The analysis of nonstationary time series using regression, correlation and cointegration with an application to annual mean temperature and sea level
AbstractThere are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference. Finally we analyse some data on annual mean temperature and sea level, by applying the cointegrated vector autoregressive model, which explicitly takes into account the nonstationarity of the variables.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2010-69.
Date of creation: 15 Oct 2010
Date of revision:
Contact details of provider:
Web page: http://www.econ.au.dk/afn/
Regression correlation cointegration; model based inference; likelihood inference; annual mean temperature; sea level;
Other versions of this item:
- Søren Johansen, 2010. "The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level," Discussion Papers 10-27, University of Copenhagen. Department of Economics.
- Søren Johansen, 2011. "The analysis of nonstationary time series using regression, correlation and cointegration - with an application to annual mean temperature and sea level," DSS Empirical Economics and Econometrics Working Papers Series 2011/4, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Phillips, P.C.B., 1986.
"Understanding spurious regressions in econometrics,"
Journal of Econometrics,
Elsevier, vol. 33(3), pages 311-340, December.
- Peter C.B. Phillips, 1985. "Understanding Spurious Regressions in Econometrics," Cowles Foundation Discussion Papers 757, Cowles Foundation for Research in Economics, Yale University.
- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
- Peter C.B. Phillips, 1988.
"Optimal Inference in Cointegrated Systems,"
Cowles Foundation Discussion Papers
866R, Cowles Foundation for Research in Economics, Yale University, revised Aug 1989.
- Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
- Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.