Good day, I've been trying to understand this for so long but you have just broken it down, really helping my studies and the assignment I have due soon. God bless you. Thanks Sir :)
Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there for feedback. Thank you, Sayed Hossain from Hossain Academy facebook.com/groups/hossainacademy/
Normally regression line using cross sectional data do not have serial correlation but they normally suffer from heteroscedasticity. So you can drop checking serial correlation when the data is cross section type.
Many thanks for this informative video. If I would like to examine the impact of oil price fluctuations on GDP growth and inflation rate, do I need first to check all this features before estimating the model?
Imy question would like to know is it possible to run a regression where one variable is first difference and the rest are not or its a must to make all variable similar ?
From the literature review I saw many researchers go for stationary test, and when variables in time series found to be stationary then the model will be estimated using VAR. After that they employ Granger causality analysis, Impulse Response function and Variance Decomposition analysis. So my question when should I apply the above tests to make sure that this is the best regression model. My understanding is that I can test my model if I'm going to use it for forecasting, I'm not sure really!.
Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there for feedback. Thank you, Sayed Hossain from Hossain Academy facebook.com/groups/hossainacademy/
Hello, i am affraid but i have negative variables, so i cannot convert it to log, how can i do so that i have homoskedastic residuals ? PS: My variables have already been differenciated
In this model is it ok to have Constant a high value? doesn't this mean that most of the explanation of Y has been done by constant and not other x variables? I mean, my question is that in a cross section model, is it ok to have constant a high value? doesn't make the model a weak model since I couldn't find better explanatory variables?
Hi prof. Very good and helpful . One question ; if in our regression model we have some independent variable (0 or 1) and data is for 5 years and 50 company , which way is better? Best regard
So in my Eviews i should choose dynamic instead of static and then run the model , the question is the the dynamic place seems to be not activated therefore its possible to run dynamic model using simple multiple regression OLS
I have failed to understand your question. However, whether you will run dynamic or static it depends on the objective of your study. In this regard, journal article can suggest you what type of method you should choose to handle your problem.
I have started using Eviews very recently. So, though i have watched many of your videos(which are very helpful indeed) im not that much adept applying it too thoroughly. My problems are very basic one- I tried running an OLS with US GDP, stock price , interest rate & oil price....(GDP =dependant & the others independent) i made the data stationary by taking the first derivative of the logged variables. But i cannot get rid of heteroscedasticity & serial correlation anyway. ( i tried taking lagged variables of the dependent ..doesn't work). What can i do .... Does any other option works other than OLS with the data ...?
actually what is the different between using month data and quarterly data ? except large sample size may make residual normal, is there still have other different ?
Q = A +B dP + PR + Qt-1 ( in the independent variables i took the first difference for the price only dP or i need to take the first difference to all parameters dependent and independent ). Q: Oil production dP: Oil Price t - Oil Price t-1 PR : Proven reserves Qt-1 : One lag oil production Therefore my question would like to know is it possible to run a regression where one variable is first difference and the rest are not or its a must to make all variable similar ?
So residuals are not normally distributed. That is bad sign but not that bad as OLS estimators are still BLUE. So you can do two things, First, convert all variables into natural log and then run regression. If it does not work, then increase sample size. I guess residual will be normal.
Hello Hossain. You mention that the general rule is - we accept the x value if the p-value is less than 5%. How come when dealing with auto correlation, the chi square p-value is greater than 5% and we accept the null hypothesis?
+Faith Edigold Musimenta In both case, story will be just opposite. First case, p should be less than 0.05 and the second case, p should be more than 0.05 to get good regression line. For further discussion, I would like to invite you to join Hossain Academy Facebook for greater interaction about economics, finance and econometrics with me. Thank you Sayed Hossain from Hossain Academy. Please join below and post your question.facebook.com/groups/hossainacademy/
9 років тому
Thanks for the video. It's very helpful. May I ask some questions? I have run a regression model but the r-square is very small (=8.8%). Is there something wrong with that? I have read some articles about this but they say that it depended. My study is about market risk and I have about 6 independent variables with 470 samples. Could you give me some advise please? I'm very nervous right now.
Duyên Trần Normally if the independent variables are not relevant for this model R square goes down. You need to change independent variables.
9 років тому
Sayed Hossain Thank you for your reply. Can I ask another question? If my r-square is low but f-statistic is significant at the 1% level then what does it mean? Moreover, 3 out of 6 independent variables are significant. Do I still have to concern about the r-square?
If your regression model has time series variables, then serial correlation should not be there. Although R square is low but F statistics is significant, then it is OK.
Thank you very much for the video.It is really very very helpful. Especially for someone who has no experience in econometrics and statistics. I would be very thankful if you could answer additional question of mine. Is this data stationary, because as i know time series data firstly should be checked on stationary. or if I dont check it, run regression and have such kind of good results is it reliable?
