The Targeted Assignment of Incentive Schemes

Saskia Opitz (), Dirk Sliwka (), Timo Vogelsang () and Tom Zimmermann
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Saskia Opitz: University of Cologne, Faculty of Management, Economics and Social Sciences, Department of Corporate Development
Dirk Sliwka: University of Cologne, Faculty of Management, Economics and Social Sciences, Department of Corporate Development
Timo Vogelsang: Frankfurt School of Finance & Management,Department of Accounting

No 187, ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany

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.

Keywords: Randomized Controlled Trial; Incentives; Heterogeneity; Treatment Effects; Selection; Algorithm (search for similar items in EconPapers)
JEL-codes: C21 C93 M52 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2022-08
New Economics Papers: this item is included in nep-big, nep-exp and nep-hrm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ajk:ajkdps:187

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