Estimating and identifying vector autoregressions under diagonality and block exogeneity restrictions

I show how to estimate and identify a large-scale vector autoregression (VAR) when the variables in a subset are mutually independent, conditional on common factors and when the conditioning variables are independent of the former subset. The approach is useful when using VARs to estimate the responses of a large cross-section of variables to aggregate shocks.