Regression output featuring a period for one variable

[Claire McKenna]

I'm using logit regression to link state-level policies with an individual's probability of reemployment. As controls, I feature a handful of state-by-month labor market data. As in prior work that's used the same data I'm working with, and that's explored the same outcome, the model also controls for squared and cubed values of these labor market slack measures: so unemployment rate, expressed as a proportion (e.g., 0.065); then unemployment rate^2 (0.004225); and unemployment rate^3 (0.000275). Some of the non-squared or -cubed proportions are rather small; which means the squared and cubed values are even smaller. I assume that's why the regression output associated with those variables shows a dot or period, as below (see INITRATE3). Is there anything to be concerned about here? Should I remove the variable for which a dot is showing up?

                      ur_sa |   8.80e-10   1.12e-08    -1.64   0.100     1.38e-20    56.01906
                     ur2_sa |   2.56e+64   2.57e+66     1.47   0.141     4.65e-22    1.4e+150
                     ur3_sa |   5.2e-175   1.3e-172    -1.56   0.119            0    1.28e+45
                        iur |   .1303132   .9846071    -0.27   0.787     4.83e-08      351892
                       iur2 |   1.09e+14   8.32e+15     0.42   0.673     7.56e-52    1.56e+79
                       iur3 |   3.96e-41   8.42e-39    -0.44   0.661     6.3e-222    2.5e+140
                   initrate |   .0017314    .083949    -0.13   0.896     9.25e-45    3.24e+38
                  initrate2 |   1.1e-221   3.5e-218    -0.16   0.872            0           .
                  initrate3 |          .          .     0.19   0.849            0           .
                  empgrowth |   1.156185   .0878403     1.91   0.056     .9962262    1.341828
                       emp2 |   .9770312   .0225311    -1.01   0.314     .9338542    1.022205
                       emp3 |   1.002295   .0017089     1.34   0.179     .9989514     1.00565

[Carlo Lazzaro]

Claire:
the main issue with your regression outcome is that there's no evidence that your coefficients differ from 1 if expressed on OR metric.
Why this is so I cannot say, as you reported only a part of what Stata gave you back and no regression code at all.

[Claire McKenna]

Right. Thanks, Carlo Lazzaro. Here's the code, and the output. In the meantime, I'm going to investigate if anything went wrong when I merged data sets...:

logit reemp3 i.rq##i.prepostperiod i.hidh##i.prepostperiod i.lorh##i.prepostperiod i.lorech##i.prepostperiod b3.age_group b1.race_wbho b4.edu4 i.woman##i.marstdum1##i.ownkidd_18 b1.ind_nilf b1.uh_occmaj_b2 sampjl b1.durg ur_sa ur2_sa ur3_sa iur iur2 iur3 initrate initrate2 initrate3 empgrowth emp2 emp3 incrate_jhu stringd i.cutoff3n if sampall==1 & age>=18 & age<65 [pw=wtfinl], vce(cluster statefip) or

note: 11.uh_occmaj_b2 omitted because of collinearity.
Iteration 0:   log pseudolikelihood =  -20682850  
Iteration 1:   log pseudolikelihood =  -19713507  
Iteration 2:   log pseudolikelihood =  -19682778  
Iteration 3:   log pseudolikelihood =  -19682601  
Iteration 4:   log pseudolikelihood =  -19682601  

Logistic regression                                     Number of obs = 10,380
                                                        Wald chi2(43) =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -19682601                        Pseudo R2     = 0.0484

