Revise Economics as a social science and the role of models for IB Economics (1.2)

Economics is a social science, not a natural science. Natural sciences such as physics and chemistry study the physical world, where researchers can usually run controlled experiments — changing one variable while holding everything else fixed — to establish reliable laws. Economics instead studies the choices of people: individuals, firms and governments deciding how to use scarce resources. Its subject matter is human behaviour, and that changes everything about its method.

The central difficulty is that you cannot run a clean controlled experiment on a whole economy. You cannot find two identical countries, cut taxes in one, and hold every other influence constant to measure the pure effect. People also have free will and expectations, so they may react to a policy in ways that undermine the very prediction being tested. Because of this, economists lean on models and on the statistical analysis of real-world and historical data rather than on laboratory experiments.

Despite these limits, economics still applies the scientific method. An economist observes a phenomenon, forms a hypothesis about the relationship between variables, deduces a testable prediction from it, and then confronts that prediction with evidence. If the evidence contradicts the prediction, the hypothesis is revised or rejected; if it survives, confidence in the theory grows. The difference from the natural sciences is not the logic of the method but the testing ground: mostly observational data rather than controlled experiments.

Because the real world is overwhelmingly complex, economists use models: deliberately simplified representations of reality that capture the key variables and the relationships between them. A model such as demand and supply, or the production possibilities curve, throws away thousands of real details in order to make one mechanism visible. The skill of good modelling lies in choosing which details to ignore — a model is meant to be simpler than reality, not a copy of it.

Models are built on assumptions — conditions taken as given so the analysis stays manageable. The single most important assumption is ceteris paribus, Latin for 'all other things being equal'. It lets the economist change one variable and trace its effect while holding every other influence constant. For example, to study how the price of a good affects the quantity demanded, we assume consumer incomes, tastes and the prices of related goods do not change at the same time.

Conceptually: Quantity demanded ($Q_d$) = f(Price | ceteris paribus)

Assumptions are not a weakness to apologise for — they are what makes a model work. The test of an assumption is not whether it is literally true but whether the model built on it yields useful, testable predictions. Complaining that a model 'ignores' something real usually misses the point: it ignores that thing on purpose, precisely to isolate what it is trying to explain.

Standard economic models also assume rational economic decision-making: that people have clear objectives and choose the option that best achieves them, given their constraints. Consumers are assumed to maximise utility (satisfaction) from their limited income, and firms to maximise profit. This assumption is powerful because it makes behaviour predictable: if we know what people are trying to achieve, we can predict how they will respond when prices, incomes or incentives change.

A defining feature of thinking like an economist is separating positive from normative statements. Positive statements are objective and descriptive: they concern what is, was, or will be, and can be tested against evidence — 'the UK inflation rate was 9% in 2022'. Normative statements are subjective and prescriptive: they concern what ought to be and rest on value judgements that evidence cannot settle — 'the government ought to do more to control inflation'. Words such as should, ought, fair, unfair, too high and better usually flag a normative claim.

Positive economics rests on the idea of refutation. For a claim to be scientific, it must be possible to state what evidence would prove it false. A theory that no conceivable observation could contradict is empty — it explains nothing because it rules nothing out. Economists gain confidence in a theory when it repeatedly survives serious attempts to refute it, but surviving is never final proof: a future observation could still overturn it. This is why economic knowledge is always provisional and open to revision.

Models are indispensable but limited. Two limits stand out. First, ceteris paribus rarely holds in reality — several things usually change at once, so a model's prediction can be thrown off by a simultaneous shift the model held constant. Second, and more fundamentally, the rationality assumption is often violated. Behavioural economics has gathered strong evidence that people are only 'boundedly rational': they rely on rules of thumb, are swayed by how choices are framed, weigh losses more heavily than equivalent gains, and often care about fairness rather than pure self-interest.

The right conclusion is not that standard models should be thrown away. It is that they should be used with awareness of their limits and refined where the evidence demands it. The core insight — that people respond to incentives and prices — remains robust and useful. Behavioural economics sharpens the standard toolkit rather than replacing it, which is exactly how a healthy science absorbs refutation: by revising, not abandoning, its models.

The 2022 course is organised around nine key concepts. This lesson connects most directly to change — models exist to predict how outcomes change when one variable changes, ceteris paribus — and to efficiency in reasoning, since a good model achieves understanding with the fewest necessary assumptions. Being able to link a key concept to real-world material is specifically rewarded in the internal assessment, so practise naming the concept a piece of analysis illustrates. This lesson is identical at SL and HL; HL extension content begins in Unit 2.

Everything that follows in the course is model-building. Demand and supply, elasticity, market failure and macro policy are all simplified models resting on assumptions and analysed ceteris paribus, and every policy question invites both positive analysis (what will happen) and normative judgement (whether it should happen). The methodological habits you build here — isolate one variable, test your claims, keep facts and values apart, and stay alert to behavioural limits — are what turn a list of diagrams into genuine economic thinking.