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?

Code:
                      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