economics as a social science

1. What is Economic Methodology?

Economic methodology is the set of tools, techniques and procedures that economists use to develop, test and apply theories about how societies allocate scarce resources to satisfy unlimited wants. As a social science, economics must deal with:

• Purposeful human behaviour
• Value‑judgements and normative questions
• The difficulty of carrying out controlled experiments

2. Core Features of a Social Science

• Human behaviour is purposeful and shaped by preferences, expectations and institutions.
• Variables are often inter‑dependent; controlled experiments are rarely possible.
• Values and normative judgments influence research questions, design and interpretation.
• Methodological pluralism – a mix of quantitative and qualitative approaches.

3. Positive vs. Normative Statements

Positive statements describe the world as it is – they are testable and fact‑based. Normative statements prescribe how the world ought to be – they contain value‑laden judgements.

4. Ceteris Paribus (All Other Things Being Equal)

The ceteris‑paribus assumption isolates the effect of one variable by holding all other relevant factors constant. It is essential for:

• Deriving clear relationships (e.g., the law of demand).
• Building tractable models.
• Testing hypotheses in empirical work.

Example: When analysing the impact of a price rise on the quantity demanded of coffee, we hold income, tastes and the price of tea constant.

Link to the rest of the syllabus: Ceteris‑paribus is used throughout micro‑ and macro‑analysis – demand‑supply curves, elasticity calculations, AD/AS shifts, and the analysis of fiscal and monetary policy.

5. Role of Assumptions & Limitations of Models

Economic models are simplified representations of reality. They rely on explicit assumptions that make analysis possible but also limit applicability. Students must be able to identify the key assumptions for each major model and critique them.

6. Methodological Pluralism (Approaches)

7. From Theory to Empirics – Step‑by‑Step Outline

1. Formulate a hypothesis (positive statement) – e.g., “An increase in government spending (G) raises national output (Y).”
2. Specify an econometric model using ceteris‑paribus – e.g., Y_t = α + β G_t + ε_t
3. Collect data – time‑series, cross‑sectional or panel.
4. Estimate parameters – OLS, GLS, etc.
5. Test the hypothesis – significance tests, confidence intervals, goodness‑of‑fit.
6. Interpret results – discuss assumptions and limitations.
7. Policy evaluation (normative) – combine positive findings with value judgements to decide whether the policy should be adopted.

8. Linking Positive Analysis to Policy Evaluation (AO3)

8.1 Policy‑evaluation box

8.2 Evaluation Checklist (AO3)

• Are the model’s assumptions realistic? (e.g., perfect information, competitive market)
• What are the distributional effects? (who gains, who loses?)
• Is the policy feasible and administratively practical?
• What is the time‑frame for the effects? (short‑run vs. long‑run)
• Are there any unintended consequences?
• How does the policy align with broader societal values (equity, sustainability, efficiency)?

8.3 Worked Example – Carbon Tax

1. Positive statement: “A £20 per tonne carbon tax will reduce national CO₂ emissions by 10 % in the first year.”
2. Ceteris‑paribus analysis: Hold energy demand, technology, and global oil prices constant; model the supply‑side response of electricity producers.
3. Empirical test: Use regression of emissions on tax rate across OECD countries, controlling for GDP per capita and energy mix.
4. Result: Coefficient is –0.05 (p < 0.01), confirming the hypothesised reduction.
5. Normative judgement:
   • Distribution: Low‑income households face higher energy bills.
   • Equity solution: Re‑channel tax revenue into a rebate for households earning below the median income.
   • Feasibility: Requires a robust monitoring system for emissions.
   • Value alignment: Supports the societal goal of combating climate change while protecting vulnerable groups.

9. The Role of Values in Research Design

• Choice of variables – a researcher who values equity may include Gini coefficient, whereas a growth‑oriented study might focus on GDP growth alone.
• Time‑horizon – short‑run analysis highlights immediate effects; long‑run studies reflect sustainability concerns.
• Distributional focus – deciding whether to analyse average effects or impacts on specific groups (e.g., low‑income households).

Making these value‑judgements explicit improves transparency and strengthens evaluation arguments.

10. Interdisciplinary Links

• Sociology: Social norms and institutions that shape economic behaviour.
• Psychology: Behavioural economics – systematic departures from rationality.
• Political Science: Institutional economics – the effect of political structures on markets.
• History: Historical context for long‑run trends and policy legacies.

11. Suggested Diagram

12. Summary

Economics, as a social science, blends theoretical abstraction with empirical investigation while recognising the inevitable role of values. Mastering the distinction between positive and normative statements, the ceteris‑paribus assumption, model assumptions and their limitations, and methodological pluralism equips students to analyse economic issues rigorously (AO1‑AO2) and to evaluate policies critically (AO3) – the core skills required for Cambridge International AS & A Level Economics.