs for each impulse-response combination).

prompt

Force the dialog to appear from within a program.

p

Print the results.

bvartype = arg (default= “bayes”)

 

Impulse method: Bayesian sampling (“bayes”), classical impulse response analysis using the posterior residual covariance matrix (“classpost”), classical impulse response analysis using the empirical residual covariance matrix (“classemp”).

draws=integer (default= 100000)

Number of draws.

burn=arg (default=0.1)

Proportion of initial draws to discard.

seed=integer

Random number seed.

dropunstable

Drop any draws that produce unstable coefficients.

dgraph

Produce distribution graphs.

page=arg

Store the individual draws in a new page.

starts = arg

Set impulse dates. For multiple dates, enter a space-delimited list of values surrounded by quotation marks, e.g., "1980q1 2000q1 2020q1".

usemean

Use posterior mean as the point estimate. The posterior median is used if usemean is not included in the options list.

showci

Show credibility intervals (bands).