The ARDL controversy

The ARDL controversy It has been a long-tailed debate among analyst on the nature of variables to include in an ARDL equation. Due to...

The ARDL controversy



It has been a long-tailed debate among analyst on the nature of variables to include in an ARDL equation. Due to the infinite nature of econometrics, I will shed little light on this issue.
1) ARDL can incorporate variables of I(0) series wholly but there is no room for cointegration testing but error correction representation is highly and always permissible.
2) ARDL can incorporate variables of I(1) series wholly but some conditions are attached.

i: Used Pesaran bound test; if cointegration exist among the variables, run the model in level and error correction representation is highly and always permissible
ii: If cointegration do not exist among the variables, run your model in First difference
3) This is the most controversial aspect of the exposition. This section seek to find answers to
i: what should be the nature of the dependent variables?
ii: Can I(1) and I(0) series be cointegrated always or conditionally?
The first argument is that, your dependent variable must be I(1) in nature (Though the author argued that this hold not necessarily but it violate the cointegration theory) and there must be atleast one I(1) regressors in order for possible cointegration to exist , for valid error correction form to exist and for valid inferences to exist. Pesaran failed to give full direction about this in his paper and has been silent on this for years; the theory behind cointegration never remained silent. There is a need to show you this proof
Y(t) = a + b*X1(t) + c*X2(t) + d*X3(t) + e(t)
Y(t) > (1)
X1(t) > (1)
X2(t) > (0)
X3(t) > (0)
here the linear combination of Y(t) and X1(t) called it Z(t)=k*Y(t) + w*X1(t) , if cointegrated will be I(0) then the combination of Z(t) and the other regressors (X2(t) and X3(t)) will be I(0)......i.e e(t) = f*Z(t) + c*X2(t) + d*X2(t) will be I(0).....
I suggest two steps method in spirit of lutkepohl and kraitzig by first testing for cointegration between /among the I(1) variables and if it exists, theoretically, this must also combine with the I(0) series to be cointegrated.
Moreover, you have to know that, there are some reports you have to give about ARDL model that failing to do so render your report useless. These are the dynamic nature of the ARDL result; mean lag, median lag and the dynamic elasticity/multiplier both interim and cumulative( confidence interval may be of interest in order to know the significant and insignificant region) .


Article by  Olasehinde  Timilehin

 Contact: timmexeduconsult econometrics lab, ondo state, Nigeria.
timmexdareal@gmail.com
+2347033586042
+2347060868692
Specialize in some certain macroeconometrics modeling such as
VAR/VARX
SVAR/SVARX
VECM/VECMX
SVECM/SVECMX
ARDL/NARDL/QARDL/QAARDL......
forecasting and Nowcasting
     

Also visit: ECONOMICS AND FINANCE SCHOLARS ONLINE ECONOMETRICS LABORATORY ON FACEBOOK

                

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