Predicting Experimental Results: Who Knows What?

S-Tier
Journal: Journal of Political Economy
Year: 2018
Volume: 126
Issue: 6
Pages: 2410 - 2456

Authors (2)

Stefano DellaVigna (not in RePEc) Devin Pope (University of Chicago)

Score contribution per author:

4.022 = (α=2.01 / 2 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:ucp:jpolec:doi:10.1086/699976
Journal Field
General
Author Count
2
Added to Database
2026-01-25