Panel Data Analysis using STATA
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- Опубликовано: 15 июл 2024
- Dr. Syed Ahmad Gillani is graduated from Universiti Teknologi Malaysia. He has more than 14 years of teaching and research experience in the field of accounting and finance. He is the author of many research articles. He is a founding member of Connecting ASIA and reviewed many research articles. He is also guest-editor of Estudios de Economia Aplicada / Studies of Applied Economics. He has expertise in quantitative data analysis and trainer of STATA.
BEST EXPLANATION I'VE FOUND SO FAR. THANK YOU DR. GILLANI, YOU'VE SAVED MY THESIS!
Really a great lesson, just fully covered the whole panel data from introduction to analysis as well as converting into doc
Patiency pay-off, be calm and follow this amazing teacher
Top notch teaching style. Many thanks for putting this lecture together.
Verry effective and easy-to-understand version of the presentation. Thank you so much, sir.
An August Master class on STATA , Jazaak Allah Khair , Respected sir
Many many thanks to syed ahmad sir....from Bangladesh.
Wow! Excellently discussed. Thank you, Dr. Syed.
Excellent and very practical. Will appreciate if you will deliver a presentation on applicable models and diagnostic tests for unbalanced panel.
Very great...u covered whole panel data
i love the detailedness in your video. thanks 📌
Very informative...thank u sir so much ❤
Thank you very much for your instruction.
Well explained sir. Thank you for the details!
very helpful session, well explain thank you Dr Syed Ahmed
Thank you very much, I learned a lot
Thanks for providing the opportunity.
Best for beginners and fresh learners !!!!
Thank you so much creating this video.
Great video! Great delivery and insights!
Good Explanation. Thanks so much
Excellent Sir, quite helpful
Excellent session..thanks a lot
Thank you Dr. I learned a lot!
Thank you for this.
Thank you very much, it helped me a lot
simply amazing
ALLAH Bless you sir; great work, Thank you.
Thank you so much
thank you!!!
Thank you!
Thanks a lot
Thank you Dr Syed Ahmad Gillani for this insightful presentation. Could you help us understand the theoretical model equations underlying each panel analysis method? Thank you.
Great lesson :)
Thanku sir
Very insightful video. Please increase the clarity of the commands in your subsequent videos Thank you.
Thanks a lot sir, it is helpful, but the interpretation of hausman test has different interpretation , i if P-value of chi2 >0.05 fell to reject Ho wic is random effect is consistent estimator . If
Very informative webinar. One question I want to ask here that "How to calculate moderating variable by Stata. Please help me out
Thanks very much sir, your lecture was very superb. Pls what is the stata command for marque beta test in stats 14 for panel ardl? Thanks
Sir I need to learn SEM analysis on penal data. Need more workshop video.
Dr. I appreciate the way you explain the analysis on Stata software but the result of stata was not visible.
kindly add some video on Bootstrapping through STATA?
Where is the data? Audience needs the data to practice and reproduce the results.
We also need to learn, how can we handle multicollinearity form databases
It was indeed insightful. Just I think Dr Syed made a small unintentional mistake. We should have chosen the random effect since the prob value is greater than 0.05.
good lecture. How can we export the regression table which look like in the journels? not the regression table in this lecture.
for attendance bit.ly/AIC2020-Workshop3-Dr-Gillani
I mean the command for jarque beta test of normality test in panel ardl
sir kindly tell me about to anaylse the control variables?
Have been there right from the beginning but attendance sheet is inaccessible even when clicked the link.
If the p-value of the normality test( Jarque Bera normality test) is less than 5%(.05), what will be the treatment sir? Thanks in advance. Eagerly waiting for your valuable reply.
sir how to correct abnormality and heteroscedasticity in stata?
he form AIC-2020 PRE-CONFERENCE WORKSHOP 4 is no longer accepting responses.
Try contacting the owner of the form if you think this is a mistake.(This is what appears when I click.
10 Dr
I believe that we choose random effect if the hausman probability value is higher than 0.05
yes you are right it was mistakenly spoken about fix effect model..
@@dr.syedahmadgillani7575 For all the models it is .05 p-value which is associated with 95 percent confidence level and not .005 as you mentioned as significance value associated with rejecting the null hypothesis at 95 percent confidence level. Similarly, for a 99 percent confidence level it would be .01. A good presentation, however, with a good ado file of exporting analysis to the word file.
Hello Sir, what to do when it is heteroscedasticity?
One correction, please. If the Hausman test result is more than 0.05 then we should go for the random effect model. Fixed effect may be incorrect.
would you provide practise data sets?
hi. can i get access to the excel file used in the analysis? thanks.
my N is less than T. Should I test unit root test?
As you didn’t test unit root . I am a little bit confused .
hey can i talk to you personally? I need to do sub sample analysis in stata.. Please Respond . I am from china
21:00
48:55 i think the data has heteroscedasticity is it right
can someone send me the excel file used in that video?
very helpful can you please share excel file for demo
From 30th minute to 35th minutes there is nothing changed on the video. Just the instructions are going on!
Hi all, when I run the Hausman test I get a chi squared value of -12. Can someone please help explain whether this means that we have rejected the null or not thanks, Peter.
Hi Peter, I believe the rejection of the null is based on the p-value of the chi square. If the p-value is greater than 0.05, you fail to reject the null, meaning you use a Random Effects model. A p-value less than 0.05 means you reject the null and use Fixed Effects model.
@@faizaomar7498 Thanks Faiza, but what is the answer if the p value is -9.76 please?
@@urcommunityfeedingaustrali6982 Apologies for replying this late. I have not come across such large p-values, since probabilities are ideally meant to be between 0 and 1. Due to this, I am sorry that I cannot explain what it means. It could be some technical problems.
@@faizaomar7498 is the conclusion made on the Hausman test by Dr. Ahmed contradicts the conventional way of decision? His p-value is greater than 0.05 and he is suggesting to fixed-effect model. Anyone, please make more clear about it.
TIA.
14:04
I think the number of obs is low. So we can see that liquidity have a non significatif impact of profitability
V
Wrong interpretation of Hauman test, hausman test shows that prob is 0.06 and is more than 0.05 , is not significant at the 5% level which indicates that we can not reject H0 , which Random effect is appropriate estimator than Fixed effect.
is not positive definitive. Which means we cannot use random effect even though it is more than 5%. In this case, fixed effect is appropriate. Another way to test whether random or fixed effect model is through xtoverid (Sargan-Hansen statistic) (if less than 5% fixed effect model is appropriate and vice versa)
@@viveksarati hausman test shows that prob is 0.06, which is s more than 0.05. we can not reject null hypothesis. That means random effect is applied rather
you are right random effect is most appropriate I mistakenly named as random actually it was live session no editing option is there anyhow thanks for your interest. regards
you can not teach the whole stata in every lesson. focus on either teaching stata interface or teaching panel data models
Very Very weak analysis. Sorry professor.