Many of the models we currently have available are not only mathematically sophisticated, but their results are obtained by computer-based calibrations whose essential mechanisms lack transparency when it comes to revealing how they arrive at their results. Hence, it is difficult to assess their consistency. We have often come across complicated models where an apparently innocuous condition ends up being the determinant of the results. Complexity also jeopardizes the capacity to move from scientific research to economic policy proposals. For academic ideas to be useful in economic policy, they must be persuasive. Perhaps that was the virtue of the IS-LM model that was used for many years in macroeconomic policy discussions, or of Solow’s growth model that to this day remains the cornerstone of economic growth research. Fortunately, this is not a time where prescriptions are taken by policy makers without scrutiny – and are later labeled as orthodox – and therefore, the capacity to intuitively explain a result is essential. The bulk of theoretical research will continue to proceed in areas where its results have a good chance of being published, often at the expense of realism. It may not be very profitable from the academic point of view to incorporate elements of irrational behavior, confidence crises or other anomalies into general equilibrium models that are used in policy design.
It is harder and less rewarding for an academic to formulate distortions – of which the real world has plenty – than to use tidy competitive models to explain important stylized facts with a minimum of new ingredients. Scientific advances and models help us think about and interpret the world; they provide us a way to think about specific problems, but their scope is limited. We must avoid the temptation of thinking that a theoretical simplification is a full description of reality. But we must also avoid the other extreme, which totally dismisses what theory teaches because “reality is much more complex”. This is true, but it does not imply that all we have learned is just a theoretical exercise without practical use in reality. Models must be taken realistically, recognizing that they capture at most a small portion of reality. As for the future, the current crisis will certainly provide material for many research studies that will try to figure out what failed and how to avoid making the same mistakes again. Still, I think it will be difficult to develop simple, manageable models that can make substantive progress in having a complete description of reality. Some interesting efforts will most likely be made, but it will not be easy for them to become part of the heart of macroeconomics, since they will be necessarily complex.