Econometric Analysis with Real Data
10 weeks · 0 milestones
Build and run an econometric model (regression or equivalent) on a real, named publicly available dataset (World Bank, FRED, ONS, or equivalent). Document your dataset source, model specification, results, and a limitations section naming the main threats to validity. Proof is your analysis output plus a methodology challenge session with a statistics or economics academic who questions at least one model assumption or specification choice — your written response addressing their challenge in full is a required part of the proof. The model code or methodology must be reproducible.
Milestone map
Milestone map
3 milestones
Select a real research question that can be addressed with econometric methods using a publicly available dataset — questions about the effect of a policy on an outcome, the relationship between economic variables, or the determinants of a social or economic outcome. Choose a dataset (World Bank Open Data, FRED, OECD.Stat, or similar), formulate a testable hypothesis, and specify the econometric model: OLS, IV, difference-in-differences, panel data, or logit/probit. Document why this model is appropriate for the question and what identification assumptions it relies on.
Proof required
Research design document (500+ words) covering the research question, dataset source and key variables, econometric model specification, justification for the model choice, and identification assumptions with a discussion of whether they are likely to hold.
What gets checked
- Research question is specific enough to produce a falsifiable empirical result
- Model choice is justified by the structure of the question and the data — not chosen because it is familiar
- Identification assumptions are stated specifically — not just 'OLS assumptions hold'