We use cookies to provide you with the best possible website experience. This includes cookies that are necessary for the operation of the site, as well as cookies used for anonymous statistics, comfort settings, or displaying personalized content. You can decide which categories you want to allow. Please note that depending on your settings, some features of the website may not be available.

Cookie settings

These necessary cookies are required to enable the core functionality of the website. Opting out of these cookies is not possible.

cb-enable
This cookie stores the user's cookie consent status for the current domain. Expiry: 1 year.
laravel_session
Stores the session ID to recognize the user when the page reloads and to restore their login session. Expiry: 2 hours.
XSRF-TOKEN
Provides CSRF protection for forms. Expiry: 2 hours.
IZA Discussion Paper No. 15496
August 2022
Social Preferences and Rating Biases in Subjective Performance Evaluations
David Kusterer, Dirk Sliwka

We study the determinants of biases in subjective performance evaluations in an MTurk experiment to test the implications of a standard formal framework of rational subjective evaluations. In the experiment, subjects in the role of workers work on a real effort task. Subjects in the role of supervisors observe subsamples of the workers' output and assess their performance. We conduct 6 experimental treatments varying (i) whether workers' pay depends on the performance evaluation, (ii) whether supervisors are paid for the accuracy of their evaluations, and (iii) the precision of the information available to supervisors. In line with the predictions of the model of optimal evaluations we find that ratings are more lenient and less accurate when they determine bonus payments and that rewards for accuracy reduce leniency. When supervisors have access to more detailed performance information their ratings vary to a stronger extent with observed performance. In contrast to the model's prediction we do not find that more prosocial supervisors always provide more lenient ratings, but that they invest more time in the rating task and achieve a higher rating accuracy.

Kommunikation
Mark Fallak
mark.fallak@liser.lu
+352 585-855-526
World of Labour
Olga Nottmeyer
olga.nottmeyer@liser.lu
+352 585-855-501
Netzwerkkoordination
Christina Gathmann
christina.gathmann@liser.lu

Das IZA@LISER-Netzwerk ist eine weltweite Gemeinschaft für exzellente Forschung in der Arbeitsmarktökonomie und angrenzenden Fachgebieten. Nach dem Wechsel von Bonn wird das Netzwerk nun am Luxembourg Institute of Socio-Economic Research (LISER) koordiniert.

Über das IZA@LISER Network
Contact
IZA Network (Current Site Operator):

Luxembourg Institute of Socio-Economic Research (LISER)
11, Porte des Sciences
Maison des Sciences Humaines
L-4366 Esch-sur-Alzette / Belval, Luxembourg

IZA Institute (In Liquidation):

Forschungsinstitut zur Zukunft der Arbeit GmbH i. L.
Schaumburg-Lippe-Str. 5-9, 53113 Bonn. Germany
Phone: +49 228 3894-0 | Fax: +49 228 3894-510
E-Mail: info@iza.org | Web: www.iza.org
Represented by: Martin T. Clemens (Liquidator)