What is the optimal number of lags for an ARDL model?

My first comment is that all cointegrating studies must be based on the economic theory (and common sense) of the system that you are examining. Your theory should suggest which variables are stationary, which are non-stationary, and which are cointegrated. Your ARDL, VECM, etc, analyses are then tests of the fit of the data to your theories. It is not appropriate to use these methodologies to search for theories that fit the data. Such results will give spurious results. Now suppose that you have outlined your theory in advance of touching your computer keyboard to do your econometrics.

You have only 30 annual observations. This is on the small size for an elaborate analysis such as this. It appears that you have one dependent variable and possibly 3 explanatory variables. If you have 5 lags you are estimating about 25 coefficients which is not feasible with 30 observations.

If you wish to use the ARDL methodology you must be satisfied that (1) there is only one cointegrating relationship and (2) that the explanatory variables are (weakly) exogenous. Otherwise, a VECM approach is required and you may also not have enough data for a VECM analysis.

Is it possible that you would use a simpler approach? Could you use graphs or a simpler approach to illustrate your economic theory? These are questions that you alone can answer. Advanced econometrics is not a cure for inadequate data and a deficit of economic theory.

If this is an academic project, consult your supervisor. While what I have set out above is correct, it may not be what your supervisor expects at this stage in your studies.

Hikmet Akyol

As Mr. Frain said, the theoretical structure needs to be thoroughly understood before ARDL models can be predicted. In addition, when making ARDL estimates, it is necessary to make sure that the dependent variable is stationary in i [1].

*The most important advantage of the Ardl method is that it can also be used for a relatively small sample. For example, Narayan and Narayan (2005) used a data set of twenty-eight years (See also:Narayan & Narayan (2005). Estimating income and price elasticities of imports for Fiji in a cointegration framework).

** Narayan & Narayan (2005) compared the critical values of the F boundary test obtained in their study with studies with similar sampling. Can you try it too?

***I think the information criterion that you will use when making an ARDL estimate can be very important.t. For example, Narayan & Narayan (2005) used the Schwartz Bayesian Criteria (SBC).

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