Dear Nino, I would like to invite you to join Hossain Academy Facebook at below link to discuss about economics, econometrics and statistical models using EVIEWS, STATA, R, SPSS, Minitab, Microfit, Lingo, and Excel. Thank you, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
but when i use the first difference only for price (its non stationary and by first difference its converted to stationary0 . So when i run the model with first difference to price only relation comes positive with total oil production which is logic and similar to what has been said in the literature .
Hi Professor, thank you for your video! And I've already jointed in your group at facebook. May I ask you a quick question. What is lag and how should I chose it?
Dear Kim, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there. Actually I am in that group and may help you. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
thanks. so im using the least square for my test. but 3 out of 6 variables are insignificant including the constant. but when i removes the constant, which leaves only 5 variables and resulted 4 out of 5 significants. so i was wondering can i removes the constant or should i just leave the constant there and use the 3 insignificant out of 6 including the constant? please answerr pleaseeee
Dear Nora, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there. If I know the answer I shall certainly respond. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
hi, sir , please can if i have this model for forecasting, Ei,t+T= x0+x1*negE+x2*Ei,t..........can i say its an autoregressif model, with eviews i write variables: E, E(-1)....because i must do forecasting for t+1, t+2,....
Thank you. I would like to invite you to join Hossain Academy Facebook Group at below link and join our group discussion. Thank you. Sayed Hossain from Hossain Academy.
Previous literature says that relation between oil prices and world oil supply is positive so when prices are high world oil productions increase to gain more profits . Therefore when i run my model with below equation normally with taking any first difference relation comes negative which isnt logic and shouldnt be the case .
dear sir, thanks for your nice video. it's helping me a lot. but i got some problem which is my p-value is both for independent variable and f-statistic is it any problem?
Dear Mia, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there. Actually I am in that group and may help you. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
Hello, This is indeed a valuable effort for disseminating knowledge. I have one suggestion for more effectiveness to take less time than the given as it will further increase the interest of the incumbent video watcher. I have noticed you are repeating the things quite often which at times become tirade for the watcher. Hope you will take it in a positive manner. Stay blessed.
Thank you Burki, I would like to invite you to join Hossain Academy Facebook at below link and post your question there. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
Hello sir. My research is on cross sectional data of daily returns of companies of cnx 50 for ten years. It has variables but the independent variables also have coeeficients like beta 1 and beta 2 and there is an intercept alpha. How do we put these in the equation in eviews. Can u upload a video on how to do cross sectional data like this. Can i get your email id
Hello sir. My data is cross sectional on companies of nifty 50 for ten years. Its independent variables have coeeficients beta 1 and beta 2 . And also an intercept alpha. How can i include these three in eviews equation. Can u plz upload a video on how to do cross sectional data. Can u gv me your email id
Thank you. I would like to invite you to join Hossain Academy Facebook Group at below link and join our group discussion. Thank you. Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
you are the best professor who can simplify hard concepts. Thanks for your time and effort
Prof Hossain - Thank you so much. You made it too simple to understand. Listening to each sentence was worth
Good day, I've been trying to understand this for so long but you have just broken it down, really helping my studies and the assignment I have due soon. God bless you. Thanks Sir :)
Thank you very much for clarifying the selection of regression models!
Anthony Hawkins Please join Hossain Academy group in the Facebook. You are welcome there.
hello sir, i am very grateful for the impact you made in me. This simply shows your diligence and care for education. I really appreciate
Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there for feedback. Thank you, Sayed Hossain from Hossain Academy
facebook.com/groups/hossainacademy/
Normally regression line using cross sectional data do not have serial correlation but they normally suffer from heteroscedasticity. So you can drop checking serial correlation when the data is cross section type.
but how possible to test serial correlation on residuals for cross-section data (Not time series) (Not panel data)?
Many thanks for this informative video. If I would like to examine the impact of oil price fluctuations on GDP growth and inflation rate, do I need first to check all this features before estimating the model?
What is the P value of JB statistics?
Imy question would like to know is it possible to run a regression where one variable is first difference and the rest are not or its a must to make all variable similar ?
Is this for only time series? or can it applied to cross sectional data?
From the literature review I saw many researchers go for stationary test, and when variables in time series found to be stationary then the model will be estimated using VAR. After that they employ Granger causality analysis, Impulse Response function and Variance Decomposition analysis. So my question when should I apply the above tests to make sure that this is the best regression model. My understanding is that I can test my model if I'm going to use it for forecasting, I'm not sure really!.
I have exam in 2 hours, and this is a good summary video for revision. Thank you
Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there for feedback. Thank you, Sayed Hossain from Hossain Academy
facebook.com/groups/hossainacademy/
Hello, i am affraid but i have negative variables, so i cannot convert it to log, how can i do so that i have homoskedastic residuals ?
