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Motivations, monitoring technologies, and pay for performance

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  • Cordella, Antonio
  • Cordella, Tito

Abstract

Monitoring technologies and pay for performance (PFP) contracts are becoming popular solutions to improve public services delivery. Their track record is however mixed. To show why this may be the case, this paper develops a principal agent model where agents’ motivations vary and so the effectiveness of monitoring technologies. In such a set-up, it shows that: (i) monitoring technologies should be introduced only if agents’ motivations are poor; (ii) optimal PFP contracts are non-linear/non-monotonic in agents’ motivations and monitoring effectiveness; (iii) investments aimed at improving agents’ motivations and monitoring quality are substitutes when agents are motivated, complements otherwise; (iv) if the agents’ “type” is private information, the more and less motivated agents could be separated through a menu of PFP/non-PFP contracts, designed in a way that only the less motivated ones choose the PFP.

Suggested Citation

  • Cordella, Antonio & Cordella, Tito, 2017. "Motivations, monitoring technologies, and pay for performance," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 236-255.
    • Handle: RePEc:eee:jeborg:v:133:y:2017:i:c:p:236-255
    DOI: 10.1016/j.jebo.2016.10.016
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    More about this item

    Keywords

    Pay for performance; Public sector management; Information and communication technologies; Asymmetric information; Motivations; Optimal contracts;
    All these keywords.

    JEL classification:

    • M52 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Compensation and Compensation Methods and Their Effects
    • J33 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Compensation Packages; Payment Methods
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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