(EViews10): Heteroskedasticity and Robust Standard Errors
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- Опубликовано: 30 июл 2024
- @CrunchEconometrix This video explains how to correct heteroscedasticity with robust standard errors. Coined from the Greek word hetero (which means different or unequal), and skedastic (which means spread or scatter). So, homoskedasticity means equal spread, and heteroskedasticity, on the other hand, means unequal spread. The measure of spread is the variance, hence, heteroskedasticity deals with unequal variances. Heteroskedasticity or heteroscedasticity is the same. Only be consistent. Yes! The longest word in the econometrics dictionary with 18 words. One of the assumptions of ordinary least squares (OLS) is that the model must be homoskedastic. Needed to justify the usual t tests, F tests, and confidence intervals for OLS estimation of the linear regression model, even in large samples. In general, heteroskedasticity is more likely to occur in cross-sectional analysis. This does not imply that heteroskedasticity in time series models is impossible. What are the causes of heteroskedasticity? (1) Poor data sampling method may lead to heteroskedasticity particularly when collecting primary data. (2) Wrong data transformation. For instance, over-differencing a variable may lead to heteroskedasticity. (3) Wrong model specification. Related to the functional form: log-log, log-level, and level-level models. (4) The presence of outliers can lead to your model becoming heteroskedastic. Bogus figures that stands out. Very obvious to the prying eyes. (5) Skewness of one or more regressors (closely related to outliers being evident in the data). Consequences of heteroskedasticity: (1) OLS estimators, β ̂_OLS are still linear, unbiased and consistent. Hence the regression estimates remain unbiased and consistent. (2) But the estimators, β ̂_OLS are inefficient (that is, not having minimum variance) in the class of minimum variance estimators. (3) Therefore, OLS is no longer BLUE (Best Linear Unbiased Estimator). (4) Such that regression predictors (estimates) are also inefficient, though consistent. (5) Implies that the regression estimates cannot be used to construct confidence intervals, or used for inferences. (6) Affects the variances (and standard errors) of the estimated β ̂_S. (7) OLS method under-estimates the variances (and standard errors). (8) Yields low standard errors (9) Leads to higher than expected values of t and F statistics. (10) Yields statistically significant coefficients. (11) Rejection of the null hypothesis too often (12) Causes Type I error. (13) Both the t and the F statistics are no longer reliable any more for hypothesis testing. Some heteroskedasticity tests are: Breusch-Pagan LM Test; Glesjer LM Test; Harvey-Godfrey LM Test; Park LM Test; Goldfeld-Quandt Test; White’s Test; Engle’s ARCH Test; and Koenker-Basset Test. Heteroskedasticity can be resolved by: (1) Functional Forms; (2) Generalised (Weighted) Least Squares (GLS/WLS); and (3) White’s Robust-Standard Errors. How to detect heteroskedasticity? The truth is that there is no hard and fast rule for detecting heteroskedasticity. Therefore, more often than not, heteroskedasticity may be a case of educated guesswork, prior empirical experiences or mere speculation. However, informal and formal approaches can be used in detecting the presence of heteroskedasticity such as: Informal approach: Plotting the residuals from the regression against the estimated dependent variable
Formal approach: Perform econometric tests. There are several tests of heteroskedasticity, each based on certain assumptions. The interested reader may want to consult the references listed at the end of the video.
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References and Readings: Asteriou and Hall (2016) Applied Econometrics, 3ed; Wooldridge, J. M. (1995). Econometric Analysis of Cross Section and Panel Data. London, England: The MIT Press, Cambridge, Massachusetts; Baltagi, B.H. (1995) Econometric Analysis of Panel Data. New York, NY: John Wiley and Sons; Hsiao, C. (1986) Analysis of Panel Data, Econometric Society Monographs No. 11. Cambridge, United Kingdom: Cambridge University Press; Gujarati and Porter (2009) Basic Econometrics, International Edition; John, F. (1997) Applied Regression Analysis, Linear Models, and Related Methods, Sage Publications, California, p. 306; Mankiw, GN. (1990) “A Quick Refresher Course in Macroeconomics,” Journal of Economic Literature, Vol. XXVIII, p. 1648
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Is their anyway to email you I have question
@@Hshshsjjjskhsh Kindly state it here. Please may I know from where (location) you are reaching me?
