Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/130087 
Year of Publication: 
2015
Series/Report no.: 
cemmap working paper No. CWP01/16
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We provide general compactness results for many commonly used parameter spaces in nonparametric estimation. We consider three kinds of functions: (1) functions with bounded domains which satisfy standard norm bounds, (2) functions with bounded domains which do not satisfy standard norm bounds, and (3) functions with unbounded domains. In all three cases we provide two kinds of results, compact embedding and closedness, which together allow one to show that parameter spaces defined by a ║·║s-norm bound are compact under a norm ║·║c. We apply these results to nonparametric mean regression and nonparametric instrumental variables estimation.
Subjects: 
Nonparametric Estimation
Sieve Estimation
Trimming
Nonparametric Instrumental Variables
JEL: 
C14
C26
C51
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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