PS: My variables have already been differenciated
In this model is it ok to have Constant a high value? doesn't this mean that most of the explanation of Y has been done by constant and not other x variables? I mean, my question is that in a cross section model, is it ok to have constant a high value? doesn't make the model a weak model since I couldn't find better explanatory variables?
Hi Sayed, many thx for this, very helpful, pls inform what is the best course of action when residuals are not normally distributed ?
Increase sample size may make residual normal.
Hi prof. Very good and helpful .
One question ; if in our regression model we have some independent variable (0 or 1) and data is for 5 years and 50 company , which way is better?
Best regard
oh i see. but my JB stats is low which mean there is non normality. can the model still be accepted?
So in my Eviews i should choose dynamic instead of static and then run the model , the question is the the dynamic place seems to be not activated therefore its possible to run dynamic model using simple multiple regression OLS
I have failed to understand your question. However, whether you will run dynamic or static it depends on the objective of your study. In this regard, journal article can suggest you what type of method you should choose to handle your problem.
thank you for this video. Quick Question. What does R Squared explain?
Mohammad Ahmad R square measures whether independent variables jointly can explain dependent variable or not.
Mohammad Ahmad R square talk about how much independent variables jointly can explain dependent variables.
It measures the degree of variation in the dependent variable explained by the independent variables.
If the independent variable, although may not be significant, but very much relevant to dependent variable, you must keep it.
May be later I shall make a video on your query. Thanks for your comment.
Thanks. This is very informative. Can you explain what is Partial Least Squares using an example and how to interpret it?
The coefficient sign of a variable must follow either economic theory or literature that is findings from journal.
Yes I have few GARCH model in my website. You can see it for your thesis
Thank you so so much. You are doing a great job!!
I have started using Eviews very recently. So, though i have watched many of your videos(which are very helpful indeed) im not that much adept applying it too thoroughly. My problems are very basic one-
I tried running an OLS with US GDP, stock price , interest rate & oil price....(GDP =dependant & the others independent) i made the data stationary by taking the first derivative of the logged variables.
But i cannot get rid of heteroscedasticity & serial correlation anyway. ( i tried taking lagged variables of the dependent ..doesn't work).
What can i do .... Does any other option works other than OLS with the data ...?
actually what is the different between using month data and quarterly data ?
except large sample size may make residual normal,
is there still have other different ?
I am not sure about it. Please see literature
Q = A +B dP + PR + Qt-1 ( in the independent variables i took the first difference
for the price only dP or i need to take the first difference to all parameters dependent and independent ).
Q: Oil production dP: Oil Price t - Oil Price t-1 PR : Proven reserves Qt-1 : One lag oil production
Therefore my question would like to know is it possible to run a regression where one variable is first difference
and the rest are not or its a must to make all variable similar ?
So residuals are not normally distributed. That is bad sign but not that bad as OLS estimators are still BLUE. So you can do two things, First, convert all variables into natural log and then run regression. If it does not work, then increase sample size. I guess residual will be normal.
WOULD YOU PLEASE UPLOAD THE METHOD OF FINDING RESIDUALS(DISCRETIONARY ACCRUALS) WITH EVIEWS ?
nice one boss.....onk kaje dise :D
You are welcome sir. Thank you Sayed Hossain from Hossain Academy at www.sayedhossain.com
Hello Hossain.
You mention that the general rule is - we accept the x value if the p-value is less than 5%.
How come when dealing with auto correlation, the chi square p-value is greater than 5% and we accept the null hypothesis?
+Faith Edigold Musimenta
In both case, story will be just opposite. First case, p should be less than 0.05 and the second case, p should be more than 0.05 to get good regression line. For further discussion, I would like to invite you to join Hossain Academy Facebook for greater interaction about economics, finance and econometrics with me. Thank you Sayed Hossain from Hossain Academy. Please join below and post your question.facebook.com/groups/hossainacademy/
Thanks for the video. It's very helpful.
May I ask some questions? I have run a regression model but the r-square is very small (=8.8%). Is there something wrong with that? I have read some articles about this but they say that it depended. My study is about market risk and I have about 6 independent variables with 470 samples. Could you give me some advise please? I'm very nervous right now.
Duyên Trần Normally if the independent variables are not relevant for this model R square goes down. You need to change independent variables.
Sayed Hossain Thank you for your reply. Can I ask another question? If my r-square is low but f-statistic is significant at the 1% level then what does it mean? Moreover, 3 out of 6 independent variables are significant. Do I still have to concern about the r-square?
If F statistics is significant your model is over all fit. It is good.
3 out of 6 is fine. Go ahead.
