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Testing for Shifts in Trend With an Integrated or Stationary Noise Component
Abstract
We consider testing for structural changes in the trend function of a time series without any prior knowledge of whether the noise component is stationary or integrated. Following Perron and Yabu (2009), we consider a quasi-feasible generalized least squares procedure that uses a super-efficient estimate of the sum of the autoregressive parameters αwhen α=1. This allows tests of basically the same size with stationary or integrated noise regardless of whether the break is known or unknown, provided that the Exp functional of Andrews and Ploberger (1994) is used in the latter case. To improve the finite-sample properties, we use the bias-corrected version of the estimate of αproposed by Roy and Fuller (2001). Our procedure has a power function close to that attainable if we knew the true value of αin many cases. We also discuss the extension to the case of multiple breaks.
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In the citing paper
“𝑊𝑅𝑄𝐹 is the Wald robust quasi-FGLS statistic proposed by Perron and Yabu (2009) to test the null that the trend function does not change in the period under consideration.”
From Fertility Transitions in Developing Countries: Convergence, Timing, and Causes (2019) · cites this paper as Perron and Yabu (2009)
In the citing paper
“The test is asymptotically distributed as a chi-squared random variable.”
From Fertility Transitions in Developing Countries: Convergence, Timing, and Causes (2019) · cites this paper as Perron and Yabu (2009)
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Research works printed but not linked: 24
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- 10.1016/0304-3932(82)90012-5 · DOI
- 10.2307/1913712 · DOI · Paper page
- Perron P., 1992, Proceedings of the Business and Economic Statistics Section, American Statistical Association, pp., 144
- 10.1016/j.jeconom.2009.03.011 · DOI
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- 10.1086/261592 · DOI
- 10.1198/07350010152596736 · DOI
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- 10.1214/aos/1176344136 · DOI · Paper page
- 10.1017/S0266466600006289 · DOI
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Cited by
Sorted by citations
Fertility Transitions in Developing Countries: Convergence, Timing, and Causes
Papagni, E. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3522996 · Cited by 1
Metadata
- Authors
- Perron, P., & Yabu, T.
- Affiliations
- Keio University (JP)
- Venue
- Journal of Business & Economic Statistics
- Publisher
- Informa UK Limited
- Published
- 2009-07
- Volume
- 27
- Issue
- 3
- Pages
- 369-396
- ISSN
- 0735-0015 (ISSN-L)
- 1537-2707
- OpenAlex
- W2026639679
- Cited by
- 271
- References
- 0
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 7 · 2023: 4 · 2022: 10 · 2021: 16 · 2020: 21 · 2019: 15 · 2018: 14 · 2017: 21 · 2016: 19 · 2015: 21 · 2014: 25 · 2013: 31 · 2012: 16
- FWCI
- 43.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Business and Economic Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Monetary Policy and Economic Impact
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Diverse Scientific and Economic Studies
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- structural breaks, trend shifts, stationary noise, autoregressive parameter estimation, bias correction, multiple breaks, finite sample properties, unit roots
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- The paper
- Perron, P., & Yabu, T. (2009). Testing for Shifts in Trend With an Integrated or Stationary Noise Component. Journal of Business & Economic Statistics. https://doi.org/10.1198/jbes.2009.07268
