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Hi all, I am estimating a simple regression: Y = C(1) + C(2)*X (1) Suppose I find that: X = X1 + X2 So that (1) can be rewritten as: Y = C(1) + C(3)*X1 + C(4)*X2 (2) Now I am interested in investigating (but don't know how to, please help!): 1. Whether regressions (1) and (2) are the same, i.e. whet...

Thank you again Gareth! I tried your suggestion, but it doesn't seem to be a practical solution because Eviews keeps warning "Out of memory" (although I believe my laptop is not too bad). My panel has 18 periods and 1677 cross-sections. And there's just another matter (purely econometrics)...

Thank you very much Gareth. However, does it mean that this is the only way to go ahead? I guess there should be an easier way to get round the problem. What about the Wald test, do you know how to perform a Wald test to compare the coefficient on X1 when SIZE=1 with the corresponding coefficient wh...

Hi, Does anyone know what is the maximum number of regressors we can add the LHS of an equation in Eviews? It seems to me that I could not add more than 1000 regressors in 1 equation. If so, I just don't know if there is anyway that I can compare the coefficient of a regression (with fixed time and ...

Well, I think I now know the problem (but unfortunately I don't know how to overcome it :-( Because adding fixed effects will essentially add year and cross-section dummies variables to the regression, it seems that I have to interact the (sub-group identifiers) dummies (i.e. Size=1, Size=2, Size=3)...

As Startz suggested in another post, we can use interactions to test the difference between a coefficient when regression is run across 3 (or more) sub-samples. However, the approach seems problematic when I add fixed effects to the regression. Specifically, suppose that I have a unbalanced dated pa...

Sorry for this messing around, but I have one more enquiry. Startz's solution is OK, but when I add fixed time and fixed cross-section effect and require the coefficient covariance clustered by period, there seems to be a problem. Specifically, when I run the following equation in the whole sample: ...

Thank you very much Startz. You answer really helps, as usual.

I posted this question a while ago and unfortunately I received no response. So I guess I failed to explain my question clearly. Hope I can make it better this time. In an unbalanced dated panel, I sub-divide my sample into 3 sub-groups (categorized by, say, SIZE, which could be either 1, 2 or 3). I...

Hi, I am working with a dated panel. I want to estimate the same regression across five subsamples (5 quintiles of firms ranked by firm size): equation a_all.ls(cx=f,per=f,cov=perwhite) wcapex_a c vb_total_la1 log(wbv_a_la1) misprice_firm_la1 wc_cf_a My first question is how to compare the coefficie...

Thank you very much Glenn. I can confirm that I've tried the White covariance without restructuring the workfile (i.e. when the workfile is still as a dated panel), and the problem seemed to be resolved.

Hi Glenn, First of all, thank you very much for the response. You're absolutely right that the a3t is not estimated as a panel. However, because in this case the observations are firm-years, clustering by firm-year should produce White stadard errors (as explained in page 12 of the Gow et al's paper...

Hi, I posted a while ago asking for instruction to estimate two-way cluster robust standard errors (i.e. clustered by BOTH cross section and period, as described in page 12 of the attached paper). Glenn kindly provided me with the answer, which I very much appreciate. I quote Glenn's answer below: &...

Thank you very much Glenn. The answer is excellent and very to the point. I've followed the suggestions and the results look very "reliable" (as I've compared the results with some "comparable" methodologies).

Chau

I want to calculate clustered standard errors for the coefficients estimated from OLS regression on panel data. Eviews provides the option to calculate the coefficient covariance matrix using White – cross section and White – period. But the problem is that I want the 2-way clustered standard error,...