Evidence and data

Evaluate forecasts out of sample and report posterior uncertainty rather than only the posterior mean.

Calibration or measurement

Prior tightness, lag length, variable scaling, and dummy observations define the practical model.

Boundaries

• Shrinkage can hide misspecification.
• Priors matter more in short samples.
• Structural interpretation still requires identification.

Use guidance

When sufficient

Forecasting and conditional projections with a moderate-to-large variable set when shrinkage priors discipline overparameterization. The Minnesota prior (Litterman 1986 JBES) and its extensions (Banbura-Giannone-Reichlin 2010 JAE) keep the VAR tractable as the variable count grows, improving out-of-sample forecast accuracy over OLS estimation when the sample is short relative to the number of parameters. The right tool for large-system forecasting where the BVAR dominates smaller specification-searched VARs.

When sketch only

A BVAR remains a reduced-form forecasting tool. Structural identification still requires a separate assumption block: a sign-restriction or proxy-SVAR layer must be added before impulse responses carry causal content. Also do not use the posterior mean alone as the point forecast without reporting posterior uncertainty; prior tightness can mask genuine parameter uncertainty.

When to switch

Switch to a factor-augmented VAR (FAVAR, Bernanke-Boivin-Eliasz 2005 QJE) when a large panel of indicators is relevant but only a few latent factors drive the common variation, making a full BVAR over all indicators unnecessary. Switch to a BVAR with identification when structural shock responses are the object, adding whatever restriction maps the reduced form to the structural form.

Falsification signal

Forecast performance that degrades as variables are added to the system, producing higher RMSFE at larger dimensions rather than lower, indicates the prior is misspecified or the prior tightness is too loose to offset the overfitting from additional parameters. A rolling pseudo-real-time comparison of BVARs with 5, 15, and 30 variables showing the 30-variable system losing to the 5-variable version would be the concrete signal.