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Uniform Inference in Autoregressive Models
Abstract
The purpose of this paper is to provide theoretical justification for some existing methods for constructing confidence intervals for the sum of coefficients in autoregressive models. We show that the methods of Stock (1991), Andrews (1993), and Hansen (1999) provide asymptotically valid confidence intervals, whereas the subsampling method of Romano and Wolf (2001) does not. In addition, we generalize the three valid methods to a larger class of statistics. We also clarify the difference between uniform and pointwise asymptotic approximations, and show that a pointwise convergence of coverage probabilities for all values of the parameter does not guarantee the validity of the confidence set. Copyright The Econometric Society 2007.
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Cited by
Testing for Shifts in Trend With an Integrated or Stationary Noise Component
Perron, P., & Yabu, T. (2009) · Journal of Business & Economic Statistics · doi:10.1198/jbes.2009.07268 · Cited by 271
ESTIMATION AND INFERENCE WITH NEAR UNIT ROOTS
Phillips, P. C. B. (2023) · Econometric Theory · doi:10.1017/s0266466622000342 · Cited by 44
Metadata
- Authors
- Mikusheva, A.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2007-09
- Volume
- 75
- Issue
- 5
- Pages
- 1411-1452
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W2044594680
- Cited by
- 196
- References
- 0
- FWCI
- 9.01
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
