Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
Publikation: Working paper › Forskning
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Correlation, Regression, and Cointegration of Nonstationary Economic Time Series. / Johansen, Søren.
Department of Economics, University of Copenhagen, 2007.Publikation: Working paper › Forskning
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TY - UNPB
T1 - Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
AU - Johansen, Søren
N1 - JEL Classification: C22
PY - 2007
Y1 - 2007
N2 - Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient
AB - Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient
KW - Faculty of Social Sciences
M3 - Working paper
BT - Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
PB - Department of Economics, University of Copenhagen
ER -
ID: 1523792