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Optimal Design of Policymaking Panels: Size Matters More Than Diversity for Accuracy
Insights from the Field
collective accuracy
organizational diversity
United States
regression discontinuity
Public Administration
AJPS
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Dataverse
Organizational Structure and the Optimal Design of Policymaking Panels: Evidence from Consensus Group Commission's Revenue Forecasts in the American States was authored by George A. Krause and James W. Douglas. It was published by Wiley in AJPS in 2013.

Collective policymaking panels in the United States often aim to improve accuracy by increasing size and diversity. This study shows that while these elements can enhance group capability, there's a crucial trade-off when they interact.

The research analyzes official revenue forecasts from state independent commissions with consensus group structures. Using regression discontinuity design, it finds an asymmetric effect: adding diversity to large panels reduces forecast accuracy significantly more than reducing diversity in small panels.

This discovery challenges simplistic prescriptions for improving panel performance. It reveals that the relationship between size and diversity is complex:

• Increasing diversity improves accuracy in small groups by about 25%

• But adds error rates nearly fourfold in large groups

Policy implications suggest careful calibration of these characteristics to maximize collective judgment quality.

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