A note on limit theory for mildly stationary autoregression with a heavy-tailed GARCH error process
Author
Abstract
Suggested Citation
DOI: 10.1016/j.spl.2019.04.009
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Liudas Giraitis & Peter C. B. Phillips, 2006.
"Uniform Limit Theory for Stationary Autoregression,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 27(1), pages 51-60, January.
- L Giraitis & P C B Phillips, "undated". "Uniform limit theory for stationary autoregression," Discussion Papers 05/23, Department of Economics, University of York.
- Liudas Giraitis & Peter C.B. Phillips, 2004. "Uniform Limit Theory for Stationary Autoregression," Cowles Foundation Discussion Papers 1475, Cowles Foundation for Research in Economics, Yale University.
- Phillips, Peter C.B. & Magdalinos, Tassos, 2007.
"Limit theory for moderate deviations from a unit root,"
Journal of Econometrics, Elsevier, vol. 136(1), pages 115-130, January.
- Peter C.B. Phillips & Tassos Magdalinos, 2004. "Limit Theory for Moderate Deviations from a Unit Root," Cowles Foundation Discussion Papers 1471, Cowles Foundation for Research in Economics, Yale University.
- Zhang, Rongmao & Ling, Shiqing, 2015. "Asymptotic Inference For Ar Models With Heavy-Tailed G-Garch Noises," Econometric Theory, Cambridge University Press, vol. 31(4), pages 880-890, August.
- Fei, Yijie, 2018. "Limit theory for mildly integrated process with intercept," Economics Letters, Elsevier, vol. 163(C), pages 98-101.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Eunju Hwang, 2021. "Limit Theory for Stationary Autoregression with Heavy-Tailed Augmented GARCH Innovations," Mathematics, MDPI, vol. 9(8), pages 1-10, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Eunju Hwang, 2021. "Limit Theory for Stationary Autoregression with Heavy-Tailed Augmented GARCH Innovations," Mathematics, MDPI, vol. 9(8), pages 1-10, April.
- Xinghui Wang & Wenjing Geng & Ruidong Han & Qifa Xu, 2023. "Asymptotic Properties of the M-estimation for an AR(1) Process with a General Autoregressive Coefficient," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-23, March.
- Yabe, Ryota, 2017. "Asymptotic distribution of the conditional-sum-of-squares estimator under moderate deviation from a unit root in MA(1)," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 220-226.
- Jingjie Xiang & Gangzheng Guo & Qing Zhao, 2022. "Testing for a Moderately Explosive Process with Structural Change in Drift," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 300-333, April.
- Zhishui Hu & Ioannis Kasparis & Qiying Wang, 2020. "Locally trimmed least squares: conventional inference in possibly nonstationary models," Papers 2006.12595, arXiv.org.
- Bailey, N. & Giraitis, L., 2013. "Weak convergence in the near unit root setting," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1411-1415.
- Chevillon, Guillaume & Mavroeidis, Sophocles, 2011.
"Learning generates Long Memory,"
ESSEC Working Papers
WP1113, ESSEC Research Center, ESSEC Business School.
- Guillaume Chevillon & Sophocles Mavroeidis, 2013. "Learning generates Long Memory," Post-Print hal-00661012, HAL.
- Peter C. B. Phillips, 2014.
"On Confidence Intervals for Autoregressive Roots and Predictive Regression,"
Econometrica, Econometric Society, vol. 82(3), pages 1177-1195, May.
- Peter C.B. Phillips, 2012. "On Confidence Intervals for Autoregressive Roots and Predictive Regression," Cowles Foundation Discussion Papers 1879, Cowles Foundation for Research in Economics, Yale University.
- Andrews, Donald W.K. & Cheng, Xu & Guggenberger, Patrik, 2020.
"Generic results for establishing the asymptotic size of confidence sets and tests,"
Journal of Econometrics, Elsevier, vol. 218(2), pages 496-531.
- Donald W.K. Andrews & Xu Cheng & Patrik Guggenberger, 2011. "Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests," Cowles Foundation Discussion Papers 1813, Cowles Foundation for Research in Economics, Yale University.
