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how to interpret the results please make another video

please tell me from where we take data for distance

which econometric model can be used in case of CD presence?

Mam.. error message "near singular matrix" is displayed after lag length criteria command. Kindly guide me further

Great work...! Mam waiting for System GMM second part.... please upload

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very nice❤❤🎉🎉👌👌😊👍

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Nice explanation!!!

Why you have taken log variable in your data set ...

Hi, I have a question, usually it is said that we can use DOLS if y is I(1) and x (the regressor) is I(1) or I(0) but is it possible to use it also in the opposite situation given that we have cointegration? So when y is I(0) and x (the regressor) is I(1)?

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Ma'am in time series analysis minimum how many year should be taken?

Ma'am could you please share the excel file ?

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how to convert annual panel data to semi-annual panel data inside eviews?

Thank you !

pleasse ye be bata dy ke hum FTAbothin and FTAonein include kry

how we include pairs of countries please tell me

Where is the part 2 to SYS-GMM? Thank you

Can you examine long-run and short-run effects using IV-GMM?

Hello mam how to get longrun coefficient of cross sectional data in eviews ardl?

Thanks for the video. Is this also applicable to the panel regression (OLS)?

how can i and how many days are required to learn panel regression with gmm ?

Very helpful video, thank you!

Hi, may I know what is the name for this test that used for endogeneity? May I know would it be possible for me to have references to test for endogeneity?

Is it necessary that for causality test variables should be stationary

Thank you very much for the video and the explanation. When we are referring to "shock" of the impulse variable, do we mean like a negative or positive "shock" will result in a positive reaction of the response variable?

Hi Ma'am, I have a question. Now I know how to get long-term coefficients, but what about the significance of thse long-run coefficients? How to get p-value for those? Also, which are the short-run coefficients? I am doing NARDL on STATA and I got variables like var1 and d(var1), I thought var1 could be long-run and and d(var1) could be short-run. I am using the NARDL module created by Marco Sunder. Could you please help me

Excellent video! Clear and easy to understand.

Amazing 😍 video mam

Veri nice video🎉🎉👌👌🥰

That's helpful mam and very easy to understand ❤ Thank you mam.

That's helpful and insightful, ma'am. Thank you for sharing:)

knowledgeable video mam 🙌🏻👏🏻

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I have one problem remove autocorrelation through lag the p value is less than 0.05 how I can slove these problem if using the log but data are both type of data positive and negative can it handle the data change into positive and using log ?

Thanks

Thank you very much Komal! Your videos are very helpful for my Ph D.

very helpful video, please tell how to have long run causality test results using Block Exogeneity Wald Test, from where we can have ECT values and how to interpret them ?

Hello...i am getting "N/A" for my dummy variable when doing the granger causality test...please explain

thank sir

Unless you are willing to make assumptions, there is no way to convert yearly data into monthly or quarterly data. If you are willing to make the assumption that whatever it is you have data on happens at a uniform rate throughout the year then quarterly data would just be yearly data divided by 4.

do we check for heteroscedasticity and autocorrelation after selecting the model based on chow test, hausman test and breusch pagan test of should be check for heteroscedasticity and autocorrelation in initial stage

how did you determine the 10 lags in the command (aic 10)?

Ma'am, I guess this was a mistake at 10.35 onwards. You said since p<0.05 (which is the case here), "we cannot reject H0, and hence we accept the alternate hypothesis of having no unit root, i.e. data is stationary." However, this conclusion is not correct: if p>0.05, yes we do not reject H0, meaning that in the case of stationarity, we would ACCEPT H0 (not H1), that is, data has a unit root or is non-stationary. I think you need to clarify this, as it will lead to a lot of confusion for others watching this video.

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