Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217197 
Authors: 
Year of Publication: 
2020
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 11 [Issue:] 2 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2020 [Pages:] 609-636
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
This paper studies the inference problem of an infinite-dimensional parameter with a shape restriction. This parameter is identified by arbitrarily many unconditional moment equalities. The shape restriction leads to a convex restriction set. I propose a test of the shape restriction, which controls size uniformly and applies to both point-identified and partially identified models. The test can be inverted to construct confidence sets after imposing the shape restriction. Monte Carlo experiments show the finite-sample properties of this method. In an empirical illustration, I apply the method to ascending auctions held by the US Forest Service and show that imposing shape restrictions can significantly improve inference.
Subjects: 
Nonparametric/semiparametric models
partial identification
shape restrictions
unconditional moments
JEL: 
C12
C14
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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