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

Publikation: Working paper › Forskning

Standard

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

Department of Economics, University of Copenhagen, 2010.

Publikation: Working paper › Forskning

Harvard

Johansen, S 2010 'The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level' Department of Economics, University of Copenhagen.

APA

Johansen, S. (2010). The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level. Department of Economics, University of Copenhagen.

Vancouver

Johansen S. The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level. Department of Economics, University of Copenhagen. 2010.

Author

Johansen, Søren. / The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level. Department of Economics, University of Copenhagen, 2010.

Bibtex

@techreport{fe8c3140dc2711df825b000ea68e967b,
title = "The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level",
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.",
author = "S{\o}ren Johansen",
note = "JEL classification: C32",
year = "2010",
language = "English",
publisher = "Department of Economics, University of Copenhagen",
address = "Denmark",
type = "WorkingPaper",
institution = "Department of Economics, University of Copenhagen",

}

RIS

TY - UNPB

T1 - The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration with an Application to Annual Mean Temperature and Sea Level

AU - Johansen, Søren

N1 - JEL classification: C32

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

M3 - Working paper

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

PB - Department of Economics, University of Copenhagen

ER -

ID: 22613395