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Expertise and Prediction Accuracy

Elisabeth Grewenig, Gründler, Klaus, Philipp Lergetporer (), Niklas Potrafke, Katharina Werner and Helen Zeidler
Additional contact information
Elisabeth Grewenig: KfW, Frankfurt
Gründler, Klaus: University of Kassel
Philipp Lergetporer: Technical University of Munich
Niklas Potrafke: ifo Institute
Katharina Werner: Business School Pforzheim
Helen Zeidler: Technical University of Munich

No 18453, IZA Discussion Papers from IZA Network @ LISER

Abstract: Public support for policy interventions depends on citizens’ beliefs about their likely effects. We examine how individuals form such beliefs by studying their predictions of experimental outcomes in a policy-relevant setting, and why their predictions differ from expert benchmarks. We elicit forecasts from 127 professional economists and a representative sample of 6,200 German households about a large-scale behavioral experiment on education policy (N = 3, 133). Nonexperts predict both average outcomes and treatment effects far less accurately than experts. Prediction accuracy improves with calibrated priors, self-reported effort, and the use of structured reasoning, but remains well below expert levels. We show that scalable design features, including the provision of well-calibrated numerical anchors and monetary incentives to rise effort, improve non-expert predictions, with effects comparable in magnitude to tertiary education or structured reasoning. Our findings have important implications for bridging the ‘expertise gap’ in public discourse.

Keywords: expert forecasts; lay predictions; belief formation; expertise gap; policy support; behavioral experiments (search for similar items in EconPapers)
JEL-codes: A11 D83 H52 I22 (search for similar items in EconPapers)
Date: 2026-03
New Economics Papers: this item is included in nep-exp and nep-for
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