In these equations, I am adding extra variables to see if they improve the model.įor example, we may have a model, through economic theory that states: In regards to using 1 cointegrating vector when Johansen's may suggest 2 or more, I am testing specific model equations. For example, if the lag selection criteria suggest 3 lags for annual data, we use 2 lags 1 2) for our Johansen test and (1 2) for our VECM. Just so I understand, because a Var(p) is an equivalent representation of a VECM (p-1), we must also use (p-1) when conducting a Johansens test for cointegration as we intend to use VECM if cointegration is found using this test. Choosing only one is simply a convenience that reduces model complexity and interpretation. In other words, any lag testing on the VEC model will be done one one lag less than the equivalent VAR model.Īs for the number of cointegrating relationships to use, there is nothing in the literature that suggests one should use only one cointegrating relationship when one has several to choose from. VAR(1) => Y_t = Gamma * Y_) + Beta * X + eps_tĬlearly, a VAR(p) model has an equivalent representation as a VEC(p-1) model.
You can use mathematical induction or a brute force method to demonstrate the general case. I'll give you the case for p = 1 and p = 2. Why do you need peer-reviewed journals to show this? You can do so yourself directly. VECM Process VECM.JPG (55.11 KiB) Viewed 7015 times I have spoken to my PhD supervisor about this and she says it not always appropriate to follow online EVIEWS instructions, rather, she would like to see peer-reviewed journals and published books that suggest p-1 lags and only using 1 cointegrating vector is appropriate.ĭoes anyone have any experience or have read any peer-reviewed research or textbooks to find sources to reference? I am finding this task very difficult. We can do this to reduce the complexity of results. Please see below some examples of using EVIEWs and doing this:Īlso, I have seen throughout instruction videos, that if Johansen's method suggests more than 1 cointegrating Vector, say 2, 3, 4, we can use 1 cointegrating vector within our VECM model. That is, if the VAR process, at level, suggests 3 lags for annual data, we use 2 lags for our Johansen's method and VECM testing (3-1) = 2 lags. These authors claim that because the VECM model is rewriting the VAR by differencing and losing one lag, we must follow p-1 for lag selection. While watching instruction on how to run VECMs on youtube (from strong sources), I can see examples where after lag selection, Johansen's testing for cointegration requires to test for p-1 lags and lag selection for the VECM test also requires p-1. I have followed the usual steps (Please see the attached file below). My name is Michael and I am doing a multivariable time series analysis for my PhD.
0 kommentar(er)
