 Minimizing learning in repeated real-effort tasksVolker Benndorf, Holger A. Rau and Christian Sölch Journal of Behavioral and Experimental Finance, 2019, vol. 22, issue C, 239-248 Abstract: In this paper, we discuss learning behavior and the heterogeneity of subjects’ ability to perform in real-effort tasks. We present a task, which aims to minimize learning in repeated settings. In the task participants encrypt words into numbers. We randomize the numbers in the allocation table and the position of the words in the table after a puzzle was solved. We report data where subjects work repeatedly in the task for ten periods. We find a very weak learning behavior of 2% between periods 1–5 and periods 6–10 of the data. The data demonstrate that subjects show a small heterogeneity in performance. Our results also show that women perform better in the task. Hence, the task is also adequate for settings, which aim to analyze gender settings where female participants have an advantage. This may be helpful as many tasks find a male advantage or no gender difference. Keywords: Experimental methods; Learning behavior; Real effort (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:beexfi:v:22:y:2019:i:c:p:239-248 DOI: 10.1016/j.jbef.2019.04.002 Access Statistics for this article Journal of Behavioral and Experimental Finance is currently edited by Michael Dowling and Jürgen Huber More articles in Journal of Behavioral and Experimental Finance from Elsevier |
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