Harvard Dataverse hosts replication data for the paper 'Information and learning in coordination games: Theory and experiment'. The dataset, authored by Xiaomeng Ding, provides the raw data and calculations used to generate the paper's tables and figures. It was last updated on March 25, 2026.
Use Cases
- Replicate statistical analyses and visualizations based on the raw data and calculations provided.
- Conduct secondary analysis on coordination game outcomes based on the experimental data.
- Validate theoretical models of learning in games using the empirical results.
- Benchmark new experimental designs against the provided data and methodology.
Strengths
- Data is directly linked to a published academic paper, providing clear context.
- Includes detailed calculations enabling full replication of the paper's results.
- Hosted on the authoritative Harvard Dataverse platform.
Limitations
- 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
- Likely collected from controlled laboratory experiments.
- Time Range
- null
- Freshness
- Last updated 2026-03-25 22:43:36; freshness should be verified.
- Geography
- null