                                             (Std. err. adjusted for 45 clusters in statefip)
---------------------------------------------------------------------------------------------
                            |               Robust
                     reemp3 | Odds ratio   std. err.      z    P>|z|     [95% conf. interval]
----------------------------+----------------------------------------------------------------
                       1.rq |   1.303789   .2088128     1.66   0.098     .9525336    1.784573
            1.prepostperiod |    1.96668   .4754841     2.80   0.005     1.224444    3.158848
                            |
           rq#prepostperiod |
                       1 1  |   .7607078   .1140951    -1.82   0.068     .5669569    1.020671
                            |
                     1.hidh |   .9630058   .1174915    -0.31   0.757       .75819     1.22315
                            |
         hidh#prepostperiod |
                       1 1  |    1.01543   .1280341     0.12   0.903     .7930919      1.3001
                            |
                     1.lorh |   1.058664   .0863695     0.70   0.485     .9022237    1.242231
                            |
         lorh#prepostperiod |
                       1 1  |   1.029519   .1007378     0.30   0.766     .8498547    1.247165
                            |
                   1.lorech |   .7904797   .1392273    -1.33   0.182      .559717    1.116382
                            |
       lorech#prepostperiod |
                       1 1  |   1.270628   .2499634     1.22   0.223     .8641044    1.868402
                            |
                  age_group |
                     18-24  |    1.14913   .1105757     1.44   0.149     .9516163    1.387639
                     25-34  |   .9743042   .0852849    -0.30   0.766     .8207017    1.156655
                     45-54  |   .9802508   .0706162    -0.28   0.782     .8511725    1.128904
                     55-64  |   .8323383   .0606694    -2.52   0.012     .7215319    .9601613
                            |
                  race_wbho |
                2 black nh  |   .6766168    .075328    -3.51   0.000     .5439741    .8416031
         3 hispanic/latino  |   .9216113   .0871562    -0.86   0.388     .7656851    1.109291
                  other nh  |   .7288072   .0790963    -2.91   0.004     .5891598    .9015549
                            |
                       edu4 |
            1 Less than HS  |    1.00358   .1162179     0.03   0.975     .7997975    1.259285
               2 HS or GED  |   1.002949   .0888458     0.03   0.973     .8430934    1.193115
3 Some college or Associ..  |   .9976285   .0869765    -0.03   0.978     .8409271     1.18353
                            |
                    1.woman |   1.131493   .0843544     1.66   0.098      .977673    1.309514
                1.marstdum1 |   1.481742   .1759729     3.31   0.001      1.17404    1.870087
                            |
            woman#marstdum1 |
                       1 1  |   .7691248   .1265107    -1.60   0.111     .5571672    1.061715
                            |
                 ownkidd_18 |
1: Own children, <18, in..  |   .8563432   .1368613    -0.97   0.332      .626049    1.171352
                            |
           woman#ownkidd_18 |
                         1 #|
1: Own children, <18, in..  |   1.242547   .2498485     1.08   0.280     .8378289    1.842768
                            |
       marstdum1#ownkidd_18 |
                         1 #|
1: Own children, <18, in..  |   1.043226   .2892507     0.15   0.879     .6058561    1.796335
                            |
 woman#marstdum1#ownkidd_18 |
                         1 #|
                         1 #|
1: Own children, <18, in..  |   .8733474   .2490553    -0.47   0.635     .4993984    1.527309
                            |
                   ind_nilf |
                         2  |   .2856043   .0913719    -3.92   0.000     .1525613    .5346693
                         3  |   .8386183   .3070126    -0.48   0.631     .4092089    1.718635
                         4  |    .891526    .394866    -0.26   0.795     .3742209    2.123929
                         5  |   .8300109   .2969469    -0.52   0.603     .4116761    1.673447
                         6  |   .7522237     .24655    -0.87   0.385     .3956907    1.430007
                         7  |   .8772725   .2995761    -0.38   0.701     .4492223    1.713199
