Economists take their inspiration from exactly the kinds of observations that we have discussed. Economists look at the world around them—from the transactions in fast-food restaurants to the policies of central banks—and try to understand how the economic world works. This means that economics is driven in large part by data. In microeconomics, we look at data on the choices made by firms and households. In macroeconomics, we have access to a lot of data gathered by governments and international agencies. Economists seek to describe and understand these data.
But economics is more than just description. Economists also build models to explain these data and make predictions about the future. The idea of a model is to capture the most important aspects of the behavior of firms (like KFC) and individuals (like you). Models are abstractions; they are not rich enough to capture all dimensions of what people do. Yet a good model, for all its simplicity, is still capable of explaining economic data.
And what do we do with this understanding? Much of economics is about policy evaluation. Suppose your national government has a proposal to undertake a certain policy—for example, to cut taxes, build a road, or increase the minimum wage. Economics gives us the tools to assess the likely effects of such actions and thus to help policymakers design good public policies.
This is not really what you thought economics was going to be about when you walked into your first class. Back then, you didn’t know much about what economics was. You had a vague thought that maybe your economics class would teach you how to make money. Now you know that this is not really the point of economics. You don’t have any more ideas about how to get rich than you did when you started the class. But your class has taught you something about how to make better decisions and has given you a better understanding of the world that you live in. You have started to think like an economist.
Suppose you were building a model of pricing at KFC. Which of the following factors would you want to make sure to include in your model? Which factors do you think would be irrelevant?
