Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/262349 
Year of Publication: 
2022
Series/Report no.: 
ECONtribute Discussion Paper No. 187
Publisher: 
University of Bonn and University of Cologne, Reinhard Selten Institute (RSI), Bonn and Cologne
Abstract: 
A central question in designing optimal policies concerns the assignment of individuals with different observable characteristics to different treatments. We study this question in the context of increasing workers' performance by using targeted incentives based on measurable worker characteristics. To do so, we ran two large-scale experiments. The key results are that (i) performance can be predicted by accurately measured personality traits, (ii) a machine learning algorithm can detect such heterogeneity in worker responses to different schemes, and (iii) a targeted assignment of schemes to individual workers increases performance in a second experiment significantly above the level achieved by the single best scheme.
Subjects: 
Randomized Controlled Trial
Incentives
Heterogeneity
Treatment Effects
Selection
Algorithm
Document Type: 
Working Paper

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