st: RE: Cross-sectional dependence in fixed effects panel model

["Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>]

Christina,

Driscoll-Kraay SEs rely on large-T asymptotics.  Your T is rather small
- only 11 - and that suggests D-K SEs may not be the way to go.

Daniel Hoechle's 2007 SJ paper (7:3) on xtscc has a nice and accessible
discussion of D-K SEs and more.

HTH,
Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> christina sakali
> Sent: 14 September 2011 10:44
> To: statalist
> Subject: st: Cross-sectional dependence in fixed effects panel model
> 
> Dear Statalisters,
> 
> I would like to estimate a fixed effects panel model with 
> possible cross-sectional dependence (contemporaneous 
> correlation). My sample consists of N=11, T=11.
> 
> My question regards both the interpretation of the tests 
> contained in xtcsd and the estimation with Driscoll-Kraay 
> S.E. under xtscc:
> 
> 1. First, I am not completely sure how I should interpret 
> results of the tests contained in xtcsd and xttest2, given 
> the fact that I got some conflicting results from these 
> tests, which are provided below.
> My feeling is that I should trust the results of the Pesaran 
> test (as more appropriate for my sample), which indicates the 
> presence of cross-sectional dependence, but again I am a 
> little confused regarding the conflicting and inconclusive 
> results from the other tests.
> 
> 2. Second, if my model does suffer from cross-sectional 
> dependence, I am wondering whether the Driscoll-Kraay S.E. 
> (xtscc) are appropriate for my case. De Hoyos and Sarafidis 
> (2006, p.1-2) clearly mention that if "cross-sectional 
> dependence is caused by the presence of common factors, which 
> are unobserved ... but uncorrelated with the included 
> regressors, ...  one may chose to rely on standard FE/RE 
> methods and correct the SE by following the approach proposed 
> by Driskoll and Kraay (1998). On the other hand, if the 
> unobserved components that create interdependencies across 
> cross-sections are correlated with the included regressors, 
> these approaches will not work and the FE and RE estimators 
> will be biased and inconsistent. In this case, one may follow 
> the approach proposed by Pesaran (2006).
> 
> Based on the above, I would like to ask if there is a way to 
> find out which of the two cases mentioned by De Hoyos and 
> Sarafidis (2006) is relevent for my model and what other 
> alternatives I 've got in Stata, in order to produce robust 
> S.E. in presence of contemporaneous correlation, apart from 
> the Driskoll and Kraay S.E.
> 
> In case this is relevant to the above, the residuals in my 
> model seem to be heteroscedastic but not serially correlated 
> (after checking the stats in xttest 3 and xtregar ..., fe lbi)
> 
> I am using Stata 9.2 at home but I could possibly have access 
> to some newer version of Stata at faculty.
> 
> 
> Results from xtcsd and xttest2 are provided below:
> 
> qui xtreg fdi gg rulc trade tert sec eu, fe
> 
> . xtcsd, pesaran abs
> 
> Pesaran's test of cross sectional independence =     2.899, 
> Pr = 0.0037
> 
> Average absolute value of the off-diagonal elements =     0.302
> 
> . xtcsd, friedman
> 
>  Friedman's test of cross sectional independence =    17.537, 
> Pr = 0.0633
> 
> . xtcsd, frees
> 
>  Frees' test of cross sectional independence =     0.244
> |--------------------------------------------------------|
>   Critical values from Frees' Q distribution
>                       alpha = 0.10 :   0.2333
>                       alpha = 0.05 :   0.3103
>                       alpha = 0.01 :   0.4649
> 
> . xttest2
> 
> Breusch-Pagan LM test of independence: chi2(55) =    79.711, 
> Pr = 0.0164
> Based on 11 complete observations over panel units
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