Interpretation of ARDL MODEL?

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Ette Etuk

X refers to independent variable at current time. X(-1) refers to X one time point in the past, X(-2) refers to X two lags in the past. Y refers to the dependent variable at current time, Y(-1) refers to Y one lag behind. c is the constant of the model.

S.C Thushara

HI,

Pls see the following links.

https://nomanarshed.wordpress.com/2014/11/16/a-manual-for-ardl-approach-to-cointegration/

http://shodhganga.inflibnet.ac.in/bitstream/10603/3246/13/13_chapter%205.pdf

Kind regards

Thushara

Rohani Mohd

I am not very familliar with ADRL, but i have a question also, if anyone here can answer. In an analysis conducted using ADRL, can it be possible to have the Rsquare score very high (almost 100%) whereas all variables have the coefficient very weak (between 0.0005-0.02) but they were very significant

Russell Thomas Hellein

If there are trends in the data then I don't think R squared is seen as a very good measure because of the issue of spurious regression. What I don't understand about the coefficients is that you can have with ARDL (if there is cointegration) both short and long term coefficients. I don't understand the practical difference between their interpretation and when you would expect them to have effect - that is what is the difference between short and long run.

Elias Sanidas

ARDL can be used in small samples and regardless of the cointegration order (whether I(1) or I(0), etc). The lags structure are also easier to determine. See my article in the Journal of the Asia Pacific Economy re trade liberalization of Australian PMV industry. Usually high R square and significant coefficients go together. What you call "weak" coefficients is not correct, since the magnitude of coefficients depends on how they are defined (in what units). So they might be very small in magnitude but very significant and correct sign (?). But an R square so high close to 100% makes me suspicious of your ARDL modeling process.