Perform Step by Step Fixed and Random Effect Models in STATA (with Noman Arshed)
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- Опубліковано 14 жов 2024
- #fixed #random #effect #models #paneldata #regression #regressionanalysis #econometrics #ols #stata #difference #diagnostics #estimate
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Today we Will learn
"perform step-by-step fixed and random effect models with Noman Arshed ".
In this video, we will learn about how to estimate the fixed and random effect panel data models in stata and also their common diagnostic tests.
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Thankyou very much for the video! Great work! How do we correct the problems of heteroskedasticity and autocorrelation in our model? I will be extremely thankful if you could answer this please!
there are two sources of autocorrelation, serial autocorrelation which is because of missing important variables, and pure autocorrelation which is because of data being non stationary. The second case is true when the number of years per cross section are many, in that case you may have to use panel ARDL. For the case of heteroskedasticity, you might have to explore reasons, it can be because of slope heterogeneity across cross sections for that you might have to use random coefficients models, it might be because of non linear behaviour of variable for that you might use non linear model (quadratic or moderating) or take log of variables. it may be because of outliers, then you might have to find outlier observations and remove them. Some details are provided at ua-cam.com/video/vRndUgRFFmo/v-deo.html
Your videos are more helpful than universities' professors. Good Job
Glad you like them!
thanks for the support ..... Masha Allah u r so helpful for members like us
Thanks and welcome
very informative n helpful ..................... Jazak Allah
Thanks for liking
This video was a saviour..can't thank enough to u
I encountered a problem while running lmnadxt and resetxt command about smaller matsize.When i tried to reset the matsize ,it didn't work.The meximum matsize allowed is between 10 and 800.What can i do to overcome this because my data suffers from normality isssue.Moreover, kindly refer to any video of yours that contains the solution of hetro auto,endogeniety and system gmm for panel data. Jazakallah.
In newer versions it is autometic but in older versions you can maximize matsize to 11000 by writing set matsize 11000
@@nomanarshed
So there is no solution now rather than splitting data into subsets....
If yes,then how can we overcome the normality issue or model mispecification form?
Moreover ,do u hav any video compiling resolving auto,endogeniety and system gmm for panel data? If not,kindly make a one ...u elaborated it really well..
Hi, I have 2 dependent variables that I want to test separately, Can I run the Hausman test for both of them separately?
Yes select models using hausman test for both models seperately
How to test for autocorrelation, etc in case of a Panel ARDL with PMG?
ideally it is assumed that the model has sorted the autocorrelation, since the model has lags, you cannot use Durbin Watson method. if required you need to store the residuals and use other methods to check for autocorrelation
@@nomanarshed
Oh, ok, thank you, I thought that will be the case, but was unsure. I watched most of the videos on youtube, and nobody mentions that.
Mostly videos use plain ARDL as an example, where majority of the usual tests can be applied, but one can not find information in case of Panel ARDL.
you can ask if you have more queries. Actually, there are not any videos or any papers for the diagnostics because it is believed that panel ARDL is a solution of autocorrelation so there is no need to check for it.
In hausman test p value came 0 means fixed effect model is appropriate but in xttest0 p value came 1 means pooled is appropriate. So which on is appropriate for this analysis??? Please can you explain
xttest0 checks between OLS and RE. So even if it is 1 it is saying OLS is better than RE. and from Hausman we come to know that FE is better than RE. Now you need to estimate FE model in the bottom line of FE there is a test that checks FE vs OLS. if that is significant we will use FE as FE will be better than OLS.
Can you please tell me how to do FE test to choose Between ols vs fixed effect??
It is shown below results of fe autometically
And is it mandatory to do robust FE if FE has heterodasticity problem?
If yes than we have to write robust fe result to our report or normal FE test result?
It depends on type of hetroscedasticity. If it can be solved using advanced model then use it. If not then report robust estimates
sir why I'm not able to run lmnadxt command? when I give this command my Stata is not responding. How can I solve this?
It takes time to execute this command, you have to either wait for it or use any other alternative method.
Is stationarity and Co integration required incase of fixed and random effect if N is small and T is also not very large. If not can you give some references.
According to Pedroni, if T < 19 we can assume data to be stationary so no need of unit root and cointegration tests. Further even if prove that data is cointegrated, but the data is nonstationary, in that case FE and RE are incapable to handle nonstationary variables.
Okay thank you . And I wanted to ask one more things is cross sectional dependency required before running fixed and random effects
Because I’ve read if T< 25 and N< 25 we directly do for fixed and random effects
And can you give the full reference/ link of pedroni . Will be really thankful 😊
@@seeratsajjad3224 if N and T is large then cross sectional dependence. If it exists then FE amd RE cannot be used then you should try Driscoll and Kraay Regression.
in xtserial why "no observations" r(2000)
There might be missing values in data or any one of the variable is string
how to collect on Tobinq for previous years?
See past studies they report sources. You can request them for data.