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st: Missing standard error for Nlogit Inclusive Value


From   agostino@unical.it
To   statalist@hsphsun2.harvard.edu
Subject   st: Missing standard error for Nlogit Inclusive Value
Date   Wed, 9 Feb 2005 18:30:45 +0100

dear all,
I'm investigating financing decisions of small firms and I'm using a nested
logit to model them.
When I use STATA 8, I always get dots in the (IV params) section, as follows:



 nlogit Dchoice (posschoi= lsdsd_o lsdsd_b lrdinten_o lrdinten_b lage_o
lage_b ) (ext_int= llncapinv_a lincen_a ltgasset_a  lcashflo_a llever_a
difflev_a), group(grp)

tree structure specified for the nested logit model

        top --> bottom

     ext_int      posschoi
--------------------------
        debt                 0
                             1
       autof                 2

initial:        = -890.61013
rescale:        = -890.61013
rescale eq:     = -881.41885
Iteration 0:   log likelihood = -881.41885
Iteration 1:   log likelihood = -881.11793  (backed up)
Iteration 2:   log likelihood = -881.11422  (backed up)
Iteration 3:   log likelihood = -880.78024  (backed up)
Iteration 4:   log likelihood = -880.54555  (backed up)
Iteration 5:   log likelihood = -880.43086  (backed up)
Iteration 6:   log likelihood = -880.41612  (backed up)
Iteration 7:   log likelihood = -880.36322  (backed up)
Iteration 8:   log likelihood = -880.32841  (backed up)
Iteration 9:   log likelihood = -880.29477  (backed up)
Iteration 10:  log likelihood = -879.81536  (backed up)
Iteration 11:  log likelihood = -879.79723  (backed up)
Iteration 12:  log likelihood = -879.37898
Iteration 13:  log likelihood = -879.03583
Iteration 14:  log likelihood = -878.85494
BFGS stepping has contracted, resetting BFGS Hessian (0)
Iteration 15:  log likelihood = -878.77095
Iteration 16:  log likelihood = -878.75297  (backed up)
Iteration 17:  log likelihood = -878.75255  (backed up)

Nested logit
Levels             =          2                 Number of obs      =      3972
Dependent variable =    Dchoice                 LR chi2(12)        =   1151.62
Log likelihood     = -878.75255                 Prob > chi2        =    0.0000

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
posschoi     |
     lsdsd_o |    .004309   .0186682     0.23   0.817      -.03228     .040898
     lsdsd_b |   .0039733   .0186788     0.21   0.832    -.0326365    .0405831
  lrdinten_o |   -.257973   .4507444    -0.57   0.567    -1.141416    .6254699
  lrdinten_b |  -.0662926    .446717    -0.15   0.882    -.9418418    .8092566
      lage_o |  -2.014462   .0959822   -20.99   0.000    -2.202584   -1.826341
      lage_b |  -.8130758          .        .       .            .           .
-------------+----------------------------------------------------------------
ext_int      |
 llncapinv_a |   .1565505   .0318874     4.91   0.000     .0940524    .2190486
    lincen_a |  -.2021057   .1224135    -1.65   0.099    -.4420317    .0378203
  ltgasset_a |   .0052008   .0041965     1.24   0.215    -.0030242    .0134257
  lcashflo_a |  -.0000758   .0000223    -3.41   0.001    -.0001195   -.0000322
    llever_a |  -.0287271   .0023722   -12.11   0.000    -.0333766   -.0240776
   difflev_a |   .0520366   .0059348     8.77   0.000     .0404046    .0636687
-------------+----------------------------------------------------------------
(IV params)  |
             |
ext_int      |
       /debt |  -.0194676   .0893842    -0.22   0.828    -.1946575    .1557223
      /autof |          1          .        .       .            .           .
------------------------------------------------------------------------------
LR test of homoskedasticity (iv = 1): chi2(0)=    3.46    Prob > chi2 =      .
------------------------------------------------------------------------------

.
end of do-file

.


Notice that all regressors are interacted with alternative specific constants
("o"  for alternative 0, "b" for alternative 1, "a" for alternative 2 in the
tree above), as all explanatory variables are firm specific attributes. I do
not have choice specific attributes.
I have tried several specifications, some of them include alternative specific
constants, some do not (as the one reported above), but the same result pops
up for the INCLUSIVE VALUE /autof: its coefficient is either 1 or 0.5, but its
standard error is always missing...
What could it be the cause of  it?
Many thanks in advance
Mariarosaria


Mariarosaria Agostino, PhD student
Dipartimento di Economia e Statistica
UniversitÓ della Calabria
Arcavacata di Rende (CS)
Italia


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