                         8  |   .9668094   .3269283    -0.10   0.920     .4983169    1.875755
                         9  |   .6830549   .2527665    -1.03   0.303     .3307242    1.410734
                        10  |   .9983931   .3128206    -0.01   0.996      .540256     1.84503
                        11  |   .6522217   .2161597    -1.29   0.197     .3406351    1.248823
                        12  |   .8519087   .3124858    -0.44   0.662     .4151132    1.748314
                        13  |   .9185155   .3199965    -0.24   0.807     .4640248    1.818159
                        14  |    .438974   .3880842    -0.93   0.352     .0776097    2.482913
                            |
               uh_occmaj_b2 |
professional and related..  |   1.156541   .1200235     1.40   0.161      .943681    1.417415
       service occupations  |     1.2894   .1463898     2.24   0.025     1.032163    1.610748
sales and related occupa..  |   1.062328   .1361729     0.47   0.637     .8263212    1.365742
office and administrativ..  |   1.031202   .1366578     0.23   0.817     .7953167    1.337049
farming, fishing, and fo..  |    .675783   .2323057    -1.14   0.254     .3445086    1.325606
construction and extract..  |    1.11496   .1612931     0.75   0.452     .8396964    1.480459
installation, maintenanc..  |   .9600837   .2208604    -0.18   0.859     .6116406     1.50703
    production occupations  |   1.003564   .0862979     0.04   0.967     .8479084    1.187794
transportation and mater..  |   1.116894   .1430619     0.86   0.388     .8689248    1.435627
              armed forces  |          1  (omitted)
                            |
                     sampjl |   1.444842   .0975986     5.45   0.000     1.265674    1.649372
                            |
                       durg |
                 5-8 weeks  |   .7304258   .0516235    -4.44   0.000     .6359408    .8389489
                9-12 weeks  |   .6455754   .0481113    -5.87   0.000     .5578424    .7471064
               13-16 weeks  |   .4872494   .0368639    -9.50   0.000     .4200991    .5651333
               17-20 weeks  |   .3956191   .0542556    -6.76   0.000     .3023726     .517621
               21-26 weeks  |   .4462529   .0398389    -9.04   0.000     .3746198    .5315834
               27-32 weeks  |   .4439254   .0853959    -4.22   0.000     .3044866    .6472198
               33-38 weeks  |   .4067732   .0550623    -6.65   0.000     .3119829     .530364
               39-44 weeks  |   .4229108   .1022635    -3.56   0.000     .2632818    .6793238
               45-50 weeks  |   .3427082    .109676    -3.35   0.001     .1830277    .6417003
               51-52 weeks  |   .3869811   .0802235    -4.58   0.000      .257769    .5809635
                 >52 weeks  |   .2136835   .0428064    -7.70   0.000     .1442956    .3164382
                            |
                      ur_sa |   8.80e-10   1.12e-08    -1.64   0.100     1.38e-20    56.01906
                     ur2_sa |   2.56e+64   2.57e+66     1.47   0.141     4.65e-22    1.4e+150
                     ur3_sa |   5.2e-175   1.3e-172    -1.56   0.119            0    1.28e+45
                        iur |   .1303132   .9846071    -0.27   0.787     4.83e-08      351892
                       iur2 |   1.09e+14   8.32e+15     0.42   0.673     7.56e-52    1.56e+79
                       iur3 |   3.96e-41   8.42e-39    -0.44   0.661     6.3e-222    2.5e+140
                   initrate |   .0017314    .083949    -0.13   0.896     9.25e-45    3.24e+38
                  initrate2 |   1.1e-221   3.5e-218    -0.16   0.872            0           .
                  initrate3 |          .          .     0.19   0.849            0           .
                  empgrowth |   1.156185   .0878403     1.91   0.056     .9962262    1.341828
                       emp2 |   .9770312   .0225311    -1.01   0.314     .9338542    1.022205
                       emp3 |   1.002295   .0017089     1.34   0.179     .9989514     1.00565
                incrate_jhu |   .9997373   .0001608    -1.63   0.102     .9994221    1.000053
                    stringd |   .9982051   .0043141    -0.42   0.678     .9897853    1.006696
                 1.cutoff3n |    1.09651   .0791278     1.28   0.202     .9518902    1.263101
                      _cons |   .6563045   .3035794    -0.91   0.363     .2650786    1.624935
---------------------------------------------------------------------------------------------
Note: _cons estimates baseline odds.