One of many economists’ primary goals is to model and (hopefully) predict real-world outcomes. Want to examine the impact of an oil shortage on food prices? Build a model of the economy which incorporates these markets, and see what happens.
Naturally, the devil is in the details. Precisely how the model is constructed can greatly influence its prediction. In particular, do we know enough about how individuals make economic decisions to build a model that accurately describes those decisions? After all, economics is a social science. And sometimes, people don’t behave in the ways we think they will. Combine hundreds of millions of them in one economy, and the power of prediction can seem pretty work.
This is why many economists, philosophers of science, and other interested observers, like Alex Rosenberg and Tyler Curtain at The Stone, are asking questions like What Is Economics Good For? Unlike other sciences, they argue, the “science” of economics lacks a consistent set of predictable principles, insofar as it may not be wholly accurate to call economics a science at all:
When we put a satellite in orbit around Mars, we have the scientific knowledge that guarantees accuracy and precision in the prediction of its orbit. Achieving a comparable level of certainty about the outcomes of an economy is far dicier.
The fact that the discipline of economics hasn’t helped us improve our predictive abilities suggests it is still far from being a science, and may never be. Still, the misperceptions persist. A student who graduates with a degree in economics leaves college with a bachelor of science, but possesses nothing so firm as the student of the real world processes of chemistry or even agriculture.
This isn’t to say that what one learns in economics is not useful and powerful; but, rather, that it differs from the concrete and scientific knowledge acquired in the natural science. Economic models can provide a great deal of insight, but do not produce the universal or consistent laws we often think they do.
Why? One culprit they identify is human unpredictability:
Unlike the physical world, the domain of economics includes a wide range of social “constructions” — institutions like markets and objects like currency and stock shares — that even when idealized don’t behave uniformly. They are made up of unrecognized but artificial conventions that people persistently change and even destroy in ways that no social scientist can really anticipate. We can exploit gravity, but we can’t change it or destroy it. No one can say the same for the socially constructed causes and effects of our choices that economics deals with.
This doesn’t mean economics is useless – and Rosenberg and Curtain ultimately agree. Quite the contrary! What it does mean is that studying economics is tricky. We need to understand our models and their relationship with the real world very closely. Under what conditions will our model make sense? When will its predictions fail? And, we need to be humble. Economic thinking can contribute greatly to improve economic and social institutions, align systems of incentives, and fine-tune economic decision making – but we should be cautious with our models. We may anticipate the people in our models behaving one way, but the ones in the real world may have something else entirely in mind.
[(9/2) EDIT: Some great comments discussing the article above emerged in the NY Times editorial section. Read them here.]