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Estimation of semiparametric models when the criterion function is not smooth
Open accessAbstract
We provide easy to verify suffcient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some preliminary nonparametric estimators. Our results extend existing theories like those of Pakes and Pollard (1989), Andrews (1994a), and Newey (1994). We apply our results to two examples: a 'hit rate' and a partially linear median regression with some endogenous regressors.
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Cites
The Asymptotic Variance of Semiparametric Estimators
Newey, W. K. (1994) · Econometrica · doi:10.2307/2951752 · Cited by 717
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Metadata
- Authors
- Chen, X., Linton, O., & van Keilegom, I.
- Venue
- Working Paper Series
- Publisher
- Institute for Fiscal Studies
- Published
- 2002-11-07
- ISSN
- 1753-9196
- OpenAlex
- W2243572907
- Cited by
- 322
- References
- 1
- Type
- report
- Language
- en
- Open access
- green
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