Dear Sir, I have been watching your econometrics playlist for the past few days. I can finally say that you're an excellent teacher and the way you simplify complex concepts is truly remarkable. I recommend this to everyone studying Economics. Thank you. Wishing you all the very best going forward! Respect and Hugs from India🙏❤️
I appreciate your effort, i have learned econometrics at master level but did not clear concept at that time. Now after watching your detail video, I understood it. Thanks and JazakaALLAH
Speechless. Incredible way of explanation. Pace, Voice, Knowledge, Concepts all are co integrated beautifully. If you deliver lectures in English you will cross a million subscribers around the world Sir.
You are a blessing sir. Can't thank you enough. Sending you all the positivity and amazing health and keep sharing your amazing knowledge with the world. RESPECT from india...
Thank you sir for all these great classes! Here is my ques: If ADF, PP and KPSS are giving contradictory results, within that the mixture of I(0) and I(1) can be seen. How can I proceed? If I need to check Johansen cointegration, shall I generate first difference series and then consider that?
Thank you soo such sir for these awesome videos. This subject is really tough for me i didn't able to understand even a signal thing but with your video it became very very easy. I am really grateful to you because of you I will be able to get pass in my exam and also understood every concept thought by you. For me it was next to impossible to understand econometric. You are best sir. Thank you so much
Thank you for your appreciation. Here is the link of ECM ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-1oasRhnt5AI.html ARDL and VAR would be uploaded soon InshaAllah.
Commendable.... One question....if variables are stationary at 2nd difference or I(1) and I(2), then which model we should apply in time series.... kindly reply.
Firstly take my gratitude for such helpful videos! And my question is what model to apply if the variables are mixture of I(0),I(1) and I(2)? And in such situation how to test cointegration and causality among the variables?
I want to ask in 2nd and 3rd cases, if we get NO cointegration, we use OLS after making the variables stationary. The relationship we get in second cases are short run relation. Right? What about the relationship of 3rd cases. I mean will it give SR or LR results?
@@TJAcademyofficial Thanks forthe prompt response. I mean to say that OLS is not a model rather it is a technique to estimate coefficients of a model. Other technique is Maximum Likelihood Estimator. So we should say OLS estimator or Maximum Likelihood estimator rather than OLS model or Maximum Likelihood model. We know that most of the model employs OLS technique to estimate coefficients and So is the ARDL model. Now, my question is about your third case when variables are I(0) and I(1) both and there is cointegration. you suggested to use ARDL coefficient (keep in mind that ARDL also use OLS technique to estimate coefficients).But if there is no cointegration you suggested to use OLS. In this way ultimately we are using OLS in both the cases. Hope you get my question
Thank you for your message. You have to watch cointegration and causality lectures below. These are very different concepts. For cointegration ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-58Fc6PVYpeY.html For Causality ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-LgfZ60MiP3I.html For Granger Causality ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-lWYcDmVq1oA.html
Sir, while finding the stationary in Eviews, Can you please describe the different situations in which we can include the constant, intercept and trend term collectively and in which ituations we can ignore the the intercept and trend term during the calculation of stationary
If you watched the lecture again, you will notice that inclusion of intercept and trend is to check the robustness of stationary condition with all possibilities in the equations.
@TJ Academy Sir, In my study I have taken the data of four countries. The stationary of all the countries are different from each other. One country data is stationary at level and first difference, One is stationary at first difference, the other two are stationary at 1st+2nd difference. So for the estimations different model can be applied, Is it correct ? Can we compare the results of theses countries implied that i will be using different models of estimations?
AoA sir I just wanna ask I thing if dependent variable is stationary at level and independent variables are stationary at 1st difference what technique should use Is there any condition for ARDL that dependent variable should stationary at 1st difference
Sir, the results of the Johnsen cointegration test (using Schwarz criteria) show both the trace statistics and the maximum eigenvalue indicates 1 cointegrating equation so, does this means I can choose OLS over VECM for my study?
Sorry Sir I couldn't get your Point. Do you mean, I must use both OLS and VECM in this case or do you mean that I can chose between either OLS or VECM?
Sir, in my study the dependent variable is stationery at I(2). And there are three independent variables. Two of them are stationery at I(1) and one at I(2). Now please suggest Sir which option to choose and proceed.
Sir, if after unit root test at level we find that one series is stationary and the other is not stationary, in that case should we apply co integration test or not?
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