economics as a social science

Economic Methodology: Economics as a Social Science

Think of economics as a detective story 🔍. Instead of fingerprints, we use data and ideas to uncover how people, businesses, and governments make choices with limited resources.

1. What is Economic Methodology?

Methodology is the set of rules and tools we use to study the economy. It tells us how to gather evidence, test ideas, and draw reliable conclusions.

2. The Scientific Method in Economics

  1. Observation – Notice a pattern, e.g., higher prices → lower demand 📊.
  2. Question – Why does this happen?
  3. Hypothesis – Form a testable guess, e.g., “If price rises, quantity demanded falls.”
  4. Experiment / Data Collection – Gather real‑world data or run a controlled experiment.
  5. Analysis – Use statistical tools to see if the data support the hypothesis.
  6. Conclusion – Accept, reject, or refine the hypothesis.
  7. Communication – Share findings with others.

3. Empirical vs. Theoretical Approaches

ApproachWhat It DoesExample
TheoreticalBuilds models using assumptions to explain behaviour.Supply and demand curves showing equilibrium.
EmpiricalTests theories with real data.Regression of consumption on income.

4. Key Concepts: Causality, Correlation, and Counterfactuals

Causality means one thing actually causes another. Example: A tax cut causes increased spending.

Correlation is just a statistical relationship. Example: Ice cream sales and drowning incidents both rise in summer, but one does not cause the other.

Counterfactuals ask “what if” questions. For instance, “What would GDP be if the tax cut hadn’t happened?” This helps isolate causal effects.

Mathematically, we often write a simple causal model as:

\$ Y = \beta0 + \beta1 X + \epsilon \$

where \$Y\$ is the outcome, \$X\$ is the treatment, and \$\epsilon\$ captures other factors.

5. Common Pitfalls and How to Avoid Them

  • Confusing correlation with causation – Always ask for a mechanism or use methods like randomisation.
  • Over‑reliance on theory – Test predictions with data whenever possible.
  • Ignoring data quality – Check for missing values, outliers, and measurement error.
  • Misinterpreting statistical significance – A small p‑value doesn’t guarantee a big effect.

6. Exam Tips

Read the question carefully. Identify whether it asks for an explanation, a calculation, or a critique.

Use diagrams. A well‑labelled supply‑demand graph can earn you extra marks.

Show your work. Even if you’re unsure, write down the steps you would take.

Link theory to evidence. Mention relevant data or studies when answering.

Good luck! 🍀