@@CrunchEconometrix Hello I've tested for heteroskedasticity using the BP test and White. The BP test concludes there is no Heteroskedasticity while the white concludes there is. So I was confused to which one I should use. Moreover, when using robust standard errors to solve for heteroskedasticity it still remains within the regression. My model has natural log of the dependent variable so I was stuck on how I could remove heteroskedasticity.
@@Hshshsjjjskhsh You can decide between the BP or White test. I also showed other ways of correcting the problem.
Inspired
It's very useful. Thank you so much!
You are welcome, Sultan!
Great video, thank you!
You are welcome, Nutler🙏🥰
Thanks a lot for simplifying issues that matters
U're welcome, Ngugi. Kindly share the link to my RUclips Channel with your friends and academic community. May God bless you as you do, amen 🙏
Hello and thank you for your amazing videos
U're welcome, Eva❤️. Please may I know from where (location) you are reaching me?
@@CrunchEconometrix Greece and I m a. Phd student.
hi!! Your videos are very helpful!!! Can you also do a video on SVAR in Eviews along with the concept? Thank you.
Hi Suchitra, I'm humbled by the positive feedback. Deeply appreciated! But I'm yet to fully understand SVAR. Once I do, I'll make videos along that line. Please may I know from where (location) you are reaching me?
Thank you. Great tutorial. Hope you can make tutorials using R.
.Thanks for the encouraging feedback, Dioscoro. Deeply appreciated! I'm just learning the R software and hope to have R-versions of my videos very soon :)
your videos are so impressive dear professor ... love and respect from Nepal 🇳🇵🇳🇵 you are helping a lot
Hi Tilak, I'm encouraged and humbled by your feedback. May God bless you. Please share the link to my RUclips Channel with your students and colleagues in Nepal... thanks!
Hi, the regression i am working with is for a quadratic production function, meaning my regression has the independent variables and their squared values. When computing the log-log function, do i need to log my independent variable AND their squared variables to log? or only the original independent variables and leave the squared values as they are
Hi Brian, include the log of both the explvars and the interaction term. Regards.
Hi there, Thank you so much for your lectures. I am working on a data set of stocks return which I have already converted into log returns in Excel then imported it in the Eviews. I am facing the problem of heteroskedasticity even after changing it the estimation option at Huber-white and then Breush pagan test which shows improved values but still heteroskedastic. I am confused with if I can use log log model or not because the data has already been transformed into log model. however if I use Harvey method my results seems to have homoskedacity. waiting for your reply. Thank you so much for the good work.
Hi Meerain, you have your solution already. If the Harvey method solves the problem, go for it and put a note in your work why you used it.
Thanks for the video. I have subscribed the channel. It is amazing...
Hi TA, thanks for the positive feedback and remarks on my RUclips videos. Deeply appreciated! I am very humbled by your subscription. Please may I know from where (location) you are reaching me?
@@CrunchEconometrix hello, I am from Indonesia but studying in Australia. Your video about heteroscedasticity and robustness test was well explained and clearly understandable...
@@tan4620 Wow! You embody 2 amazing countries😍. Please spread the word about my RUclips Channel to your friends and academic networks in Indonesia 🇮🇩 and Australia 🇦🇺. They will find the content helpful too 😊. Much love from Nigeria 🇳🇬! 😀
@@CrunchEconometrix hello Doctor, thank you very much. I will share your video with my friends requiring to learn statistical data analysis...😊👍👍
Thank you so muchh💞💞
U're welcome, Demet. Glad to know you find the video helpful 😊. Please may I know from where (location) you are reaching me?
@@CrunchEconometrix
Hi😀 im from Turkey. I am a graduate student. your video was very useful for me to investigate. 😊😊
Please, a query: I am analyzing a time series and I am applying natural logarithms, in one of the variables I have two data "zero" (0), there is no natural logarithm for zero, I ask, to save this problem, can I assign it to the data a number close to zero, example 0.001 (or similar)? Thanks.
Hi Fernando, "zero"? I don't understand what you mean by this.
Professor, why do we use Breusch-Pagan-Godfrey but not white test? I see that white test is more popular.
which is more suitable for a time-series data with about 360 observations?
Thank you.
Hien, I showed various tests and their assumptions. You decide which one to use.
Could you please make video for pannel data to address hetroscadity using white covariance methoad???
Noted.
Good morning, Doctor
In the event that the goal is as a model (ARDL) and the number of observations is 46, among which is extreme data, what is the solution in this case?
