Purpose
This skill helps economists generate and refine research questions by applying economic thinking frameworks. It guides the process from observing phenomena to formulating testable hypotheses.
When to Use
- Starting a new research project
- Brainstorming dissertation topics
- Finding angles for policy analysis
- Developing extensions of existing work
Instructions
Step 1: Understand the Starting Point
Ask the user:
- Do you have a phenomenon, puzzle, or data source in mind?
- What field/subfield of economics?
- What's your methodological preference? (Theory, empirical, structural)
- Any constraints? (Data access, timeline, etc.)
Step 2: Apply Ideation Frameworks
Use these approaches:
1. The Puzzle Approach
- What's surprising about current patterns?
- What contradicts conventional economic wisdom?
- Where do standard models fail?
2. The Policy Approach
- What policies lack rigorous evaluation?
- What natural experiments remain unexploited?
- What interventions might solve important problems?
3. The Data Approach
- What new data sources have become available?
- What can existing data tell us that hasn't been explored?
- What linkages between datasets are possible?
4. The Extension Approach
- How can seminal papers be extended?
- What mechanisms remain unexplored?
- Can methods from one field apply to another?
Step 3: Evaluate and Refine
For each idea, assess:
- Feasibility: Can this be done with available data/methods?
- Contribution: What's new here?
- Interest: Who cares about this question?
- Identification: Can effects be credibly estimated?
Example Interaction
User Query: "I'm interested in labor economics and have access to LinkedIn data"
Generated Response:
Research Ideas: LinkedIn Data × Labor Economics
1. Network Effects in Job Search
Question: How do professional networks affect job transitions and wage changes?
Puzzle: Standard search models assume random matching, but most jobs come through networks. How much do networks matter for outcomes?
Approach:
- Track profile updates signaling job changes
- Measure network overlap between current/future employers
- Instrument with exogenous network shocks (school alumni connections)
Contribution: Quantify the causal role of networks vs. unobserved ability
2. Skill Signaling and Returns
Question: Do workers who list specific skills on profiles earn wage premiums?
Puzzle: Are listed skills signals of ability, or just cheap talk? What's the return to skill acquisition vs. skill signaling?
Approach:
- Compare wages before/after workers add skills
- Use skill endorsements as validation
- Exploit skill assessment features as quasi-experiments
3. Gender Gaps in Self-Promotion
Question: Do men and women describe equivalent achievements differently?
Puzzle: Lab evidence shows women understate accomplishments. Does this appear in real profiles and affect outcomes?
Approach:
- NLP analysis of profile language (adjectives, quantification)
- Compare language for workers in same role/company
- Link to recruiter contact rates if available
4. Remote Work and Labor Market Geography
Question: How has remote work changed the geographic reach of job matching?
Approach:
- Compare pre/post-2020 job applications by distance
- Measure changes in location signals on profiles
- Study wage convergence across cities
Evaluation Matrix
| Idea | Data Feasibility | Identification | Policy Relevance |
|---|---|---|---|
| Network effects | High | Medium (need IV) | High |
| Skill signaling | High | Medium | Medium |
| Gender language | High | High (descriptive) | High |
| Remote geography | High | High (COVID natural experiment) | High |
Recommended Next Steps
- For empirical work: Start with Idea #4 (clearest identification)
- For policy impact: Idea #1 has most implications for job matching platforms
- For methodological novelty: Idea #3 combines NLP with quasi-experimental methods
Frameworks for Generating Questions
The "5 Whys" for Economics
Start with an observation and drill down:
- GDP growth is slowing → Why?
- Productivity is stagnant → Why?
- Investment is low → Why?
- Uncertainty is high → Why?
- Policy is unpredictable → Testable: Does policy uncertainty cause low investment?
The "What If" Generator
- What if [policy X] were implemented?
- What if [technology Y] became widespread?
- What if [assumption Z] were relaxed?
The Cross-Field Pollinator
Take a method from one field and apply to another:
- IO techniques → Labor markets (how do firms choose wages like prices?)
- Finance models → Education (returns to schooling as asset pricing)
- Macro shocks → Micro outcomes (firm-level effects of exchange rate changes)
Common Pitfalls
- ❌ Questions that are too broad ("What causes inequality?")
- ❌ Questions without clean identification ("Does education cause income?")
- ❌ Questions without data ("Were medieval peasants happy?")
- ❌ Questions already well-answered
References
- Shapiro (2022) How to Get Started on Research in Economics
- Angrist & Pischke on Mostly Harmless research design
- AEA Research Pipelines
Changelog
v1.0.0
- Initial release with ideation frameworks