Open AccessOptimal incentive contract with endogenous monitoring technology
Author(s) -
Li Anqi,
Yang Ming
Publication year - 2020
Publication title -
theoretical economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.404
H-Index - 32
eISSN - 1555-7561
pISSN - 1933-6837
DOI - 10.3982/te3130
Subject(s) - incentive , moral hazard , microeconomics , complete information , principal (computer security) , information asymmetry , partition (number theory) , computer science , process (computing) , economics , business , industrial organization , operations research , computer security , mathematics , combinatorics , operating system
Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer's strategic planning. In otherwise standard principal–agent models with moral hazard, we allow the principal to partition agents' performance data into any finite categories, and to pay for the amount of information the output signal carries. Through analysis of the trade‐off between giving incentives to agents and saving the monitoring cost, we obtain characterizations of optimal monitoring technologies such as information aggregation, strict monotone likelihood ratio property, likelihood ratio–convex performance classification, group evaluation in response to rising monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk. We examine implications of these results for workforce management and firms' internal organizations.