Hi Khaled, I don't quite understand your query. What is "extreme data"?
hi professor , i finaly understand my problem , i use ardl model , wen i just run him with 1000 observation i have problem of( normality , heteroskedasticity , autocorellation ) but when i use only 50 observations evry thig is good so the broblem is in the large number of observations . so can i use 1000 observations and ignore ( normality , heteroskedasticity , autocorellation ) and continue my work or it is false to do that ?
You can't ignore violations of OLS assumptions.
how we get the data set in excel format, i need the data set sheet that is using in Astrio
This data is available on my website free of charge. Here's the link cruncheconometrix.com.ng/shop/
Thank you so much for the information. But One doubt mam, If there is still heteroscedasticity even after using Whites, what wii do?.Pls comment.
Hi Viswan, you may then have to change your variables to closer proxies.
Thank You. I will Try
When I estimate panel data using eviews10, only the residual heteroscedasticity test appears, not the options for choosing the type of heteroscedasticity test.
Hi Raphael, so what is the issue?
@@CrunchEconometrix
Given the limitations of eviews I ended up using stata. Anyway, thanks for your videos about GMM, they helped me a lot.
Hi, when I add an ar(1) term to fix autocorrelation in the equation specification, it now doesnt let me change the covariance method to hubber white. I was wondering how I could fix this. Thanks
I never encountered such an issue so, may not be able to guide you properly. My apologies.
thankk you so much for your help , but i when i tap ln for dependent variable i had an error message (ln is not defined , so i used log , another error message(long for non positive numer) so what can i do please i also tried the white correction and the newey west , but the heteroscedasticity didn't remove :( any one can help me please , i'm using eveiws 11
Hi Tayechi, thanks for the positive feedback. Deeply appreciated! The correct approach is to use the "Genr" to generate the log versions. Is that what you did?
isnt the point to use robust methods is to ignore heteroscedasticity? and may i ask why aren't you using the m-estimates? mm-estimates?
Wewin, I'm sure that I made it clear in the clip that you use the option ROBUST to correct for het. Thanks.
hello mamade thanks for this amazing RUclips channel, please i have a question i am looking to explain the co2 emission by gdp and gdp squared i found that an increase of 1% in gdp increases the C02 by 4.96 and an increase of 1% gdp in square decreases C02 by 0.28.
my question is the following how I can know the threshold from which my GDP begins to decrease and thank you in advance
Kindly consult similar studies for better understanding.
Dear maam, could you pls elaborate how to check heteroskedasticity in panel data using eviews?
Use the same approach described in this video.
Hello mam even if I'm using ardl for regression i need to conduct heteroskedasticity on ols?
Hi Shreesty, yes and watch my ARDL videos. Please may I know from where (location) you are reaching me?
Im from mauritius mam. I need so help im having problem with my serial correlation what can you propose me😔
can u explain heteroscedasticity in panel data?
Hi Bushra, my videos on heteroscedasticity applies to panel data analysis.
@@CrunchEconometrix can u define heteroscedasticity in eviews 10 panel data
But the "Room" variable has p-value greater than 5%. How do you make it statistically significant?
p-value of 0.0929 makes it significant at the 10% level.
How to check cluster robist standard errors in eviews
Hi Gayani, "cluster" applies to panel data but the same procedure.
Is there any difference for white methoad in pannel data ????
No difference.
Hi dear make a video on dumitrescu and hurlin heterogeneous causality on eviews by using 6 variables
Thanks Nabeela, suggestions are noted. Thanks!
@@CrunchEconometrix i recommend your channel to my students and as well follow myself. A lot of love from Pakistan.
I am very grateful...and may God bless you! 🙏
@@CrunchEconometrix my pleasure and honor ❤️
I cant find covariance selection option in my eviews
Hi Gayani, what version are you using?
@@CrunchEconometrix version 9. Where can I find cluster robust standard error? Thank you for the reply
No idea. I use version 10. I'm sure you will find that information on EViews website.
tx
I use localprojections and have still got heteroscedasticity
Hi Andazi, you can use any of the methods explained in my HETEROSCEDASTICY videos to correct it. Thanks.
@@CrunchEconometrix I've logged my dependent variable and also used white standard error like in your video but after the fourth period of my Local Projections I get autocorrelated SE. I will try it with the option of "Robust Least Squares" method of Eviews, which is below the normal OLS
Ok