External pipelines · RISE project catalogue
StatsPAI
An "agent-native" Python library for causal inference and applied econometrics — a Stata/R-replacement workbench (regress, ivreg, feols, Callaway-Sant'Anna DiD, rdrobust, synthetic control, matching, DML, meta-learners, causal forests, structural estimation; 1,145 registered functions across 87 submodules) whose structured result objects, machine-readable schemas, and MCP server are designed for LLM agents to call. Sits in the infrastructure-for-pipelines layer of RISE, like ToolUniverse, not a research pipeline itself.
Where it sits
left: what it builds on · right: what builds on it · pale: exampleContributed by Biaoyue, Scott Rozelle
How studies reach it
No published study reaches it yet.
Disciplines it reaches
No study reaches it yet.
Solid: published studies. Light: examples.
Computed from the records on this site: what each study, template and specialist names as used, which study extends which, and who contributed what. 0 studies in total.
What it does
The catalog's clearest case of tooling redesigned *for* agents rather than agents wrapped around tooling: one `import statspai as sp` entry point, `.to_agent_summary()` / `.to_latex()` / serialization on every result object, an MCP server, and a validation-tiered registry that records per-estimator R/Stata reference-parity status separately from API breadth — explicitly so that surface area is not passed off as validation evidence.
- Focus
- analysis
- Inputs
- user-dataset, model-formula
- Outputs
- estimation-results, publication-tables, figures
- Maintained by
- Biaoyue (Bryce) Wang (Stanford REAP); Scott Rozelle (Stanford REAP)
- Started
- 2025
Description
Data model- Discipline
- Economics
- Method family
- not specified
- Design
- not specified
- Research stage
- Data analysis
- Contributors
- Biaoyue; Scott Rozelle
- Usage
- not used in published research yet
- Source
- RISE project catalogue · projects/landscape · @4c17bae
- Record
- pipeline:statspai · JSON
Solid tags are declared by the source or mapped from its terms; dashed tags are inferred by a published rule. Hover a tag for its provenance.
Bring it into the standard
A pipeline built outside E2ER can meet the standard by describing its steps as a template, attaching the floor of checks and publishing evaluation records. Its authors keep ownership and credit.