It is a tough challenge to incorporate all of these effects in the theoretical and empirical models that are typically used by macroeconomists, such as structural vector autoregression (SVAR) models and micro-founded general equilibrium (DSGE) models. For these reasons turning back to the older tradition of building structural econometric models (SEMs) – built from blocks of simultaneously estimated equations with structural identifying restrictions – can be useful. This approach can be thought of as a blend of the more theory-free VAR methods and a more structural model-based approach. The main advantage of the structural econometric frameworks are that they produce quantitative results at a sector level, which can still be aggregated up to produce a general equilibrium response. They also allow models to be built up in a modular way that allows replacing and improving sets of equations for particular blocks of the model without necessarily undermining the logic of the model as a whole. This older school approach to modelling has begun to appear in a variety of modern vintages. The GVAR methodology (see Mauro and Pesaran (2013)) also takes the approach of estimating many separate blocks, with linkages between them determined by a weighting matrix. This approach has been used to analyse global shocks (for example Cesa-Bianchi et al (2012)) – with the weighting matrix built from trade relationships.Bank of England — Bank Underground
Modelling banking sector shocks and unconventional policy: new wine in old bottles?
James Cloyne, Ryland Thomas and Alex Tuckett.