| restrict {vars} | R Documentation |
Estimation of a VAR, by imposing zero restrictions manually or by significance.
restrict(x, method = c("ser", "manual"), thresh = 2.0, resmat = NULL)
x |
An object of class ‘ |
method |
A character, choosing the method |
thresh |
If method |
resmat |
If method |
Given an estimated VAR object of class ‘varest’, a restricted VAR
can be obtained by either choosing method ser or
manual. In the former case, each equation is re-estimated
separately as long as there are t-values that are in absolut value below the
threshhold value set by the function's argument thresh. In the
latter case, a restriction matrix has to be provided that consists of
0/1 values, thereby selecting the coefficients to be retained in the
model.
A list with class attribute ‘varest’ holding the
following elements:
varresult |
list of ‘ |
datamat |
The data matrix of the endogenous and explanatory variables. |
y |
The data matrix of the endogenous variables |
type |
A character, specifying the deterministic regressors. |
p |
An integer specifying the lag order. |
K |
An integer specifying the dimension of the VAR. |
obs |
An integer specifying the number of used observations. |
totobs |
An integer specifying the total number of observations. |
restrictions |
The matrix object containing the zero restrictions
provided as argument |
call |
The |
Currently, the restricted VAR is estimated by OLS and not by an efficient EGLS-method.
Bernhard Pfaff
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)
var.2c <- VAR(Canada, p = 2, type = "const")
## Restrictions determined by thresh
restrict(var.2c, method = "ser")
## Restrictions set manually
restrict <- matrix(c(1, 1, 1, 1, 1, 1, 0, 0, 0,
1, 0, 1, 0, 0, 1, 0, 1, 1,
0, 0, 1, 1, 0, 1, 0, 0, 1,
1, 1, 1, 0, 1, 1, 0, 1, 0),
nrow=4, ncol=9, byrow=TRUE)
restrict(var.2c, method = "man", resmat = restrict)