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Re: st: -xtpcse and period dummies- no full table reported due to asymmetric and singular variance matrix


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: -xtpcse and period dummies- no full table reported due to asymmetric and singular variance matrix
Date   Mon, 14 Mar 2011 13:13:33 +0000

So, you are getting a clear signal that the model is a very poor idea
for your data. Why not back off and consider a different treatment of
time, e.g. not using dummies but a linear, quadratic or spline fit?

Nick

On Mon, Mar 14, 2011 at 1:01 PM, Felix Wädlich <[email protected]> wrote:
> Hey Justina,
>
> I include gdp as a measure of market size and gdppc as an indicator
> for development or wealth.
>
> I tried to build up the covariates, but the problem remains: as soon
> as I include the year dummies (yr*), I get the breakdown message. It
> probably is a very basic problem, but I just dont see what I am doing
> wrong, and also what else I can do. Any more thoughts?
>
> Best,
> Felix
>
>
> 2011/3/14 Justina Fischer <[email protected]>:
>> Hi
>>
>> try to build up the covariates step-by-step and observe when breakdown occurs.
>>
>> Why do you include gdppc and gdp simulatenously ?
>>
>> Justina
>> -------- Original-Nachricht --------
>>> Datum: Mon, 14 Mar 2011 13:39:28 +0100
>>> Von: "Felix Wädlich" <[email protected]>
>>> An: [email protected]
>>> Betreff: Re: st: -xtpcse and period dummies- no full table reported due to asymmetric and singular variance matrix
>>
>>> Dear Clive,
>>>
>>> thanks for ur suggestion, but unfortunately that did not do the job.
>>> Still getting the same warning message.Any other tip?
>>>
>>> Best,
>>> Felix
>>>
>>> . xtpcse  c_capital c_loggdppc c_loggdp c_lgovcon c_lgrowth
>>> c_lregionothers yr*, pairwise c(ar1)
>>>
>>> Number of gaps in sample:  8
>>> (note: computations for rho restarted at each gap)
>>> note: yr1 omitted because of collinearity
>>> note: yr2 omitted because of collinearity
>>> (note: estimates of rho outside [-1,1] bounded to be in the range [-1,1])
>>> (note: at least one disturbance covariance assumed 0, no common time
>>> periods
>>>       between panels)
>>> Warning:  variance matrix is nonsymmetric or highly singular
>>>
>>> Prais-Winsten regression, correlated panels corrected standard errors
>>> (PCSEs)
>>>
>>> Group variable:   Country                       Number of obs
>>>      =      2814
>>> Time variable:    year                          Number of
>>> groups   =       134
>>> Panels:           correlated (unbalanced)       Obs per group: min
>>> =         2
>>> Autocorrelation:  common AR(1)
>>>     avg =        21
>>> Sigma computed by pairwise selection
>>>   max =        25
>>> Estimated covariances      =      9045          R-squared
>>>      =    0.0493
>>> Estimated autocorrelations =         1          Wald chi2(0)
>>>     =         .
>>> Estimated coefficients     =        30          Prob > chi2
>>>      =         .
>>>
>>> ------------------------------------------------------------------------------
>>>             |           Panel-corrected
>>>   c_capital |      Coef.   Std. Err.      z    P>|z|     [95%
>>> Conf. Interval]
>>> -------------+----------------------------------------------------------------
>>>  c_loggdppc |  -.5241978          .        .       .
>>>        .           .
>>>    c_loggdp |    .110086          .        .       .
>>>        .           .
>>>   c_lgovcon |   .0016855          .        .       .
>>>        .           .
>>>   c_lgrowth |   .0008101          .        .       .
>>>        .           .
>>> c_lregiono~s |   .1941566          .        .       .
>>>        .           .
>>>         yr1 |  (omitted)
>>>         yr2 |  (omitted)
>>>         yr3 |    .022493          .        .       .
>>>          .           .
>>>         yr4 |   .0273882          .        .       .
>>>          .           .
>>>         yr5 |   .0115461          .        .       .
>>>          .           .
>>>         yr6 |   .0337352          .        .       .
>>>          .           .
>>>         yr7 |   .0598745          .        .       .
>>>          .           .
>>>         yr8 |   .0291169          .        .       .
>>>          .           .
>>>         yr9 |   .0211556          .        .       .
>>>          .           .
>>>        yr10 |   .0255307          .        .       .
>>>          .           .
>>>        yr11 |   .0242099          .        .       .
>>>          .           .
>>>        yr12 |   .0043918          .        .       .
>>>          .           .
>>>        yr13 |  -.0247601          .        .       .
>>>          .           .
>>>        yr14 |   .0009665          .        .       .
>>>          .           .
>>>        yr15 |   .1060365          .        .       .
>>>          .           .
>>>        yr16 |   .0805885          .        .       .
>>>          .           .
>>>        yr17 |   .0332214          .        .       .
>>>          .           .
>>>        yr18 |   .0832608          .        .       .
>>>          .           .
>>>        yr19 |   .0403092          .        .       .
>>>          .           .
>>>        yr20 |   .0195583          .        .       .
>>>          .           .
>>>        yr21 |   .0004272          .        .       .
>>>          .           .
>>>        yr22 |    .013192          .        .       .
>>>          .           .
>>>        yr23 |   .0135001          .        .       .
>>>          .           .
>>>        yr24 |   .0059468          .        .       .
>>>          .           .
>>>        yr25 |   .0014196          .        .       .
>>>          .           .
>>>        yr26 |    -.00606          .        .       .
>>>          .           .
>>>       _cons |  -.0334178          .        .       .
>>>        .           .
>>> -------------+----------------------------------------------------------------
>>>         rho |   .8822325
>>> ------------------------------------------------------------------------------
>>>
>>>
>>> 2011/3/13 Clive Nicholas <[email protected]>:
>>> > Felix Waedlich:
>>> >
>>> >> I have to run a Prais-Winsten-regression with Period-Dummies and
>>> panel-corrected standard errors [by xtpcse, corr(ar1)], since my (unbalanced)
>>> panel needs correction for serial correlation, groupwise heteroskedasticity
>>> and contemporaneous correlation. I need the period dummies to control for
>>> common shocks and trends, since I have a Diffusion variable respectively
>>> spatial lag, which requires a conservative test against alternative external
>>> influences.
>>> >> Without period dummies, there appears to be no problem: Stata reports
>>> me all the coefficients, the z-values, etc. But when I include the period
>>> dummies, Stata says "warning: variance matrix is nonsymmetric or highly
>>> singular", and only lists the coefficients, but no standard errors, no z-values,
>>> etc.. Since this is a standard specification in my field of research, I am
>>> wondering how I can solve this problem. Any suggestions? Help much
>>> appreciated
>>> >> I read the only article on Statalist about this error message, but it
>>> really does not help me, and i dont really see how my data suffers from
>>> these problems.
>>> >
>>> > Try centering your continously measured variables by period and then
>>> > run -xtpcse, c(ar1)- again. Doing this comes at the cost of robbing
>>> > your model of explaining the variance in your response variable that
>>> > it would otherwise in a 'normal' model.

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