Sayed Hossain Thank you a lot for your help. I'm very appreciated! Have a nice day, sir!
I could not understand your question. Please ask me again
If your regression model has time series variables, then serial correlation should not be there. Although R square is low but F statistics is significant, then it is OK.
Thank you very much for the video.It is really very very helpful. Especially for someone who has no experience in econometrics and statistics. I would be very thankful if you could answer additional question of mine. Is this data stationary, because as i know time series data firstly should be checked on stationary. or if I dont check it, run regression and have such kind of good results is it reliable?
Dear Nino, I would like to invite you to join Hossain Academy Facebook at below link to discuss about economics, econometrics and statistical models using EVIEWS, STATA, R, SPSS, Minitab, Microfit, Lingo, and Excel. Thank you, Sayed Hossain from Hossain Academy.
facebook.com/groups/hossainacademy/
but when i use the first difference only for price (its non stationary and by first difference its converted to stationary0 .
So when i run the model with first difference to price only relation comes positive with total oil production which is logic and similar to what has been said in the literature .
You need to consult journals and literature to know what are the variables to be chosen in the area you are doing research. You can write me here.
you can apply for both.
Hi Professor, thank you for your video! And I've already jointed in your group at facebook. May I ask you a quick question. What is lag and how should I chose it?
Dear Kim, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your
question there. Actually I am in that group and may help you. Thank you once
again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
thanks. so im using the least square for my test.
but 3 out of 6 variables are insignificant including the constant.
but when i removes the constant, which leaves only 5 variables and resulted 4 out of 5 significants.
so i was wondering can i removes the constant or should i just leave the constant there and use the 3 insignificant out of 6 including the constant?
please answerr pleaseeee
Dear Nora, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your question there. If I know the answer I shall certainly respond. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
hi,
sir what if i get Rsquare value as -9.6611 . what should it be construed as?
mayuresh G R square can not be negative
Sayed Hossain R square can not be negative. There is something wrong
hi, sir ,
please can if i have this model for forecasting, Ei,t+T= x0+x1*negE+x2*Ei,t..........can i say its an autoregressif model, with eviews i write variables: E, E(-1)....because i must do forecasting for t+1, t+2,....
This type of model is possible. We call it auto-regressive model or dynamic model.
Many thanks!!!
SIR IAM USINNG PANEL DATA ANALYSIS USING FIXED EFFECTS MODEL CAN I CHECK THE MODEL FITNESS USING THE SAME ASSUMPTIONS
Thank you. I would like to invite you to join Hossain Academy Facebook Group at below link and join our group discussion. Thank you. Sayed Hossain from Hossain Academy.
Previous literature says that relation between oil prices and world oil supply is positive so when prices are high world oil productions increase to gain more profits .
Therefore when i run my model with below equation normally with taking any first difference relation comes negative which isnt logic and shouldnt be the case .
Thank you very much sir. Thank you.
thanks for your guide ,
dear sir, thanks for your nice video. it's helping me a lot. but i got some problem which is my p-value is both for independent variable and f-statistic is it any problem?
Dear Mia, Thank you. I would like to invite you to join Hossain Academy Facebook at below link and post your
question there. Actually I am in that group and may help you. Thank you once
again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
Hello, This is indeed a valuable effort for disseminating knowledge. I have one suggestion for more effectiveness to take less time than the given as it will further increase the interest of the incumbent video watcher. I have noticed you are repeating the things quite often which at times become tirade for the watcher. Hope you will take it in a positive manner. Stay blessed.
Thank you Burki, I would like to invite you to join Hossain Academy Facebook at below link and post your question there. Thank you once again, Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
Thank you! :)
I feel also like literature that you have mentioned.
Hello sir. My research is on cross sectional data of daily returns of companies of cnx 50 for ten years. It has variables but the independent variables also have coeeficients like beta 1 and beta 2 and there is an intercept alpha. How do we put these in the equation in eviews. Can u upload a video on how to do cross sectional data like this. Can i get your email id
Hello sir. My data is cross sectional on companies of nifty 50 for ten years. Its independent variables have coeeficients beta 1 and beta 2 . And also an intercept alpha. How can i include these three in eviews equation. Can u plz upload a video on how to do cross sectional data. Can u gv me your email id
Thank you. I would like to invite you to join Hossain Academy Facebook Group at below link and join our group discussion. Thank you. Sayed Hossain from Hossain Academy. facebook.com/groups/hossainacademy/
In that case you better add some variables and run
May be in future
Should be similar
my JB statistic is 17.53451 and the probability is 0.000156
Yes I have few GARCH model in my website. You can see it for your thesis
Yes I have few GARCH model in my website. You can see it for your thesis
Yes I have few GARCH model in my website. You can see it for your thesis