Well we can now have ARDL module in EViews 9 which can replicate same results as compared to what Microfit can do with the advantage that we can have more than two lags and more than 6 variables which currently available demo version of Microfit does not allow. You can download your trial version of EViews 9 at following link
In this post I will provide a brief tutorial to how to do ARDL in EViews rest of the details can be seen from my previous ARDL manual post.
First of all we have to import the data into the EViews 9
After that we select the variables by pressing control button and selecting the dependent variable first and independent variables after it and right click it and open it as equation. Here in the drop down menu we can see option of ARDL at bottom
Select it. It will show the options of ARDL model
Here we can fix some particular lag or use automatic selection within the maximum lags of dependent variable and independent variable. The automatic lag selection criteria can be changed from default in the option window. press ok to see the ARDL model results in the following
these are the basic results see here that there are 4 lags used for the dependent and 2 for the first independent and 3 for the second independent variable using AIC criteria. Now we need the Bounds F test to see if there is cointegration or not, it can be done by pressing view button on the top and going in the coefficient diagnostics
This F test will tell if we can proceed further or not
Here we can see that our F test value of 3.5 is not bigger than any of the I1 bound value hence there is no cointegration among these variables. Since it is a tutorial I will show you further steps. If the F test value is small then we have to change the variables (add or remove) or try adding trend variable. and If we find F test value larger then we can go for the Long run results which can be seen by pressing view button and coefficient diagnostics
it will then show the short run and long run results both
Here we can see that there was no cointegration because all the long run coefficients are insignificant and the coefficient of cointEq(-1) is also non negative and insignificant which is with the short run coefficients. These should be significant as they are important. Further diagnostics like hetroskedasticity, Auto-correlation etc can be done by selecting view and residuals diagnostics.
Note: You can generate the CUSUM or CUSUM sq charts from the following link or update the eviews version.