Video

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

Thank you for your favor and reply, I have installed Eviews 12 and this option was shown to me. but my data is an unbalanced panel, and Eviews gave an error that this test (panel unit root with cross-sectional dependence) cannot be performed for an unbalanced panel. Please introduce me to the link of the video where you have taught the unit root test test (the second generation of the unit root test, with cross-sectional dependence) for the unbalanced panel. I looked for it myself, but I didn't find anything, thanks. My emphasis is on the unbalanced panel.

Thank you !

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

how we include pairs of countries please tell me

Hello and thank you for your scientific and valuable content, I need this answer urgently. thanks. At minute 5:51, when your mouse is on the unit root test, a small black triangle can be seen on the right side of the unit root, which shows two separate parts: 1. cross-sectionally dependent 2. cross-sectionally independent But for me, in my eviwes it is not displayed like that, and two options 1. cross sectionally dependent 2. cross-sectionally independent Is it not displayed !! My Eviews is version 11, what is the cause of this problem?

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 🙌🏻👏🏻

❤😊

👏👏🥰

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.

Menit 2:20 oke

perfect... in short time.. optimum gyaan shared

Hello how can i generate impulse response function for parsimonious VAR model ? there is no option for that in eviews

Thank you so much for your videos, they are very useful for me. My question is if I can use this model to estimate the effect of the trade agreement on the exports of a single trading partner, without using the data panel for several countries.

Thank you

Is your data of t-bill in percentage?

Why does panel ardl doesn't have rsquare value

thank you...also show on spss how anova &.Acnova model results are interpreted

For unbalanced panel fata how to do it in ky case problem of csd cone so i want to run cips but since data unbalanced i cant apply also cadf is not giving t value what shall i do

Dear Komal, Can you please help me how to apply quantile VAR approach?????

Thanks so kindly for this informative video. However, the interpolation feature is not available in the student version of "Eviews 12". Can you help with an alternative?

Hank you so much ❤❤❤

Thank you very much, Komal, for a nice explanation.

Greetings. Do you have time series data analysis videos?

Ma'am how can I contact you?

Good explanation