- Christis Katsouris, 2022. "Asymptotic Theory for Unit Root Moderate Deviations in Quantile Autoregressions and Predictive Regressions," Papers 2204.02073, arXiv.org, revised Aug 2023.
- Stauskas, Ovidijus, 2019. "On the Limit Theory of Mixed to Unity VARs: Panel Setting With Weakly Dependent Errors," Working Papers 2019:2, Lund University, Department of Economics.
- Phillips, Peter C.B. & Magdalinos, Tassos & Giraitis, Liudas, 2010.
"Smoothing local-to-moderate unit root theory,"
Journal of Econometrics, Elsevier, vol. 158(2), pages 274-279, October.
- Peter C.B. Phillips & Tassos Magdalinos & Liudas Giraitis, 2008. "Smoothing Local-to-Moderate Unit Root Theory," Cowles Foundation Discussion Papers 1659, Cowles Foundation for Research in Economics, Yale University.
- Jardet, Caroline & Monfort, Alain & Pegoraro, Fulvio, 2013.
"No-arbitrage Near-Cointegrated VAR(p) term structure models, term premia and GDP growth,"
Journal of Banking & Finance, Elsevier, vol. 37(2), pages 389-402.
- Jardet, C. & Monfort, A. & Pegoraro, F., 2009. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working papers 234, Banque de France.
- Caroline JARDET & Alain MONFORT & Fulvio PEGORARO, 2011. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working Papers 2011-03, Center for Research in Economics and Statistics.
- Donald W. K. Andrews & Patrik Guggenberger, 2014.
"A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter,"
The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 376-381, May.
- Donald W.K. Andrews & Patrik Guggenberger, 2011. "A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter," Cowles Foundation Discussion Papers 1812, Cowles Foundation for Research in Economics, Yale University.
- Donald W.K. Andrews & Patrik Guggenberger, 2011. "A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter," Cowles Foundation Discussion Papers 1812R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2012.
- Sai-Hua Huang & Tian-Xiao Pang & Chengguo Weng, 2014. "Limit Theory for Moderate Deviations from a Unit Root Under Innovations with a Possibly Infinite Variance," Methodology and Computing in Applied Probability, Springer, vol. 16(1), pages 187-206, March.
- Ibragimov, Rustam & Phillips, Peter C.B., 2008.
"Regression Asymptotics Using Martingale Convergence Methods,"
Econometric Theory, Cambridge University Press, vol. 24(4), pages 888-947, August.
- Rustam Ibragimov & Peter C.B. Phillips, 2004. "Regression Asymptotics Using Martingale Convergence Methods," Cowles Foundation Discussion Papers 1473, Cowles Foundation for Research in Economics, Yale University.
- Ibragimov, Rustam & Phillips, Peter C.B., 2008. "Regression asymptotics using martingale convergence methods," Scholarly Articles 2624459, Harvard University Department of Economics.
- Yixiao Sun, 2014.
"Fixed-smoothing Asymptotics and AsymptoticFandtTests in the Presence of Strong Autocorrelation,"
Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 14, pages 23-63,
Emerald Group Publishing Limited.
- Sun, Yixiao, 2014. "Fixed-smoothing Asymptotics and Asymptotic F and t Tests in the Presence of Strong Autocorrelation," University of California at San Diego, Economics Working Paper Series qt8479f4s2, Department of Economics, UC San Diego.
- Yu Miao & Yanling Wang & Guangyu Yang, 2015. "Moderate Deviation Principles for Empirical Covariance in the Neighbourhood of the Unit Root," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 234-255, March.
- Nannan Ma & Hailin Sang & Guangyu Yang, 2023. "Least absolute deviation estimation for AR(1) processes with roots close to unity," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 799-832, October.
- Stephan Smeekes & Joakim Westerlund, 2019.
"Robust block bootstrap panel predictability tests,"
Econometric Reviews, Taylor & Francis Journals, vol. 38(9), pages 1089-1107, October.
- Westerlund, J. & Smeekes, S., 2013. "Robust block bootstrap panel predictability tests," Research Memorandum 060, Maastricht University, Graduate School of Business and Economics (GSBE).
More about this item
Keywords
Autoregression; Heavy-tailed GARCH process; Least squared estimator; Limit theory;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:152:y:2019:i:c:p:59-68. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.