What is vector error correction model?
A vector error correction (VEC) model is a restricted VAR designed for use with nonstationary series that are known to be cointegrated. The cointegration term is known as the error correction term since the deviation from long-run equilibrium is corrected gradually through a series of partial short-run adjustments.
How do you read Engle-Granger test results?
Interpreting Our Cointegration Results The Engle-Granger test statistic for cointegration reduces to an ADF unit root test of the residuals of the cointegration regression: If the residuals contain a unit root, then there is no cointegration. The null hypothesis of the ADF test is that the residuals have a unit root.
When to use a vector error correction model?
If there is a cointegration between the variables, vector error correction model can be used. This method is known as augmented Granger causality test. In this approach, error correction term (ECT) is added to the VAR system.
When was vector autoregression introduced in time series modeling?
Vector autoregression (VAR) was introduced by Sims (1980 )as a technique that could be used by macroeconomists to characterize the joint dynamic behavior of a collection of varia- bles without requiring strong restrictions of the kind needed to identify underlying structural parameters. It has become a prevalent method of time- series modeling.
Which is Cointe grating vector is not unique?
Cointegration typically refers to alinearcombination of nonstationary variables.Moreover, the cointegrating vector is not unique. If(β1,β1,…,βn)is a cointe-grating vector, then for any nonzero value ofλ,(λ β1,λ β1,…,λ βn)is also acointegrating vector.
Are there any efficient estimators for cointegration vectors?
A variety of tests for cointegration and efficient estimators for cointegrating vectors are developed and compared. Finally, structural VAR modeling is surveyed, with an emphasis on interpretation, econometric identification and construction of efficient estimators.