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Minimizing Learning Behavior in Experiments with Repeated Real-Effort Tasks

19 Pages Posted: 1 Oct 2014  

Volker Benndorf

Heinrich Heine University Dusseldorf - Duesseldorf Institute for Competition Economics (DICE)

Holger Andreas Rau

University of Göttingen

Christian Sölch

University of Erlangen-Nuremberg-Friedrich Alexander Universität Erlangen Nürnberg

Date Written: September 2014

Abstract

In this paper, we introduce a new real-effort task which mitigates learning behavior in repeated real-effort tasks. In our task, participants need to encode three-letter words into numbers. The task is based on Erkral et al. (2011), however, in our version a double-randomization mechanism is applied to minimize learning. Existing experiments using repeated real-effort tasks report an increase of 15-30% in subjects' performance in the course of the experiment. By contrast, we find that when comparing performance in the first period with the last period, our task mitigates learning behavior down to 8%. The difference between the first and second half of the experiment is only about 3%.

Keywords: Experimental Methods, Learning Behavior, Real-Effort.

JEL Classification: C90, C91

Suggested Citation

Benndorf, Volker and Rau, Holger Andreas and Sölch, Christian, Minimizing Learning Behavior in Experiments with Repeated Real-Effort Tasks (September 2014). Available at SSRN: https://ssrn.com/abstract=2503029 or http://dx.doi.org/10.2139/ssrn.2503029

Volker Benndorf

Heinrich Heine University Dusseldorf - Duesseldorf Institute for Competition Economics (DICE) ( email )

Universitaetsstr. 1
Duesseldorf, NRW 40225
Germany

Holger Andreas Rau (Contact Author)

University of Göttingen ( email )

Platz der Göttinger Sieben 3
Göttingen, Niedersachsen 37073
Germany

Christian Sölch

University of Erlangen-Nuremberg-Friedrich Alexander Universität Erlangen Nürnberg ( email )

Lange Gasse 20
Nuremberg, Bavaria 90403
Germany

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