Arbeitspapier
Compactness of infinite dimensional parameter spaces
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.
- Sprache
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Englisch
- Erschienen in
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Series: cemmap working paper ; No. CWP01/16
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
Model Construction and Estimation
- Thema
-
Nonparametric Estimation
Sieve Estimation
Trimming
Nonparametric Instrumental Variables
- Ereignis
-
Geistige Schöpfung
- (wer)
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Freyberger, Joachim
Masten, Matthew
- Ereignis
-
Veröffentlichung
- (wer)
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Centre for Microdata Methods and Practice (cemmap)
- (wo)
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London
- (wann)
-
2015
- DOI
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doi:10.1920/wp.cem.2016.0116
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:21 MESZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Freyberger, Joachim
- Masten, Matthew
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2015