Re: st: RE: Testing serial correlation by predicted residuals

[Waedlich Felix <fwaedlich@gmail.com>]

Thanks Nick. 

I am not sure though how to interpret that -xtserial- still indicates strong autocorrelation with or without the LDV and Time effects, whereas the significance of the lagged predicted values drastically decreases after including the LDV.
Felix
Am 09.03.2011 um 22:40 schrieb Nick Cox:

> Can't comment on the specific merits of this, but I'd always plot residuals vs lagged residuals too. 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> Waedlich Felix
> 
> I still have problems with my unbalanced panel (140 countries, 27 years) when I want to detect whether my model suffers from serial correlation.
> The -xtserial- command indicates autocorrelation even after including a LDV and time effects. Other tests (like -estat dwatson-) dont work due to my unbalanced panel. 
> I found an alternative solution from Pluemper/Troeger:  first estimate -xtpcse- (without LDV), then -predict xb if e(sample)- to generate residuals,  -gen residuals = DV - xb- and run -xtpcse residuals independent variables.... und lagged_residuals -. If the lagged residuals are significant (by t-test) my models suffers from autocorrelation. After adding the LDV to 3., looking at t-test again, and check whether the null of independent errors still has to be rejected.
> In my case the lagged_residuals are significant (in res model without LDV) and insignificant after adding the LDV.
> Do you think this constitutes a valid test for autocorrelation?
> And don't get me wrong, unit root test are probably a good idea for my data set, but i cannot get into them now, since I am kinda running out of time.
> 
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