Journal article
Boundedness of M-estimators for linear regression in time series
- Abstract:
- We show boundedness in probability uniformly in sample size of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semicontinuous and sufficiently large for large argument. Particular cases are the Huber-skip and quantile regression. Boundedness requires an assumption on the frequency of small regressors. We show that this is satisfied for a variety of deterministic and stochastic regressors, including stationary and random walks regressors. The results are obtained using a detailed analysis of the condition on the regressors combined with some recent martingale results.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 277.8KB, Terms of use)
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- Publisher copy:
- 10.1017/S0266466618000257
Authors
- Publisher:
- Cambridge University Press
- Journal:
- Econometric Theory More from this journal
- Volume:
- 35
- Issue:
- 3
- Pages:
- 653-683
- Publication date:
- 2018-09-04
- Acceptance date:
- 2018-04-17
- DOI:
- EISSN:
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1469-4360
- ISSN:
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0266-4666
- Keywords:
- Pubs id:
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pubs:859273
- UUID:
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uuid:49df2901-e87f-4e4d-8e17-f7087ebb8e08
- Local pid:
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pubs:859273
- Source identifiers:
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859273
- Deposit date:
-
2018-06-25
Terms of use
- Copyright holder:
- Cambridge University Press
- Copyright date:
- 2018
- Notes:
- COPYRIGHT: © Cambridge University Press 2018. This is the accepted manuscript version of the article. The final version is available online from Cambridge University Press at: https://doi.org/10.1017/S0266466618000257
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