3
$\begingroup$

I am trying to estimate a VECM and I read in Asteriou´s book "Applied Econometrics" that

"The most common procedure in choosing the optimal lag length is to estímate a VAR model including all our variables in levels (non-differenced data). This VAR model should be estimated for a large number of lags, then reducing down by reestimating the model for one lag less until we reach zero lags."

However, I will introduce a dummy variable in my model.

Question: should I include the dummy in this VAR or should I include the dummy only afterwards when I estimate the VECM?

$\endgroup$
  • 1
    $\begingroup$ What do you think about the answer? $\endgroup$ – Richard Hardy Sep 11 '17 at 12:56
1
$\begingroup$

I would include the dummy variable(s) right away. For example, if the data generating process is well described by a VAR(1) and (strong) additive seasonality, then a sensible lag selection procedure will correctly suggest lag 1 if you include the seasonal dummies in the models among which you are choosing. However, if you do not include the dummies at the model selection stage, a VAR($p$) model could be suggested by the procedure instead, where $p$ could be equal to the seasonal period (e.g. 4 for quarterly data), as the (strong) additive seasonality will induce (high) autocorrelation at lag 4.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.