Consider two rationales for building models:
(a) Build a model in order to clarify the signal by filtering out the noise in a complex causal system. This is a knowledge-seeking endeavor.
(b) Build a model in order to be able to say, “In setting X, I can show how you get outcome Y.” This is just playing a game.
An example of playing a game is Akerlof’s Lemons model. In effect, it says, “In a setting where sellers know the quality of the product and buyers do not, sellers of high-quality products will have to settle for low prices, if they choose to sell at all.”
1. I am pretty sure that economists are unique in their attachment to model-building as a game. My sense is that in other disciplines, including those that study human behavior and those that use non-mathematical models, researchers are more likely to be building models in order to try to separate the signal from the noise in a complex causal system.
2. Countless papers begin by describing a setting as having two factors of production, capital and labor, before adding further wrinkles to the setting. From the knowledge-seeking perspective, I fear that this is a dubious strategy. The two-factor model gets rid of a lot of signal and introduces a lot of noise. But for playing the game (and getting published) it works well.
3. Economists who work in business (think of Hal Varian at Google) do not have the luxury of playing games. If they want to use models to help the firm, they need to build them with the goal of separating signal from noise.