title: CasualLab
slug: casuallab
summary: Experimental causal inference and policy simulation toolkit with NYC-oriented public examples.
research_question: How do causal mechanisms and heterogeneous treatment effects shape market outcomes and policy interventions in field-like datasets?
why_it_matters: Credible policy evaluation requires both transparent identification assumptions and reproducible decision rules.
research_fields:
  - Causal inference
  - Experimental economics
  - Market design
project_type: research-replication
status: public-live
authors:
  - Repository owner and maintainer
original_source: CasualLab workspace project
original_sample_period: Not applicable; the public package uses synthetic and open examples.
updated_sample_period: Updated when a documented public-data refresh is released.
data_sources:
  - Public synthetic or open policy data configured per run
  - Repository fixtures and NYC sample data
data_license: RIGHTS_UNKNOWN for raw third-party sources; included fixtures are publishable examples.
code_license: Project-local terms; third-party components retain their own licenses.
reproduction_command: make reproduce
expected_runtime: Varies by module and selected estimator.
outputs:
  - src/
  - reports/
  - scripts/
  - tests/
  - data/fixtures/
github_url: https://github.com/YangXiaoShawn/open-economic-quant-casuallab
site_url: https://yangxiaoshawn.github.io/projects/casuallab/
dataset_url: https://huggingface.co/datasets/ShawnChamberlain/open-economic-quant-research-data/tree/main/CasualLab
space_url: https://huggingface.co/spaces/ShawnChamberlain/open-economic-quant-research-observatory
last_updated: 2026-08-10
limitations: Numerical result comparisons are reported only when a source, sample, and validation record are available. Publication rights for new raw sources must be reviewed before release.
catalog:
  field: causal
  accent: teal
  tags:
    - Causal Inference
    - Policy Simulation
    - Heterogeneity
  metric: Reproducible fixtures