Life is nothing but a series of decisions. Add your decisions to everyone in your country and you get the economy. Add all decisions human beings make together and you get the global economy.
In a perfect world, we would have knowledge and information at hand to make the best decisions given the opportunities we have. Unfortunately, even in the information age, we face significant uncertainty and gaps in our knowledge.
For one, we do not know (nor can we necessarily anticipate well) the choices of others, which is a key input into our own choices. Sometimes having too many choices or too much information to process prevents us from making the choice that is right for us.
The problem is even more urgent at a policymaking level. Policymakers want to learn about the choices people will make, given the options that they can set before them.
But the individual choices people make in part depend on what policies the policymaker is considering now and in the future. For example, voters can decide to behave in one way rather than another to influence a policy choice. Moreover, sometimes people make mistakes from the perspective of an outside observer and behave in ways that seem against their own interests.
Economics tries to bring order to this chaos. The natural benchmark to study is when everyone has all the necessary information and knows that everyone knows that fact, i.e., the common knowledge of rationality.
But this is just the starting point. From there, economists study the theoretical outcomes when we strip information and rationality away bit by bit. We then put these predictions to the test using data collected by firms, NGOs, government agencies, laboratory and field experiments, and our own surveys.
Through theory and evidence, we can build nuanced models of the world and the decision-making processes that underpin it. These models allow us to study policy and policy outcomes.
Economics also relies on natural experiments to causally determine the impacts of policy. Natural experiments are happy accidents where unintentionally a policy has created the conditions of an experiment. Using these events, we can measure the impact of policies that otherwise are unknown.