The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level

27 Pages Posted: 18 Oct 2010

See all articles by Soren Johansen

Soren Johansen

University of Copenhagen - Department of Economics; Aarhus University - CREATES

Date Written: October 15, 2010

Abstract

There 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

Keywords: regression correlation cointegration, model based inference, likelihood inference, annual mean temperature, sea level

JEL Classification: C32

Suggested Citation

Johansen, Soren, The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level (October 15, 2010). Univ. of Copenhagen Dept. of Economics Discussion Paper No. 10-27, Available at SSRN: https://ssrn.com/abstract=1693759 or http://dx.doi.org/10.2139/ssrn.1693759

Soren Johansen (Contact Author)

University of Copenhagen - Department of Economics ( email )

Øster Farimagsgade 5
Bygning 26
1353 Copenhagen K.
Denmark

Aarhus University - CREATES ( email )

Nordre Ringgade 1
Aarhus, DK-8000
Denmark

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