The Targeted Assignment of Incentive Schemes

46 Pages Posted: 17 Apr 2022

See all articles by Saskia Opitz

Saskia Opitz

University of Cologne

Dirk Sliwka

University of Cologne - Faculty of Management, Economics and Social Sciences; IZA Institute of Labor Economics

Timo Vogelsang

Frankfurt School of Finance & Management

Tom Zimmermann

University of Cologne

Date Written: April 7, 2022

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

JEL Classification: C21, C93, M52

Suggested Citation

Opitz, Saskia and Sliwka, Dirk and Vogelsang, Timo and Zimmermann, Tom, The Targeted Assignment of Incentive Schemes (April 7, 2022). Available at SSRN: https://ssrn.com/abstract=4077778 or http://dx.doi.org/10.2139/ssrn.4077778

Saskia Opitz

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Dirk Sliwka

University of Cologne - Faculty of Management, Economics and Social Sciences ( email )

Richard-Strauss-Str. 2
Cologne, D-50923
Germany

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Timo Vogelsang (Contact Author)

Frankfurt School of Finance & Management ( email )

Sonnemannstra├če 9-11
Frankfurt
Germany

Tom Zimmermann

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
161
Abstract Views
636
Rank
281,371
PlumX Metrics