Open research infrastructure
Research Notebook Lab
Reproduce the published analyses with downloadable Python notebooks, public inputs, and validation checks. Each notebook records its sources and interpretation limits.
Notebook execution route
Merger review: public rows become reviewable codeSecond Request rate from Federal Trade Commission and U.S. Department of Justice- Notebooks
- 7
- executable packets
- API routes
- 14
- public JSON inputs
- Default rows
- 2,193
- bounded observations
- Artifacts
- .ipynb
- downloadable source
Reproduce the analysis, not a conclusion.Each notebook keeps its declared dataset, entity universe, period, source custody, and interpretation boundary. Recipes never combine unlike metrics into a composite market-power score.
Download active notebookHSR report panel / 137 rows / Python 3
Federal merger review pipeline
How do the annual, fiscal-month, and transaction-size panels reproduce the federal HSR review pipeline across FY2016-FY2025?- Default rows
- 137
- 10 annual / 120 monthly / 7 size rows
- Code cells
- 7
- parameterized + bounded
- Source review
- Jul 18, 2026
- Federal Trade Commission and U.S. Department of Justice
- Output
- Trend
- Federal HSR pipeline reproduction packet
Executed result contract
Federal HSR pipeline reproduction packet
InputHSR report panel / 137 rows
Validate6 assertions
AnalyzeSecond Request rate
Publish.ipynb + figure
Parameter ledger
Defaults remain editable in the notebook- Fiscal years
- FY2016-FY2025
- Evidence panel
- 10 annual + 120 monthly + 7 size rows
- Rate denominator
- adjusted HSR transactions
Research handoff
From public rows to reviewable evidence.
Every notebook keeps the endpoint grammar visible, checks the fields it consumes, produces one bounded figure, and routes the result back to live profiles and methods.
Open public briefings