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Search found 19 matches
- Sun Nov 12, 2017 11:01 am
- Forum: Estimation
- Topic: one-way unbalanced random effect model (Swamy/Arora)
- Replies: 8
- Views: 7735
- Thu Oct 26, 2017 5:33 am
- Forum: Estimation
- Topic: one-way unbalanced random effect model (Swamy/Arora)
- Replies: 8
- Views: 7735
Re: one-way unbalanced random effect model (Swamy/Arora)
Thank you for your answer, Glenn. Still, I was not able to reproduce EViews' standard errors. My results agree with, e.g., the implementation in gretl (for the unbalanced option as per Baltagi/Chang as in gretl version 2017d and the R package plm version 1.6-6) which claims to use the same approach,...
- Mon Oct 23, 2017 4:14 pm
- Forum: Estimation
- Topic: one-way unbalanced random effect model (Swamy/Arora)
- Replies: 8
- Views: 7735
Re: one-way unbalanced random effect model (Swamy/Arora)
I don't think we can simply drop the sigma^2 (s^2) for the estimator of the variance of the regression coefficients, see e.g. Hsiao (2014), formula 3.3.15 (p. 43). The values without sigma^2 are way off to what is given by EViews for the standard errors. Btw: I use s^2 = 0.135242^2 for the example d...
- Sat Oct 21, 2017 2:56 am
- Forum: Estimation
- Topic: one-way unbalanced random effect model (Swamy/Arora)
- Replies: 8
- Views: 7735
Re: one-way unbalanced random effect model (Swamy/Arora)
By calculation of the variance-covariance matrix in the "usual way" I meant calculating it like in OLS but on the quasi-demeaned matrix (Z):
s^2 * (Z'Z)^(-1).
I get the same "S.E. of regression" as EViews, but the variance-covariance matrix is different.
s^2 * (Z'Z)^(-1).
I get the same "S.E. of regression" as EViews, but the variance-covariance matrix is different.
- Fri Oct 20, 2017 2:50 am
- Forum: Estimation
- Topic: one-way unbalanced random effect model (Swamy/Arora)
- Replies: 8
- Views: 7735
one-way unbalanced random effect model (Swamy/Arora)
When I implement the unbalanced random effect model myself (Baltagi/Chang (1994) extension of Swamy/Arora (1979)), I get the same estimates as EViews. I can replicate the coefficient estimates for the hedonic housing prices data set used in Baltagi/Chang (1994), table 2, column SA. EViews seems to m...
- Sat Sep 30, 2017 1:54 am
- Forum: Bug Reports
- Topic: documenation for Hadri's panel unit root test
- Replies: 0
- Views: 2822
documenation for Hadri's panel unit root test
In the documentation for Hadri's panel unit root test (http://www.eviews.com/help/helpintro.html#page/content%2Fadvtimeser-Panel_Unit_Root_Testing.html%23), there is likely a typo in formula (38.63): In Hadri (2000) we see zeta is actually squared in the respecitve formulae. That would give values f...
- Sat Jun 17, 2017 1:29 am
- Forum: Bug Reports
- Topic: one-way unbalanced random effect model
- Replies: 3
- Views: 4750
Re: one-way unbalanced random effect model
Well, the desription of the method has not been changed. But the numbers. The sentence below formula (9.20) is only true if one takes the u^b residuals to stem from the "full length" between regression ("Note that u^b' * P * u^b can be obtained as the OLS residual sum of squares from ...
- Mon Jun 12, 2017 7:37 am
- Forum: Bug Reports
- Topic: one-way unbalanced random effect model
- Replies: 3
- Views: 4750
one-way unbalanced random effect model
I noticed that for the one-way unbalanced random effect model with the Swamy-Arora method, the results given by EViews 9.5 diverge from the values printed in text book of Baltagi (2013), table 9.1 (Hedonic housing data), e.g. the coefficient for variable 'crim' is -0.72 in the text book but -0.74 in...
- Fri Jun 09, 2017 7:43 am
- Forum: Estimation
- Topic: calculate random effects
- Replies: 5
- Views: 4850
Re: calculate random effects
Btw: The "Representations" (View -> Representations) seem a little odd: Under "Substituted Coefficients", it is suggested to add the random effects to get the fitted values. But one gets the fitted values without adding the random effects. (Note: this is different in the fixed ef...
- Wed Jun 07, 2017 6:18 am
- Forum: Estimation
- Topic: calculate random effects
- Replies: 5
- Views: 4850
Re: calculate random effects
Thank you, Glenn.
Is there any guidance in simpler terms available?
Is there any guidance in simpler terms available?
- Fri Jun 02, 2017 4:36 am
- Forum: Estimation
- Topic: calculate random effects
- Replies: 5
- Views: 4850
calculate random effects
I am looking to guidance on how the random effects (cross-section, time/balanced, unbalanced) are calculated. I do not mean the model coefficients but the random effects avaiable via View -> Fixed/Random Effects.
I did not find anything in the user's guide nor in text books.
I did not find anything in the user's guide nor in text books.
- Sun May 29, 2016 11:16 am
- Forum: Suggestions and Requests
- Topic: Lagrange Multiplier Tests for Random Effects
- Replies: 8
- Views: 13384
Re: Lagrange Multiplier Tests for Random Effects
Just checked the latest update. Thank your for implementing the correction. I noticed: The latest docs still have the wrong critical value mentioned: User Guide II, Ch. 44, pp. 894, 896. Well, the paragraph refers to the Baltagi (1998) paper where the typo occured fist, so this is technical not a wr...
- Sun May 29, 2016 10:56 am
- Forum: Bug Reports
- Topic: cross-sec and time effects in two-way unbalanced FE model
- Replies: 0
- Views: 2524
cross-sec and time effects in two-way unbalanced FE model
I am running the Student Lite version 9: For an estimated two-way fixed effects model I feel like there is an a inconsistent presentation for the individual and time effects. (Those effects that can be accessed by View -> Fixed/Random Effects -> Cross-section Effects|PeriodEffects.) I know those eff...
- Sat May 28, 2016 7:19 am
- Forum: Econometric Discussions
- Topic: Panel Data - Fixed Effects
- Replies: 22
- Views: 32630
Re: Panel Data - Fixed Effects
This was very helpful! Is there also a similar guidance when we deal with unbalanced panels? Or maybe a literature hint?
- Tue Dec 08, 2015 11:07 pm
- Forum: Suggestions and Requests
- Topic: Lagrange Multiplier Tests for Random Effects
- Replies: 8
- Views: 13384
Re: Lagrange Multiplier Tests for Random Effects
ad 4.: Concerning the critical value 4.321 vs. 4.231 for the chi-bar-square distribution: Have a look at Baltagi's textbook (2013), p. 74 table 4.1 where we have 4.231 (in the notes to this section there is 4.321 (p. 88)). It is easy to check (here is how I did it with R): crit <- c(7.289, 4.321, 2....