Sample average approximation for the continuous type principal-agent problem
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Authors
Singham, D.I.
Subjects
Pricing
Mechanism design
Principal-agent models
Sample average approximation
Mechanism design
Principal-agent models
Sample average approximation
Advisors
Date of Issue
2019-06
Date
Publisher
Elsevier B.V.
Language
Abstract
We develop a method for finding approximate solutions to the continuous agent type principal-agent
problem when analytical methods are not available. The solution is calculated by solving a discrete agent
type version of the problem using sample average approximation and bootstrapping. We show how a solution to the approximate problem can be used to derive a lower bound and expected upper bound for
the optimal objective function, and evaluate the error associated with the approximation. Numerical examples illustrate convergence in the approximate solution to the true solution as the number of samples
increases. This works yields a method for obtaining some tractability in continuous type principal-agent
problems where solutions were previously unavailable.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1016/j.ejor.2018.12.032
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
National Science Foundation grant CMMI-1535831
Format
8 p.
Citation
Singham, Dashi I. "Sample average approximation for the continuous type principal-agent problem." European Journal of Operational Research 275.3 (2019): 1050-1057.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.