Economics
ec·o·nom·ics · oikos: household · nomos: management, law
Economics is a social science concerned with the production, distribution, and consumption of goods and services — and, underneath all of it, how people and societies make choices when resources are scarce.
- Anchor the project to a specific market, policy, or decision you can measure.
- Always ask “compared to what?” — a number needs a counterfactual.
- Correlation isn't causation; watch for the confounders that move both variables.
- Use public data and cite it; be clear about what your evidence can and can't show.
Related areas & concentrations
Economics overlaps with nearly every social science — and with psychology and philosophy on how people actually decide. Those neighbors are where you'll find data and framing.
Related research areas
- Politics & policy: Political Science, International Relations, History
- Society & mind: Sociology, Psychology, Education
- Ideas & practice: Philosophy and Business
Sample concentrations
- Judgement & decision-making: the science of how people actually choose
- Global economic governance: economics meets international relations, sociology & political science
- International economics: trade, exchange, and the global economy
Sample papers for economics are available — ask a mentor or check the journal for examples to model your own work on.
Four ways into a question
Most economics papers work through one of these lenses. For a student, the data-driven and behavioral ones are the most reachable.
Microeconomics
Individuals, firms, and markets — prices, incentives, and how single decisions add up.
How did a price change affect what students bought at the school store?
Macroeconomics
The whole economy — growth, inflation, unemployment, and the policies that steer them.
How does a country's education spending relate to its later GDP growth?
International & Development
Trade, exchange rates, global governance, and how economies develop.
Did a trade agreement change exports between the two countries involved?
Behavioral & Applied
How real people depart from “rational” models — tested with data or simple experiments.
Does framing a choice as a loss change what your classmates pick?
Turning an interest into a question
A topic isn't a research question. Narrow to one market or policy, one measurable outcome, and a comparison that makes the effect visible.
Start from data you can actually get
Public economic data — prices, wages, trade, growth — is free and vast. Pick something with a real dataset behind it.
Narrow to one outcome
Not “what causes inequality” but one wage, one price, one employment rate over a defined period.
Find your comparison
Before vs. after a policy, or a place that changed vs. one that didn't — that contrast is your evidence.
Plan for confounders
Ask what else could explain the pattern, and be honest about what your data can prove.
Methods & where to look
Economics runs on public data. Pair a method you can carry out with the datasets and papers economists actually use.
Common methods
- Data analysis: comparing trends across time or place, and simple regression.
- Natural experiments: a policy change that created a before/after or treated/untreated split.
- Surveys & experiments: testing how people decide (behavioral economics).
- Case & policy analysis: studying one program and its effects.
- Modeling: supply and demand and other simple frameworks.
A little spreadsheet or Python skill goes a long way with economic data.
Where to find data & papers
- Data: FRED (Federal Reserve), the World Bank, the OECD, and Our World in Data.
- US stats: the Bureau of Labor Statistics and the Census Bureau.
- Working papers: NBER and SSRN, plus Google Scholar.
- Journals: the Journal of Economic Perspectives is written to be readable.
FRED is a great starting point — thousands of charts you can download in seconds.
“Compared to what?”
The whole discipline turns on one question: what would have happened otherwise? Three habits keep your claims honest.
Measure
Define your outcome precisely and find a real, comparable number for it.
Counterfactual
Identify what you're comparing against — a before, or a group that didn't get the change.
Caution
List what else could explain the pattern. Correlation isn't causation, and confounders are everywhere.
Cite every dataset, and separate what the data shows from what you think it means.