IRIS Toolbox Reference Manual

# Bayesian VAR prior dummies: BVAR package

The BVAR package can be used to create the basic types of prior dummy observations when estimating Bayesian VAR models. The dummy observations are passed in the `VAR/estimate` function through the `'BVAR='` option.

#### Constructing dummy observations

- `covmat` - Covariance matrix prior dummy observations for BVARs.
- `litterman` - Litterman's prior dummy observations for BVARs.
- `sumofcoeff` - Doan et al sum-of-coefficient prior dummy observations for BVARs.
- `uncmean` - Unconditional-mean dummy (or Sims' initial dummy) observations for BVARs.
- `user` - User-supplied prior dummy observations for BVARs.

#### Weights on prior dummy observations

The prior dummies produced by `litterman`, `uncmean`, `sumofcoeff` can be weighted up or down using the input argument `Mu`. To give the weight a clear interpretation, use the option `'stdize=' true` when estimating the VAR. In that case, setting `Mu` to `sqrt(N)` means the prior dummies are worth a total of extra `N` artifical observations; the weight can be related to the actual number of observations used in estimation.

#### Getting help on BVAR functions

    help BVAR
    help BVAR/function_name

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