Economics Research Ideation Skill for ChatGPT: Turn Observations Into Testable Questions
Start with an economic phenomenon, dataset, or policy change. Generate observable mechanisms and competing explanations, then compare research questions by feasibility, identification, and contribution to existing work.
中文Install in ChatGPT
Use an eligible ChatGPT workspace with permission to create skills and, for uploads, upload permission. The installation path for this text-only adaptation was checked against OpenAI documentation. Workspace runtime verification is pending.
- Download _skills/ideation/research-ideation/SKILL.md from the pinned GitHub source. Keep the name, description, and instructions for research-ideation together as a standalone text skill.
- In a ChatGPT workspace with skills and uploads enabled, open Plugins, Skills, Create, and Upload from your computer. Choose a skill package format accepted by the file picker. You can also choose Create with editor and enter the original name, description, and instructions.
- After the scan completes, check that research-ideation appears in Installed. Type @ in a new chat, select the skill, and use the fictional example on this page to check the output.
Example task
Two fictional cities have weekly aggregate bus ridership and weather data. One cuts fares before summer break and the other leaves fares unchanged. Ask for two testable questions, directional hypotheses, missing data, and a first validation step.What to check
Each question should name the unit of analysis, time window, and outcome. The answer should flag the overlapping school break, propose a pre-trend check, and identify additional cities or historical data as follow-up evidence.
Original SKILL.md on GitHub · Updated
Frequently asked question
Can I draw a causal conclusion from one observation?
Use the observation to formulate a hypothesis with testable predictions and possible confounders. Causal identification depends on the comparison, data coverage, and research design.