Economic models | Basic economics concepts | AP Macroeconomics and Microeconomics | Khan Academy

The field of economics is daunting due to millions or billions of actors (humans and organizations) interacting in incredibly complex ways. Predicting individual behavior is challenging, let alone the behavior of an entire economy.

Economics borrows the idea of models from other fields. In chemistry, for instance, understanding trillions of molecules in a container is simplified by making assumptions, leading to models like the ideal gas law. These models take complex phenomena and simplify them for understanding.

Biology also uses models. Since human experimentation can be unethical and humans are complex, biologists simplify problems by studying simpler organisms like individual cells, fruit flies, or mice. These 'mouse models' allow for drug testing and understanding processes before applying them to humans.

Economists employ the same approach, using simplifying assumptions. These include assumptions like all actors being rational or having perfect information, even though these are not entirely true in reality. Such assumptions allow economists to create models like the production possibility frontier or supply and demand curves.

Economic models are very useful for initial understanding, forming the basis of early economics education. However, it's crucial to acknowledge their simplifying assumptions and not treat them as absolute descriptions of reality. Nobel Prizes have been awarded for revisiting these assumptions and developing new models.

Unlike chemistry or even biology, economics faces difficulties in testing models in an absolute way. It's not possible to conduct controlled experiments by applying different policies to multiple identical economies, making validation more challenging.

Models are valuable across sciences, including economics. Economics, however, straddles social and natural sciences because experiments cannot be run in the same way. Simplifying assumptions, though not always perfectly true, are essential for making sense of the incredibly complex real world.