I like the way you explain your tutorial videos, they are really beneficial, thanks. My data are stationary at fist difference, I want to do impulse response in VAR, should I use first differenced data or level data?
Hi! Thank you for the detailed video on diagnostics. It's quite clear. I have a question on residual analysis though. When you tested for serial correlation at lag=3, there is still an autocorrelation at lag=1. Based on previous readings, the lag should be further increased, i.e. more than 3 because there should be no autocorrelation at all lag levels/ periods. Could you please clarify? Thank you.
Hello Sir, thank you so much for your efforts to make such videos. These are really helpful. I have a question. What is normality test results yield that residuals are not normally distributed and also if the residuals are heteroscedastic, what should be the next step?
@@DhavalSaifaleeAaryash yes, the variables are stationary at first level. I tried both ways, using level data as well as 1st difference. For both am getting the same results
Hi sir, if my variable are stationnary at first difference should i estimate the first difference of the variable with var or just the level variable ?
sir, my variables are stationary after first difference. should i use my data in levels in forecasting or should i difference my variables first before building the var model?
hello Dr. Dhaval.. thanks for very clear explanation. it's very helpfull.. i have question for the wald test to determine significant model. based your explanation the null hypothesis is all the coefficients are equal to zero. so, is that mean the intercept coefficients are included ? or only the variable coefficient ? thank you
While performing VAR test, we have included 2 lags in "lag length criteria". My question is - if this 2 is constant in all the cases or we can also increase it to 3 or 4? Because, when I entered 3 lags, its showed better results (lower value). Please guide on this. Thanks
If you consider r2 here, increasing lags will definetly increase but it will give rise to multicollinearity. Reasonably dont go above 2 lags as number of terms in final model will go on increasing
hello Dr. Dhaval.. I've been carried out heteroscedasticity test for VAR model, but i got the error message "Positive or non-negative argument to function expected". could you help to explain what does it means ? i use data with 30 obeservations and 2 variable. Thank you
хорошее видео, спасибо!
I like the way you explain your tutorial videos, they are really beneficial, thanks. My data are stationary at fist difference, I want to do impulse response in VAR, should I use first differenced data or level data?
Hi! Thank you for the detailed video on diagnostics. It's quite clear. I have a question on residual analysis though. When you tested for serial correlation at lag=3, there is still an autocorrelation at lag=1. Based on previous readings, the lag should be further increased, i.e. more than 3 because there should be no autocorrelation at all lag levels/ periods. Could you please clarify? Thank you.
Hello Sir, thank you so much for your efforts to make such videos. These are really helpful. I have a question. What is normality test results yield that residuals are not normally distributed and also if the residuals are heteroscedastic, what should be the next step?
Did u check stationarity of variable first
@@DhavalSaifaleeAaryash yes, the variables are stationary at first level. I tried both ways, using level data as well as 1st difference. For both am getting the same results
Hello Sir, I am getting an error 'Log of non positive number'. How to deal with it?
Hi sir, if my variable are stationnary at first difference should i estimate the first difference of the variable with var or just the level variable ?
run normal ols with first difference variable
@@DhavalSaifaleeAaryash thanks sir
hello can you answer my question please can i use var test when series are stationary at level
No
sir, my variables are stationary after first difference. should i use my data in levels in forecasting or should i difference my variables first before building the var model?
We hv to difference it
👍
hello Dr. Dhaval.. thanks for very clear explanation. it's very helpfull..
i have question for the wald test to determine significant model.
based your explanation the null hypothesis is all the coefficients are equal to zero.
so, is that mean the intercept coefficients are included ? or only the variable coefficient ?
thank you
Only coefficient of variable are included
@@DhavalSaifaleeAaryash thanks
Two variables should be stationary according to granger but which order. At level or first difference or same order
At any order, it may be at level or after the first difference, but both the variables should be stationary in the same order
While performing VAR test, we have included 2 lags in "lag length criteria". My question is - if this 2 is constant in all the cases or we can also increase it to 3 or 4? Because, when I entered 3 lags, its showed better results (lower value). Please guide on this. Thanks
If you consider r2 here, increasing lags will definetly increase but it will give rise to multicollinearity. Reasonably dont go above 2 lags as number of terms in final model will go on increasing
hello Dr. Dhaval..
I've been carried out heteroscedasticity test for VAR model, but i got the error message "Positive or non-negative argument to function expected".
could you help to explain what does it means ? i use data with 30 obeservations and 2 variable.
Thank you
Data insufficient