# mode: empirical discipline: economics title: ""

# Research brief — (empirical)

# 1. Research objective and scope

• Question. <e.g., Does X affect Y in population P over period T?>
• Hypotheses. H1: <…>. H0 is a real possibility: a well-identified null result is a valid outcome.
• Scope and unit of analysis. <firms/countries/households…; frequency; sample window>.

# 2. Domain, mode and methodology

• Discipline: <economics/finance/statistics/…>. Primary mode: empirical.
• Methodology: <OLS/panel FE/DiD/IV/event study/GARCH/ML forecasting…>, chosen because .
• Inference: <clustered/robust SE, bootstrap, multiple-testing policy>.

# 3. Contribution and novelty

• <Expected contribution; the 3–5 closest papers to position against.>

# 4. Literature and source rules

• Indexes: OpenAlex + Crossref (+ Semantic Scholar). Target ≥ 15 verified sources; must-read: .
• Map every background claim to a verified key.

# 5. Data

• Sources: <exact dataset/API/series ids, e.g., FRED series XYZ; World Bank indicator ABC; SEC EDGAR filings; public Kaggle/Zenodo DOI>. Only legally usable, documented data; record license and access date.
• Construction: <variable definitions, cleaning rules, sample selection, treatment of missing values and outliers>.
• Size limits: keep raw + derived data under 200 MB in the workspace (subsample and document if larger).
• No synthetic data unless explicitly allowed here: <allowed/not allowed>.

# 6. Procedure (pre-registered)

1. Data acquisition and manifest (data/manifest.json, SHA-256, license).
2. Descriptive statistics table and at least one figure of the raw series/distribution.
3. Main specification(s): <exact equations/models, controls, fixed effects, sample>.
4. Secondary/exploratory analyses: <…> (label as exploratory).
5. Write code/reproduce.sh regenerating all tables/figures/metrics from raw inputs; log every run.

# 7. Baselines, robustness and falsification

• Robustness: <alternative controls, windows, estimators, placebo/pre-trend tests, leave-one-out, winsorization>.
• Report robustness results that weaken the finding. State what would falsify H1.

# 8. Reproducibility and artifacts

• Pinned environment (uv), seeds, results/experiment-log.jsonl, results/metrics.json with every reported value registered.

# 9. Manuscript

• AutoScholar class; tables with units/notes/standard errors; figures with legible axes; 10–20 pages.

# 10. Review and revision

• Reviewer focus: identification threats, standard-error validity, data leakage, p-hacking signals, claim-to-evidence gaps.

# 11. Limitations, ethics, legal

• <Measurement error, external validity, data license constraints; no personal data.>

# 12. Acceptance criteria

• Main specification estimated on the full sample with CIs; ≥ 3 robustness checks; reproduction script regenerates metrics.json; ≥ 15 verified citations; limitations stated.