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st: Missing chi squared in negative binomial


From   joe j <[email protected]>
To   [email protected]
Subject   st: Missing chi squared in negative binomial
Date   Mon, 4 Jan 2010 10:27:05 +0100

I ran a couple of negative binomial estimations - three specifications
for each of my five dependent variables - and in just some models I
find chi2 missing. All models produce all other relevant statistics,
such as regression coefficients, standard errors, log likelihood, etc,
but not chi2.

The dependent variable is indeed a count variable and all of the
independent variables are binary variables.

The problem happens only in estimations involving one of the five
dependent variables in all three specifications (one base
specification and and two specifications with one additional variable
each), and another dependent variable in two specifications, but not
in the base specification. I am using Stata 10.1 (I've tired
estimations in a Unix version and a windows version but the results
remain the same)

I show one result below:


Negative binomial regression                      Number of obs   =        603
Dispersion           = mean                       Wald chi2(45)   =          .
Log pseudolikelihood = -701.92706                 Prob > chi2     =          .

------------------------------------------------------------------------------
             |               Robust
      driver1_d |      Coef.   Std. Err.      z    P>|z|     [95%
Conf. Interval]
-------------+----------------------------------------------------------------
    pt_d |  -.0234896   .1536004    -0.15   0.878    -.3245408    .2775617
  ptu_d |   -.030682   .2880005    -0.11   0.915    -.5951526    .5337887
       mf |   .0564921   .1372065     0.41   0.681    -.2124278    .3254119
      lf |   .2947419   .1301125     2.27   0.023      .039726    .5497577
          as |  -.6496328   .3730265    -1.74   0.082    -1.380751    .0814857
          bl |  -.1532725   .2475137    -0.62   0.536    -.6383904    .3318455
          cc |    .372959   .2649483     1.41   0.159    -.1463301    .8922482
          dn |  -.0146073   .3217503    -0.05   0.964    -.6452263    .6160117
          fn |  -.9121529    .396313    -2.30   0.021    -1.688912   -.1353938
          gr |   -19.0335   .7990463   -23.82   0.000     -20.5996    -17.4674
          hu |  -.5921105   .6853176    -0.86   0.388    -1.935308    .7510873
          ir |  -.3976526   .4131799    -0.96   0.336     -1.20747    .4121652
          it |  -.8273693   .3575956    -2.31   0.021    -1.528244   -.1264947
          lx |  -18.57973    1.34663   -13.80   0.000    -21.21907   -15.94038
          nt |   .0327339   .2128318     0.15   0.878    -.3844088    .4498766
          po |  -19.42747    .619623   -31.35   0.000    -20.64191   -18.21303
          sp |  -.4857189   .3377026    -1.44   0.150    -1.147604    .1761661
          sw |  -.1347859   .2303784    -0.59   0.559    -.5863193    .3167475
          uk |  -.3330218   .1446047    -2.30   0.021    -.6164417   -.0496019
          wg |  -.0947101   .1724238    -0.55   0.583    -.4326544    .2432343
       ind_1 |  -.2776653   .9905981    -0.28   0.779    -2.219202    1.663871
       ind_2 |   .3043203   .7201824     0.42   0.673    -1.107211    1.715852
       ind_3 |  -18.48859   .9145886   -20.22   0.000    -20.28115   -16.69603
       ind_4 |  -.1650434   .8352531    -0.20   0.843    -1.802109    1.472023
      ind_10 |   .4019891   .6747375     0.60   0.551     -.920472     1.72445
      ind_11 |     .47631   .7898398     0.60   0.546    -1.071747    2.024368
      ind_12 |   1.619832   .7886493     2.05   0.040     .0741079    3.165556
      ind_13 |   .6454832   .6341807     1.02   0.309    -.5974881    1.888454
      ind_14 |   1.177428   .5591521     2.11   0.035     .0815097    2.273346
      ind_15 |  -.1288919   .7691446    -0.17   0.867    -1.636388    1.378604
      ind_16 |  -.2740728   1.067416    -0.26   0.797     -2.36617    1.818025
      ind_17 |  -.2423931   1.053005    -0.23   0.818    -2.306245    1.821459
      ind_18 |  -.3417625    1.05286    -0.32   0.745    -2.405329    1.721804
      ind_19 |   .3247427   .8173105     0.40   0.691    -1.277157    1.926642
      ind_21 |   1.065388   .6205726     1.72   0.086    -.1509124    2.281688
      ind_22 |   .4374271   .6311023     0.69   0.488    -.7995107    1.674365
      ind_23 |    1.06703    .752356     1.42   0.156    -.4075604    2.541621
      ind_24 |    .750251   .5887075     1.27   0.203    -.4035945    1.904097
      ind_25 |   .5666918   .6344464     0.89   0.372    -.6768002    1.810184
      ind_27 |   .2474848   .9585319     0.26   0.796    -1.631203    2.126173
      ind_28 |  -.1013839   .6862014    -0.15   0.883    -1.446314    1.243546
      ind_30 |   .7012795   .5918125     1.18   0.236    -.4586518    1.861211
      ind_31 |   .6399266   .9591857     0.67   0.505    -1.240043    2.519896
      ind_32 |   1.337355   .5727254     2.34   0.020     .2148341    2.459877
      ind_33 |   .0331696   .6750534     0.05   0.961    -1.289911     1.35625
      ind_34 |   .9601812   .5610771     1.71   0.087    -.1395098    2.059872
       _cons |  -1.004334   .5720001    -1.76   0.079    -2.125433    .1167658
-------------+----------------------------------------------------------------
    /lnalpha |  -1.527903   .3898968                     -2.292086    -.763719
-------------+----------------------------------------------------------------
       alpha |   .2169903   .0846038                      .1010554    .4659304
------------------------------------------------------------------------------

Any pointers would be of much help.
JJ

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