Relational Contracts, Multiple Agents, and Correlated Outputs

Ola Kvaløy and Trond E. Olsen ()
Additional contact information
Trond E. Olsen: Department of Business and Management Science, Norwegian School of Economics, 5045 Bergen, Norway

Management Science, 2019, vol. 65, issue 11, 5360-5370

Abstract: We analyze relational contracts between a principal and a set of risk-neutral agents whose outputs are correlated. When only the agents’ aggregate output can be observed, a team incentive scheme is shown to be optimal, where each agent is paid a bonus for aggregate output above a threshold. We show that the efficiency of the team incentive scheme depends on the way in which the team members’ outputs are correlated. The reason is that correlation affects the variance of total output and thus, the precision of the team’s performance measure. Negatively correlated contributions reduce the variance of total output, and this improves incentives for each team member in the setting that we consider. This also has implications for optimal team size. If the team members’ outputs are negatively correlated, more agents in the team can improve efficiency. We then consider the case where individual outputs are observable. A tournament scheme with a threshold is then optimal, where the threshold depends on an agent’s relative performance. We show that correlation affects both the efficiency and design of the optimal tournament scheme.

Keywords: relational contracts; performance evaluation; incentives; teams (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1287/mnsc.2018.3162 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:65:y:2019:i:11:p:5360-5370

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().