One of your great videos. What if CADF shows different p-values for different cross sections as showed in your example? How to interpret the result of CADF here! Thanx
Insightful. Thank you for sharing I'm having an error message that says automatic lag selection encountered an error most likely due to insufficient observation... Working on 10 years across 60 firms
Great video, Thanks so mush 😊 i have a question, when using CIPS and CADF tests how can i check for the 1 difference and 2 difference ? i dont see the option to do it in eviews
Thanks for your kind words. Second generation panel unit root test option is available in EViews 12 and new versions only. However, To the best of my knowledge, I couldn't locate this aspect in EViews 12. Still, You can perform first and second difference for CADF and CIPS in Stata. Good day!
Great video, thanks very much. What does it mean if my data shows no cross-sectional dependence when I don't include the trend and constant, but if I include them, then it shows very strong cross-sectional dependence?
Excellent video, could you tell us wich version of Eviews you are using ? can you explain how to apply 2nd generation panel unit root test in stata? plis
Second generation panel unit root test option is available in EViews 12 and new versions. However, To the best of my knowledge, I couldn't locate this aspect in EViews 12. Still, You can perform first and second difference for CADF and CIPS in Stata. Good day!
Ma'am, I guess this was a mistake at 10.35 onwards. You said since p0.05, 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.
Here p value is greater than 0.05, so how can we accept the alternative hypothesis (10.40-11 time of streaming) pls. Check it. As per my knowledge we have to accept the null hypothesis.
Dear, the interpretation is that- This last table provides the result of the Pooled version of individual ADF test statistic in the previous table. Due to very high value we cannot reject the Null Hypothesis. We cannot reject the Null Hypothesis that- All of the variables are simultaneously not cointegrated.
I have a question plz. If i regress the series on its own trend and found it significant on trend and constant. Does this indicate that i must choose the constant and trend option in this case? Thanks
No, it doesn't. If p value is greater than 0.05, this means that the variable is not stationary at 5% level of significance. However if the p value is more than 0.05 but less than 0.10, you can state that the variable is stationary at 10% level of significance. But if it is more than .10, the variable is not stationary. We are conducting a Panel Data Analysis Workshop on 25/26 Nov. You may register if you wish to. Link- forms.gle/3R5CkRT1gJpGjrVv5 Also join my telegram group for further updates - t.me/kshekhawat
@@komalkanwarshekhawat_ thanKyOu ma'am. if the data is not getting stationary in second unit root test can't we run 1st difference and second difference on second generation unit root test? or we can conclude that the data is not getting stationary at level and assume to be stationary at 1st differnece and 2nd difference after converting into log form?
@@VarneshghildiyalvibhuYou are interpreting it in the wrong way. The second generation unit root test is performed when there is presence of cross-sectional dependence.
@@komalkanwarshekhawat_ my data exhibits cross sectional dependence, so i used the 2nd generation unit root tests CIPS and CADF to test stationary using Eviews. CADF is giving me values/ pvalues for each cross section. How to interpret the results?
thanks mam, i am following the steps and i am getting this error message "Automatic lag selection encountered an error most likely due to insufficient observations." what may i do mam
The number of observations are very few and maybe you are taking more lags. Hence the error - insufficient observations. Meaning, the observations are so less after automatic lag selection that the analysis cannot be performed.
So you say that if the test does not satisfy with constant and then go with trend? Ok leaving it aside and then you forgot about specifyig at level and first difference. You missed the lag selection process and also the results what you found with your data is not relevant what you said !!!
One of your great videos. What if CADF shows different p-values for different cross sections as showed in your example? How to interpret the result of CADF here! Thanx
Insightful. Thank you for sharing
I'm having an error message that says automatic lag selection encountered an error most likely due to insufficient observation... Working on 10 years across 60 firms
Cross sections are too large in number. Pls increase the time span.
Great video, Thanks so mush 😊
i have a question, when using CIPS and CADF tests how can i check for the 1 difference and 2 difference ? i dont see the option to do it in eviews
Thanks for your kind words.
