# ARDL with Cointegrating Bounds using EVIEWS 9

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

http://register1.eviews.com/demo/

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.

This was the brief overview of how ARDL can be operated further details can be seen in the blog link above.

Note: You can generate the CUSUM or CUSUM sq charts from the following link or update the eviews version.

## 276 thoughts on “ARDL with Cointegrating Bounds using EVIEWS 9”

1. sherry says:

hello sir,

i have ARDL equation for my 30 years annual data…but i do not know how to interpret it.

1. Noman Arshed says:

see past papers to learn interpretation

2. Iriogbe Pamela says:

I intend to use a dummy variable in my model, I have logged my other variables but I cannot log the dummy variable. Can I work with it like that? If not how can I go about it.

1. Noman Arshed says:

you cannot apply log on the dummy variable as there are 0s and 1s in it if you take log all the 0s will disappear your sample will become small. use the dummy as it is, because dummy variable is not a quantity which you can log it is a quality.

3. Faith Ibigbemi says:

What do I do if my cointeq(1) is -1.38

4. Azam says:

Eviews 9 not showing bounds test after getting ARDL Results. View—>Coefficient Diagnostics—> Shows only Four options and Bounds Test is not one of them.Please suggest.

1. Noman Arshed says:

5. iqra rani says:

i have check stationary but my dependent variable is at first difference stationary after taking log but all other variables becomes stationary without taking log.what should i do?guide me plz

1. Noman Arshed says:

you can run ARDL in this situation too. see preconditions here

6. Fethi amri says:

HOW TO RUN GRANGER CAUSALITY TEST AFTER ARDL

1. Noman Arshed says:

Eviews 9 have a build in feature, open variables as a group it will show the option of granger causality

7. Nasir islam says:

Dear sir
I m using ardl model having 36 observation annual time series data d statistic value is greater then upper bound value and data have no problem of serial correlation and hetroscadasity my ecm coefficient is positive and significant kindly give me suggestion

1. Noman Arshed says:

see theory if you can add some more relevant variables.

I have 11 variables in my analysis for time series, one of them is dependant & the others are independent includes one dummy variable … in fact I dont know which model can use it. By the way iapplied unitroot test and I take 2nd difference . I realy need help

1. Dhnaya says:

Dear sir,
Thank you very much for your assistance with ARDL model, I have used the model to publish a paper with the instruction from this page.
Now am struggling with GMM model, I Am using panel data, can you please give some guidance regarding the model, How do we choose instrumental variable in the Model.
Thanks.

1. Noman Arshed says:

I have not worked on this model, may be in future

9. Nasir islam says:

I have 36 observation in my data I can not add any other variable in my model and ecm coefficient is positive and significant and there is no problem of auto correlation and hetroskadacity what I do kindly guide me

1. Noman Arshed says:

ecm positive means no long run relation, so at least one of your long run variables is faulty, replace it.

10. Mukhtar says:

please, using eviews what are the steps to follow for ARDL estimation with breaks?
thank you.

1. Noman Arshed says:

You just have to add structural break variable, it can be known break unknown break (construction of break variable shown here)

1. Azam says: