Efficient Detrending In Cointegrating Regression
No abstract is available for this item.
Volume (Year): 15 (1999)
Issue (Month): 04 (August)
|Contact details of provider:|| Postal: Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK|
Web page: http://journals.cambridge.org/jid_ECT
- Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
- Moon, Hyungsik R. & Phillips, Peter C.B., 2000. "Estimation Of Autoregressive Roots Near Unity Using Panel Data," Econometric Theory, Cambridge University Press, vol. 16(06), pages 927-997, December.
- Moon, Hyungsik R & Phillips, Peter C B, 1999.
" Maximum Likelihood Estimation in Panels with Incidental Trends,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 61(0), pages 711-747, Special I.
- Hyungsik R. Moon & Peter C.B. Phillips, 1999. "Maximum Likelihood Estimation in Panels with Incidental Trends," Cowles Foundation Discussion Papers 1246, Cowles Foundation for Research in Economics, Yale University.
- Moon, Hyungsik & Phillips, Peter C.B., 1999. "Maximum Likelihood Estimation in Panels with Incidental Trends," University of California at Santa Barbara, Economics Working Paper Series qt3f55r5mj, Department of Economics, UC Santa Barbara.
- Pierre Perron & Gabriel Rodriguez, 2012. "Residual test for cointegration with GLS detrended data," Documentos de Trabajo / Working Papers 2012-327, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Pierre Perron & Gabriel RodrÃguez, "undated". "Residuals-based Tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series wp2015-017, Boston University - Department of Economics, revised 19 Oct 2015.
- Perron, P. & Rodriguez, G., 2000. "Residual Based Tests for Cointegration with GLS Detrended Data," Working Papers 0004e, University of Ottawa, Department of Economics.
- Xiao, Zhijie, 2004. "Estimating average economic growth in time series data with persistency," Journal of Macroeconomics, Elsevier, vol. 26(4), pages 699-724, December.
- Xiao, Qifang & Xiao, Zhijie, 2003. "Estimating Average Economic Growth in Time Series Data with Persistency," Working Papers 03-0111, University of Illinois at Urbana-Champaign, College of Business.
- Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
- Peter C.B. Phillips & Hyungsik R. Moon, 1999. "Nonstationary Panel Data Analysis: An Overview of Some Recent Developments," Cowles Foundation Discussion Papers 1221, Cowles Foundation for Research in Economics, Yale University.
- Marco Morales, 2014. "Cointegration testing under structural change: reducing size distortions and improving power of residual based tests," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 265-282, June.
- Ted Juhl & Zhijie Xiao, 2000. "N-Consistent Semiparametric Regression: Partially Linear Models with Unit Roots," Econometric Society World Congress 2000 Contributed Papers 1532, Econometric Society.
- Boswijk, H. Peter & Jansson, Michael & Nielsen, Morten Ørregaard, 2015. "Improved likelihood ratio tests for cointegration rank in the VAR model," Journal of Econometrics, Elsevier, vol. 184(1), pages 97-110.
- H. Peter Boswijk & Michael Jansson & Morten Ørregaard Nielsen, 2012. "Improved Likelihood Ratio Tests for Cointegration Rank in the VAR Model," CREATES Research Papers 2012-39, Department of Economics and Business Economics, Aarhus University.
- H. Peter Boswijk & Michael Jansson & Morten Ø. Nielsen, 2012. "Improved Likelihood Ratio Tests for Cointegration Rank in the VAR Model," Tinbergen Institute Discussion Papers 12-097/III, Tinbergen Institute.
- H. Peter Boswijk & Michael Jansson & Morten Ã˜rregaard Nielsen, 2012. "Improved Likelihood Ratio Tests for Cointegration Rank in the VAR Model," Working Papers 1297, Queen's University, Department of Economics.
- Gabriel Rodriguez & Pierre Perron, 2013. "Single-equation tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series 2013-016, Boston University - Department of Economics.
When requesting a correction, please mention this item's handle: RePEc:cup:etheor:v:15:y:1999:i:04:p:519-548_15. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Keith Waters)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Follow series, journals, authors & more
New papers by email
Subscribe to new additions to RePEc
Public profiles for Economics researchers
Various rankings of research in Economics & related fields
Who was a student of whom, using RePEc
Curated articles & papers on various economics topics
Upload your paper to be listed on RePEc and IDEAS
Blog aggregator for economics research
Cases of plagiarism in Economics
Job Market Papers
RePEc working paper series dedicated to the job market
Pretend you are at the helm of an economics department
Services from the StL Fed
Data, research, apps & more from the St. Louis Fed