Replication Data for a Constrained Priority Matching Mechanism

Replication data from Stanford University for a paper introducing a constrained priority mechanism. The mechanism combines machine-learning outcome predictions with preference-based matching, applied to refugee family and kindergarten student assignment. The data likely contains records for agents, preferences, and predicted outcome scores.

Use Cases

• Testing the constrained priority matching algorithm based on the described mechanism.
• Simulating refugee family assignments based on predicted employment probabilities mentioned in the description.
• Simulating student assignments to schools based on standardized test score thresholds described in the paper.
• Analyzing trade-offs between outcome efficiency and agent preferences in matching markets.

Strengths

• Data originates from a Stanford University research paper, suggesting academic rigor.
• The described mechanism is applied to two real-world contexts: refugee resettlement and school choice.

Limitations

• Row count and file size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Stanford University

Collection Method

Likely generated or collected for the research paper 'Combining Outcome-Based and Preference-Based Matching: A Constrained Priority Mechanism'.