vars (version 1.1-9)

predict: Predict method for objects of class varest and vec2var

Description

Forecating a VAR object of class varest or of class vec2var with confidence bands.

Usage

## S3 method for class 'varest':
predict(object, ..., n.ahead = 10, ci = 0.95, dumvar = NULL)
## S3 method for class 'vec2var':
predict(object, ..., n.ahead = 10, ci = 0.95, dumvar = NULL)

Arguments

object

An object of class varest; generated by VAR(), or an object of class vec2var; generated by vec2var().

n.ahead

An integer specifying the number of forecast steps.

ci

The forecast confidence interval

dumvar

Matrix for objects of class vec2var or varest, if the dumvar argument in ca.jo() has been used or if the exogen argument in VA

...

Currently not used.

Value

• A list with class attribute varprd holding the following elements:
• fcst
  A list of matrices per endogenous variable containing the forecasted values with lower and upper bounds as well as the confidence interval.
• endog
  Matrix of the in-sample endogenous variables.
• model
  The estimated VAR object.
• exo.fcst
  If applicable provided values of exogenous variables, otherwise NULL.

encoding

latin1

concept

• VAR
• VECM
• Vector autoregressive
• Forecasts of VAR
• Prediction of VAR

Details

The n.ahead forecasts are computed recursively for the estimated VAR, beginning with $h = 1, 2, \ldots, n.ahead$: $$\bold{y}_{T+1 | T} = A_1 \bold{y}_T + \ldots + A_p \bold{y}_{T+1-p} + C D_{T+1}$$ The variance-covariance matrix of the forecast errors is a function of $\Sigma_u$ and $\Phi_s$.

References

Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton. L�tkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.

See Also

VAR, vec2var, plot, fanchart

Examples

data(Canada)
var.2c <- VAR(Canada, p = 2, type = "const")
predict(var.2c, n.ahead = 8, ci = 0.95)