Modelling a complex world: Improving macro-models

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.