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The Engle-Granger approach as described above suffers from a number of weaknesses. Namely it is restricted to only a single equation with one variable designated as the dependent variable, explained by another variable that is assumed to be weakly exogeneous for the parameters of interest. It also relies on pretesting the time series to find out whether variables are I(0) or I(1). These weaknesses can be addressed through the use of Johansen's procedure. Its advantages include that pretesting is not necessary, there can be numerous cointegrating relationships, all variables are treated as endogenous and tests relating to the long-run parameters are possible. The resulting model is known as a [[vector error correction model]] (VECM), as it adds error correction features to a multi-factor model known as [[vector autoregression]] (VAR). The procedure is done as follows:
* Step 1: estimate an unrestricted VAR involving potentially non-stationary variables
* Step 2: Test for cointegration using [[Johansen test]]
*Step 3: Form and analyse the VECM
===An example of ECM===
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