Predicting Experimental Results: Who Knows What?

• 成果类型: Article
• 署名作者: DellaVigna, Stefano; Pope, Devin
• 署名单位: University of California System; University of California Berkeley; National Bureau of Economic Research; University of Chicago
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/699976
• 发表日期: 2018
• 页码: 2410-2456
• 关键词: markets

摘要

We analyze how academic experts and nonexperts forecast the results of 15 piece-rate and behavioral treatments in a real-effort task. The average forecast of experts closely predicts the experimental results, with a strong wisdom-of-crowds effect: the average forecast outperforms 96 percent of individual forecasts. Citations, academic rank, field, and contextual experience do not correlate with accuracy. Experts as a group do better than nonexperts, but not if accuracy is defined as rank-ordering treatments. Measures of effort, confidence, and revealed ability are predictive of forecast accuracy to some extent and allow us to identify superforecasters among the nonexperts.