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November 2018 Shape Constraints in Economics and Operations Research
Andrew L. Johnson, Daniel R. Jiang
Statist. Sci. 33(4): 527-546 (November 2018). DOI: 10.1214/18-STS672

Abstract

Shape constraints, motivated by either application-specific assumptions or existing theory, can be imposed during model estimation to restrict the feasible region of the parameters. Although such restrictions may not provide any benefits in an asymptotic analysis, they often improve finite sample performance of statistical estimators and the computational efficiency of finding near-optimal control policies. This paper briefly reviews an illustrative set of research utilizing shape constraints in the economics and operations research literature. We highlight the methodological innovations and applications, with a particular emphasis on utility functions, production economics and sequential decision making applications.

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Andrew L. Johnson. Daniel R. Jiang. "Shape Constraints in Economics and Operations Research." Statist. Sci. 33 (4) 527 - 546, November 2018. https://doi.org/10.1214/18-STS672

Information

Published: November 2018
First available in Project Euclid: 29 November 2018

zbMATH: 07032828
MathSciNet: MR3881207
Digital Object Identifier: 10.1214/18-STS672

Rights: Copyright © 2018 Institute of Mathematical Statistics

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Vol.33 • No. 4 • November 2018
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