Replication code for the study 'Apparent thermal tipping points in fisheries economics are statistical artifacts of extreme events' is available. The code was authored by Guiñares, Recamar and is hosted by Harvard Dataverse. It was last updated on July 2, 2026.
Use Cases
- Replicate statistical models for fisheries economics based on the described study
- Analyze the relationship between temperature extremes and economic outcomes based on the study's methodology
- Test the robustness of reported thermal tipping points in ecological economics
Strengths
- Code is directly linked to a specific, named academic study
- Hosted on the Harvard Dataverse platform, suggesting institutional backing
- Last updated on July 2, 2026, indicating recent maintenance
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
Provenance
- Source
- Harvard Dataverse
- Freshness
- Last updated 2026-07-02 19:20:29