Journal ArticleDOI
Shape Constraints in Economics and Operations Research
TLDR
This paper briefly reviews an illustrative set of research utilizing shape constraints in the economics and operations research literature and highlights the methodological innovations and applications with a particular emphasis on utility functions, production economics and sequential decision making applications.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.read more
Citations
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Journal ArticleDOI
Order Restricted Statistical Inference.
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The collective model of household consumption: A nonparametric characterization
TL;DR: In this paper, the authors provide a nonparametric characterization of a general collective model for household consumption, which includes externalities and public consumption, and establish testable necessary and sufficient conditions for data consistency with collective rationality that only include observed price and quantity information.
Proceedings Article
Hard Shape-Constrained Kernel Machines
TL;DR: In this paper, the authors prove that hard affine shape constraints on function derivatives can be encoded in kernel machines, which represent one of the most flexible and powerful tools in machine learning and statistics.
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Multivariate Convex Regression at Scale
Wenyu Chen,Rahul Mazumder +1 more
TL;DR: This framework can solve instances of the convex regression problem with $n=10^5$ and $d=10$---a QP with 10 billion variables---within minutes; and offers significant computational gains compared to current algorithms.
References
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ReportDOI
Flexible Functional Forms and Global Curvature Conditions
W. Erwin Diewert,Terence Wales +1 more
TL;DR: In this paper, the authors developed two methods for imposing curvature conditions globally in the context of cost function estimation, based on a generalization of a functional form first proposed by McFadden.
Journal ArticleDOI
Statistical inference under order restrictions : the theory and application of isotonic regression
TL;DR: Isotonic regression under order restrictions has been used to test the equality of ordered means for goodness of fit as discussed by the authors, in the normal case and in the special case of a sigma-lattice.
Journal ArticleDOI
A survey of maintenance models: The control and surveillance of deteriorating systems
TL;DR: The literature on maintenance models is surveyed and includes models which involve an optimal decision to procure, inspect, and repair and/or replace a unit subject to deterioration in service.
Journal ArticleDOI
Monte Carlo bounding techniques for determining solution quality in stochastic programs
TL;DR: It is shown that, in expectation, z^*"n is a lower bound on z* and that this bound monotonically improves as n increases, and confidence intervals are constructed on the optimality gap for any candidate solution x@^ to SP.