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From |
Julius Frédéric André <juliusandre@gmail.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: RE: RE: Re: RE: panel data analysis using xtregar |

Date |
Wed, 30 Nov 2005 13:10:27 +0100 |

Jean, thanks for the hint, even though I was initially planning not to use an LSDV approach due to the loss in df. I will look into it, the paper from Bruno on the method in xtlsdvc is quite appealing. Regards, Julius -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Salvati, Jean Sent: 29 November 2005 15:40 To: statalist@hsphsun2.harvard.edu Subject: st: RE: RE: Re: RE: panel data analysis using xtregar Julius, You may also want to look at the bias-corrected LSDV estimator implemented in the Stata module xtlsdvc by Giovanni Bruno. See the following page: http://ideas.repec.org/c/boc/bocode/s450101.html Jean Salvati > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Julius > Frédéric André > Sent: Tuesday, November 29, 2005 3:19 AM > To: statalist@hsphsun2.harvard.edu > Subject: st: RE: Re: RE: panel data analysis using xtregar > > Thanks to Rodrigo and Steve for taking the time to comment, I will > consider these in my work. > > Regards, > > JULIUS > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Rodrigo > Alfaro > Sent: 27 November 2005 17:17 > To: statalist@hsphsun2.harvard.edu > Subject: st: Re: RE: panel data analysis using xtregar > > Julius, first lagged dependent variable (LDV) with xtreg, fe and > xtregar is not the same. xtregar works like Cochrane-Orcutt regression > (meaning you have the first observation... read Autocorrelation > section in any textbook to learn about it)... for that purpose you > have to set what kind of rho will be in your regression (option > rhotype)... > the default is Durbin-Watson. > Details of the formula appear in the manual reference. If the > coefficient of your LDV is near to 1 maybe you have a Unit Root case > (note that this coefficient is downward-biased if it is positive > Nickell 1968). There is a huge (and maybe more than that) about LDV+FE > versus Arellano-Bond (1991, GMM estimator), Anderson-Hsiao (1981, IV > estimator)... it seems to me that the bias generated by LDV+FE it is > not so bad in compare with weak instruments. > Hahn-Kuersteiner (2000) propose an asymptotic correction for that > parameter... all these is available in Arellano's book. Rodrigo. > > > ----- Original Message ----- > From: "Steve Stillman" <stillman@motu.org.nz> > To: <statalist@hsphsun2.harvard.edu> > Sent: Saturday, November 26, 2005 8:48 PM > Subject: st: RE: panel data analysis using xtregar > > > > Julius. It is not exactly clear what your model is here, but, in > > general, > > > panel data models with lagged dependent variables cannot be > > consistently estimated by directly entering the lagged > variable as a > > RHS variable. It sounds like you should have a look at xtabond and > > the user-written > > xtabond2 for your model. > > > > Cheers, > > Steve > > > > -----Original Message----- > > From: owner-statalist@hsphsun2.harvard.edu > > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Julius > > Frédéric André > > Sent: Sunday, November 27, 2005 7:26 AM > > To: statalist@hsphsun2.harvard.edu > > Subject: st: panel data analysis using xtregar > > > > > > Dear statalist, > > > > Currently researching balanced panel data using insolvency > prediction > > estimates for different companies and regressing them (among other > > controlling, time-variant variables) on time dummies to > evaluate the > > effects of a policy introduction in a certain year. I am > using xtreg, > > fe for evaluation, the panel is described by t=12 and > i=110. I presume > > autocorrelation of the insolvency predictor (ie. the dependent > > variable) and therefore constructed a dataset with a lagged > variable > > for the insolvency predictor, hence also had to eliminate the first > > period of the original dataset. It turned out that the estimator of > > the lagged variable is indeed highly significant. > > > > Now I also consider using xtregar. Being new to stata (also > to panel > > data and time series analysis), however, I unfortunately could not > > find the underlying formula used by Stata up to now. Would such an > > autoregressive model be similar to the approach I did manually with > > introducing a lagged variable and deleting the values of the first > > period for each I? The stata result being different for the AR(1) > > model and the fixed-effect model including a lagged variable do not > > corroborate this assumption, so I assume some other > underlying model. > > I know that an AR appproach incorporates past values, but does this > > mean the past error term, the past dependent or the past > independent > > variable (or all of them)? It would be of great help if > someone could > > provide a formula here or give a brief statement if I > should resort to > > xtregar at all if I assume autocorrelation anyways (so that the > > applying AR is simply not necessary anymore). > > > > Additionally, I would like to backup my decision to include > a lagged > > variable in the model by testing on autocorrelation, using a > > Durbin-Watson substitute for panel data, such as Bhargava et al. I > > know that Stata can calculate this statistic when using xtregar, > > however, it seems to me that the reported output is the > result AFTER > > applying the AR (1) model, indicating only the presence or > absence (or > > degree) of autocorrelation left after using the AR model? Is this > > correct, or does the test statistic indicate autocorrelation before > > using the AR model? > > > > Lastly, I am not sure whether I could also use the Baltagi-Wu test > > score alternatively, seeing to it that I have a balanced > dataset. Is > > this test statistic only working with unbalanced data? > > > > The three preceding issues certainly are still on a somewhat basic > > level, however, I would definitely appreciate useful > comments on any > > or all of these! > > > > > > Thank you very much in advance, > > > > JULIUS ANDRE > > > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: RE: RE: Re: RE: panel data analysis using xtregar***From:*"Salvati, Jean" <JSalvati@imf.org>

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