VAR {vars}R Documentation

Estimation of a VAR(p)

Description

Estimation of a VAR by utilising OLS per equation.

Usage

VAR(y, p = 1, type = c("const", "trend", "both", "none"))

Arguments

y Data item containing the endogenous variables
p Integer for the lag order (default is p=1).
type Type of deterministic regressors to include.

Details

Estimates a VAR by OLS per equation. The model is of the following form:

y_t = CD_t + A_1 y_{t-1} + ... + A_p y_{t-p} + u_t

where y_t is a K times 1 vector of endogenous variables and u_t assigns a spherical disturbance term of the same dimension. The coefficient matrices A_1, ..., A_p are of dimension K times K. In addition, either a constant and/or a trend can be included as deterministic regressors (term CD_T, by setting the type argument to the corresponding value. The default is const.

Value

A list with class attribute ‘varest’ holding the following elements:

varresult list of ‘lm’ objects.
resid A matrix object of the residuals.
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 Either NULL or a matrix object containing the zero restrictions of the VAR(p).
call The call to VAR().

Author(s)

Bernhard Pfaff

References

Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.

Lütkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.

See Also

summary.varest, plot.varest, predict.varest

Examples

data(Canada)
VAR(Canada, p = 2, type = "none")
VAR(Canada, p = 2, type = "const")
VAR(Canada, p = 2, type = "trend")
VAR(Canada, p = 2, type = "both")

[Package vars version 0.5.3 Index]