Research question and relevance
Question: How do causal mechanisms and heterogeneous treatment effects shape market outcomes and policy interventions in field-like datasets?
Credible policy evaluation requires more than a point estimate. The project connects identification assumptions, estimator recovery, heterogeneous effects, intervention allocation, and reporting so a decision can be traced back to evidence.
Original paper or report: CasualLab is a project-originated research toolkit; this release does not claim to reproduce a specific third-party paper without a documented citation and benchmark.
Data and sample
The public GitHub copy contains synthetic fixtures, NYC-oriented samples, schemas, and tests. The full versioned research content is stored under CasualLab/ in the Dataset.
| Record | Current evidence |
|---|---|
| Original sample period | Not applicable to synthetic fixtures; source-specific periods are documented per run. |
| Updated sample period | Published only with a documented public-data refresh. |
| Data availability | Compact fixtures on GitHub; full research payload on Hugging Face. |
Replication methodology
- Define the estimand and identification assumptions.
- Load an authorized source or documented fixture.
- Estimate average and heterogeneous effects.
- Run estimator-recovery and sensitivity checks.
- Publish outputs with provenance and a result manifest.
Robustness work includes alternative specifications, heterogeneous-effect recovery, placebo or synthetic checks where applicable, and explicit release boundaries.
Original, replicated, and updated results
| Result stage | Status | Interpretation |
|---|---|---|
| Original benchmark | Not asserted | No third-party benchmark is claimed without a citation and matched sample. |
| Replicated result | Fixture validated | Tests support workflow behavior, not an invented empirical magnitude. |
| Updated result | Versioned data available | A numerical update will appear only with a validated result manifest. |
Charts and summary tables are released with validated outputs. This page labels incomplete numeric evidence instead of displaying simulated findings as research results.
Reproduction and citation
Run make reproduce from the standalone repository. Cite the Observatory release, Dataset revision, CasualLab, and every original data provider used in a run.
Limitations
Raw third-party sources require source-level rights review. Numerical comparisons remain incomplete until a benchmark, sample, configuration, output manifest, and validation record are released.