Second generation panel unit root test option is available in EViews 12 and new versions only. However, To the best of my knowledge, I couldn't locate this aspect in EViews 12. Still, You can perform first and second difference for CADF and CIPS in Stata. Good day!
Great video, thanks very much. What does it mean if my data shows no cross-sectional dependence when I don't include the trend and constant, but if I include them, then it shows very strong cross-sectional dependence?
Then there is a presence of cross-sectional dependence.
Excellent video, could you tell us wich version of Eviews you are using ? can you explain how to apply 2nd generation panel unit root test in stata? plis
Thank you! I'm using EViews SV 12.
Thank you so much, i have a question (how to run the first and second difference for CADF and CIPS tests?)
Second generation panel unit root test option is available in EViews 12 and new versions. However, To the best of my knowledge, I couldn't locate this aspect in EViews 12. Still, You can perform first and second difference for CADF and CIPS in Stata. Good day!
Ma'am, I guess this was a mistake at 10.35 onwards. You said since p0.05, 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.
You are correct.
which econometric model can be used in case of CD presence?
Here p value is greater than 0.05, so how can we accept the alternative hypothesis (10.40-11 time of streaming) pls. Check it. As per my knowledge we have to accept the null hypothesis.
Dear, the interpretation is that-
This last table provides the result of the Pooled version of individual ADF test statistic in the previous table.
Due to very high value we cannot reject the Null Hypothesis.
We cannot reject the Null Hypothesis that- All of the variables are simultaneously not cointegrated.
thank you so much
Welcome! Keep following 👍
I have a question plz. If i regress the series on its own trend and found it significant on trend and constant. Does this indicate that i must choose the constant and trend option in this case? Thanks
Yes!
mam please clear me that if the p value is more than .05 that means the variable is stationary in second genration unit root test?
No, it doesn't. If p value is greater than 0.05, this means that the variable is not stationary at 5% level of significance. However if the p value is more than 0.05 but less than 0.10, you can state that the variable is stationary at 10% level of significance. But if it is more than .10, the variable is not stationary.
We are conducting a Panel Data Analysis Workshop on 25/26 Nov. You may register if you wish to.
Link- forms.gle/3R5CkRT1gJpGjrVv5
Also join my telegram group for further updates - t.me/kshekhawat
@@komalkanwarshekhawat_ thanKyOu ma'am. if the data is not getting stationary in second unit root test can't we run 1st difference and second difference on second generation unit root test? or we can conclude that the data is not getting stationary at level and assume to be stationary at 1st differnece and 2nd difference after converting into log form?
@@VarneshghildiyalvibhuYou are interpreting it in the wrong way. The second generation unit root test is performed when there is presence of cross-sectional dependence.
in CADF test , what if some of the cross sections exhibit non stationary? how can we interpret the result here for this specific variable? Thank you
Check whether it is stationary at first difference or not ?
@@komalkanwarshekhawat_ my data exhibits cross sectional dependence, so i used the 2nd generation unit root tests CIPS and CADF to test stationary using Eviews. CADF is giving me values/ pvalues for each cross section. How to interpret the results?
Thanx Thanx Thanx
Your welcome 😊
I am not getting the cips and panic test in the unit root tests window . only adf and other tests
Try running again. The options must be there.
thanks mam, i am following the steps and i am getting this error message "Automatic lag selection encountered an error most likely due to
insufficient observations." what may i do mam
The number of observations are very few and maybe you are taking more lags. Hence the error - insufficient observations.
Meaning, the observations are so less after automatic lag selection that the analysis cannot be performed.
So you say that if the test does not satisfy with constant and then go with trend? Ok leaving it aside and then you forgot about specifyig at level and first difference. You missed the lag selection process and also the results what you found with your data is not relevant what you said !!!
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Very nice
Please your explanation is contradictory
Kindly elaborate!
If we do not reject the null hypothesis, it means we accept the null hypothesis and reject the alternative hypothesis.
✨ ρяσмσѕм
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