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
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: 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
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