Modelling a Complex World: Improving Macromodels

Macro models have come under criticism for their ability to understand or predict major
economic events such as the global financial crisis and its aftermath. Some of that
criticism is warranted; but, in our view, much is not. This paper contributes to the debate
over the adequacy of benchmark DSGE models by showing how three extensions, which
are features that have characterized the global economy since the early 2000s, are
necessary to improve our understanding of global shocks and policy insights. The three
extensions are to acknowledge and model the entire global economy and the linkage
through trade and capital flows; to allow for a wider range of relative price variability by
moving to multiple sector models rather than a single good model; and to allow for
changes in risk perceptions which propagate through financial markets and adjustments
in the real economy. These extensions add some complexity to large scale macromodels,
but without them policy models can oversimplify things, allowing
misinterpretations of shocks and therefore costly policy mistakes to occur. Using oversimplified
models to explain a complex world makes it more likely there will be “puzzles”.
The usefulness of these extensions is demonstrated in two ways; first, by briefly
revisiting some historical shocks to show how outcomes can be interpreted that make
sense within a more complex DSGE framework; then, by making a contemporary
assessment of the implications from the proposed large fiscal stimulus and the bans on
immigration by the Trump administration which have both sectoral and macroeconomic
implications that interact.