Achim Ahrens maintains this replication repository for the guide "An Introduction to Double/Debiased Machine Learning." The repository was last updated on April 14, 2026, on the Harvard Dataverse platform. Its primary purpose is to provide the data and code necessary to reproduce the examples and results from the associated educational material.
Use Cases
- Replicate econometric examples based on the methods described in the companion guide.
- Validate double/debiased ML estimation techniques using the provided replication data.
- Learn practical implementation of debiased machine learning for causal inference.
- Benchmark new causal inference algorithms against the guide's established examples.
Strengths
- Repository is directly linked to a published educational guide on a specific methodology.
- Last update timestamp is precisely recorded as 2026-04-14 20:47:28.
- Hosted on the authoritative Harvard Dataverse platform.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and file formats are unknown, which may limit suitability assessment.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Created as a replication repository for an educational guide.
- Time Range
- null
- Freshness
- Last updated 2026-04-14 20:47:28; freshness should be verified.
- Geography
- null