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Re: st: time-invariant regressors in xtdpdsys


From   Hewan Belay <[email protected]>
To   Stata List <[email protected]>
Subject   Re: st: time-invariant regressors in xtdpdsys
Date   Tue, 5 Aug 2008 08:53:12 -0700 (PDT)

I want to add to my question below a more stata-oriented (as opposed to 
econometric) question but related to the same topic. I estimated a dynamic 
model including time-invariant regressors using -xtdpdsys-. Since -xtdpd- 
is a generalised version of the former, it should be possible to replicate 
this estimation in -xtdpd-, but I was not able to. Here is an example:

webuse abdata, clear
by id, s: egen avg_emp = mean(emp)
/* No. 1 */    xtdpdsys 	n w k avg
/* No. 2 */    xtdpdsys 	n w k
/* No. 3 */    xtdpd L(0/1).n w k, div(w k) dgmmiv(n) lgmmiv(n)

Equation 3 was an attempt to replicate the results of equation 1. Instead 
however, (3) produces results identical to (2) i.e. is not able to 
identify the time-invariant variable. I tried different ways of writing 
the -xtdpd- command to get the results of (1), to no avail. How can -xtdpd-
 be made to replicate Blundell-Bond with time-invariant regressors, which 
it should be able to, since it is supposed to be able to accomodate 
estimations of Blundell-Bond as well as Arellano-Bond (or -xtdpdsys- and -
xtabond-)? Below please find the full results of the above stated commands.

Thanks in advance,
Hewan


.. webuse abdata, clear

.. by id, s: egen avg_emp = mean(emp)

.. /* No. 1 */    xtdpdsys         n w k avg
note: avg_emp dropped from div() because of collinearity

System dynamic panel-data estimation         Number of obs         =       891
Group variable: id                           Number of groups      =       140
Time variable: year
                                             Obs per group:    min =         6
                                                               avg =  6.364286
                                                               max =         8

Number of instruments =     38               Wald chi2(4)          =   4550.53
                                             Prob > chi2           =    0.0000
One-step results
------------------------------------------------------------------------------
           n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           n |
         L1. |   .5514304    .043601    12.65   0.000      .465974    .6368869
           w |  -.6130319   .0513926   -11.93   0.000    -.7137595   -.5123042
           k |   .3334923   .0239851    13.90   0.000     .2864823    .3805022
     avg_emp |  -.0032794   .0042283    -0.78   0.438    -.0115668    .0050079
       _cons |   2.541278   .1785823    14.23   0.000     2.191263    2.891293
------------------------------------------------------------------------------
Instruments for differenced equation
        GMM-type: L(2/.).n
        Standard: D.w D.k
Instruments for level equation
        GMM-type: LD.n
        Standard: _cons

.. /* No. 2 */    xtdpdsys         n w k

System dynamic panel-data estimation         Number of obs         =       891
Group variable: id                           Number of groups      =       140
Time variable: year
                                             Obs per group:    min =         6
                                                               avg =  6.364286
                                                               max =         8

Number of instruments =     38               Wald chi2(3)          =   4601.24
                                             Prob > chi2           =    0.0000
One-step results
------------------------------------------------------------------------------
           n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           n |
         L1. |   .5419106   .0416037    13.03   0.000     .4603688    .6234524
           w |  -.6152988   .0510225   -12.06   0.000     -.715301   -.5152965
           k |   .3306255   .0235661    14.03   0.000     .2844369    .3768142
       _cons |   2.531675   .1771563    14.29   0.000     2.184455    2.878895
------------------------------------------------------------------------------
Instruments for differenced equation
        GMM-type: L(2/.).n
        Standard: D.w D.k
Instruments for level equation
        GMM-type: LD.n
        Standard: _cons

.. /* No. 3 */    xtdpd L(0/1).n w k, div(w k) dgmmiv(n) lgmmiv(n)

Dynamic panel-data estimation                Number of obs         =       891
Group variable: id                           Number of groups      =       140
Time variable: year
                                             Obs per group:    min =         6
                                                               avg =  6.364286
                                                               max =         8

Number of instruments =     38               Wald chi2(3)          =   4601.24
                                             Prob > chi2           =    0.0000
One-step results
------------------------------------------------------------------------------
           n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           n |
         L1. |   .5419106   .0416037    13.03   0.000     .4603688    .6234524
           w |  -.6152988   .0510225   -12.06   0.000     -.715301   -.5152965
           k |   .3306255   .0235661    14.03   0.000     .2844369    .3768142
       _cons |   2.531675   .1771563    14.29   0.000     2.184455    2.878895
------------------------------------------------------------------------------
Instruments for differenced equation
        GMM-type: L(2/.).n
        Standard: D.w D.k
Instruments for level equation
        GMM-type: LD.n
        Standard: _cons




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