IDEAS home Printed from https://ideas.repec.org/p/lmu/muenec/12222.html

Monitoring and Pay: An Experiment on Employee Performance under Endogenous Supervision

Author

Listed:
  • Dittrich, Dennis A. V.
  • Kocher, Martin G.

Abstract

We present an experimental test of a shirking model where monitoring intensity is endogenous and effort a continuous variable. Wage level, monitoring intensity and consequently the desired enforceable effort level are jointly determined by the maximization problem of the firm. As a result, monitoring and pay should be complements. In our experiment, between and within treatment variation is qualitatively in line with the normative predictions of the model under standard assumptions. Yet, we also find evidence for reciprocal behavior. Our data analysis shows, however, that it does not pay for the employer to solely rely on the reciprocity of employees.

Suggested Citation

  • Dittrich, Dennis A. V. & Kocher, Martin G., 2011. "Monitoring and Pay: An Experiment on Employee Performance under Endogenous Supervision," Discussion Papers in Economics 12222, University of Munich, Department of Economics.
  • Handle: RePEc:lmu:muenec:12222
    as

    Download full text from publisher

    File URL: https://epub.ub.uni-muenchen.de/12222/1/Dittrich_Kocher_2011_mimeo_Monitoring_and_Pay.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yongjin Wang & Laixun Zhao, 2013. "Saving Good Jobs under Global Competition by Rewarding Quality and Efforts," Discussion Paper Series DP2013-17, Research Institute for Economics & Business Administration, Kobe University, revised May 2013.
    2. Vera Mironova & Sam Whitt, 2017. "International Peacekeeping and Positive Peace," Journal of Conflict Resolution, Peace Science Society (International), vol. 61(10), pages 2074-2104, November.
    3. Charness, Gary & Kuhn, Peter, 2011. "Lab Labor: What Can Labor Economists Learn from the Lab?," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 3, pages 229-330, Elsevier.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lmu:muenec:12222. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tamilla Benkelberg (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.