The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
The Grid Bootstrap and the Autoregressive Model
Abstract
A “grid” bootstrap method is proposed for confidence-interval construction, which has improved performance over conventional bootstrap methods when the sampling distribution depends upon the parameter of interest. The basic idea is to calculate the bootstrap distribution over a grid of values of the parameter of interest and form the confidence interval by the no-rejection principle. Our primary motivation is given by autoregressive models, where it is known that conventional bootstrap methods fail to provide correct first-order asymptotic coverage when an autoregressive root is close to unity. In contrast, the grid bootstrap is first-order correct globally in the parameter space. Simulation results verify these insights, suggesting that the grid bootstrap provides an important improvement over conventional methods. Gauss code that calculates the grid bootstrap intervals-and replicates the empirical work reported in this paper'is available from the author's Web page at www.ssc.wisc.edu˜bhansen
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Cites
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Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations
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Small-sample Confidence Intervals for Impulse Response Functions
Kilian, L. (1998) · Review of Economics and Statistics · doi:10.1162/003465398557465 · Cited by 917
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The Annals of Mathematical Statistics
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Some Impossibility Theorems in Econometrics With Applications to Structural and Dynamic Models
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Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models
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Bootstrapping autoregressions with conditional heteroskedasticity of unknown form
Gonçalves, S., & Kilian, L. (2004) · Journal of Econometrics · doi:10.1016/j.jeconom.2003.10.030 · Cited by 629
Local Projection Inference Is Simpler and More Robust Than You Think
Montiel Olea, J. L., & Plagborg-Møller, M. (2021) · Econometrica · doi:10.3982/ecta18756 · Cited by 437
Cluster-robust inference: A guide to empirical practice
MacKinnon, J. G., Nielsen, M. Ø., & Webb, M. D. (2023) · Journal of Econometrics · doi:10.1016/j.jeconom.2022.04.001 · Cited by 407
Investigating Inflation Persistence Across Monetary Regimes*
Benati, L. (2008) · Quarterly Journal of Economics · doi:10.1162/qjec.2008.123.3.1005 · Cited by 351
ESTIMATION AND INFERENCE WITH NEAR UNIT ROOTS
Phillips, P. C. B. (2023) · Econometric Theory · doi:10.1017/s0266466622000342 · Cited by 44
Metadata
- Authors
- Hansen, B. E.
- Venue
- Review of Economics and Statistics
- Publisher
- MIT Press - Journals
- Published
- 1999-11
- Volume
- 81
- Issue
- 4
- Pages
- 594-607
- ISSN
- 0034-6535 (ISSN-L)
- 1530-9142
- OpenAlex
- W2090128667
- Cited by
- 344
- References
- 20
- FWCI
- 7.34
- 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.
