Kointegrationsvektoren

Kointegrationsvektoren, also known as cointegration vectors, are a concept in econometrics and time series analysis that describe the long-term equilibrium relationship between two or more non-stationary time series. These vectors are used to identify and analyze the underlying relationships between variables that are not stationary, meaning their statistical properties change over time.

The concept of cointegration was first introduced by Clive W.J. Granger in 1981. It is based on the idea that while individual time series may be non-stationary, a linear combination of them might be stationary. This stationary combination is what is referred to as the cointegration vector.

To identify a cointegration vector, one typically uses the Engle-Granger two-step method. The first step involves testing for cointegration using statistical tests such as the Augmented Dickey-Fuller (ADF) test or the Phillips-Perron (PP) test. If cointegration is present, the second step involves estimating the cointegration vector using methods like Ordinary Least Squares (OLS) regression.

Cointegration vectors are crucial in various fields, including economics, finance, and engineering, where they help in understanding the long-term relationships between variables. They are particularly useful in forecasting and policy-making, as they provide insights into the stable relationships that exist between non-stationary time series.