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I've got two conflicting answers when I search the internet for my question. Since cointegration is sensitive to maximum lag length, it is important to choose maximum lag length wisely. According to one answer, maximum lag length in the underlying VAR should be 1 for annual data, 4 for quarterly, and 12 for monthly data. I use annual data, so I should use 1 for maximum lag length.

But if I use 1 for maximum lag length, why and how can I use any information criterion to obtain the optimal number of lags? I mean, if I only have one option, 1 lag, information criteria become useless, right?

Also, when I proceed to VECM, only one lag will not show any short-run relations between the variables, just to the cointegration coefficient, huh? I'm a novice at econometrics, so please bear with me if I'm asking silly questions.

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  • $\begingroup$ Look here for a related question and a nice answer to it. Also look here, especially if you use R. And even if you do not use R, it is still a good presentation of VECM modelling. $\endgroup$
    – Richard Hardy
    Commented Oct 30, 2014 at 20:00
  • $\begingroup$ You can use a sensitivity analysis of your model under different numbers and/or lengths of lags, too. $\endgroup$
    – Alexis
    Commented Feb 5, 2016 at 1:28

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That recommendation (1 for annual, 4 for quartely, etc) is simply a rule of thumb that was obtained by other people who probably used some information criteria so that now you don't have to. That is, if your time series is much longer or shorter than a typical case, you should determine the optimal lag yourself, otherwise relying on the rule of thumb is ok.

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    $\begingroup$ Thanks for your answer! What do you think would be the length of a typical case? Also, if my time series is shorter/longer than that, and I would determine the optimal lag myself, I´d use information criteria such as AIC or BIC? Or just be parsimoneous and use one lag (which I red somewhere)? $\endgroup$
    – Lars Ahnland Nordfors
    Commented Oct 1, 2014 at 12:04

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