. regress socialsecurity ageeea ageeea2 eea ageeeaeea ageeea2eea if eeadonutregression==1 [pweight=wtcrnh], cluster(hhid)
(sum of wgt is 58,510,996)

Linear regression Number of obs = 16,530
F(5, 7181) = 789.80
Prob > F = 0.0000
R-squared = 0.2189
Root MSE = .42552

(Std. Err. adjusted for 7,182 clusters in hhid)
------------------------------------------------------------------------------
| Robust
soc ialsecu~y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ageeea | -.0000625 .0001282 -0.49 0.626 -.0003137 .0001887
ageeea2 | -2.37e-07 1.50e-07 -1.58 0.114 -5.31e-07 5.72e-08
eea | .3296937 .04218 7.82 0.000 .2470085 .4123789
ageeeaeea | .0003761 .000228 1.65 0.099 -.000071 .0008231
ageeea2eea | 6.58e-08 2.56e-07 0.26 0.797 -4.36e-07 5.67e-07
_cons | .1654308 .0237605 6.96 0.000 .1188532 .2120083
------------------------------------------------------------------------------

. regress socialsecurity ageeea ageeea2 ageeea3 eea ageeeaeea ageeea2eea ageeea3eea if eeadonutregression==1 [pweight=wtcrnh], cluster(hhid)
(sum of wgt is 58,510,996)

Linear regression Number of obs = 16,530
F(5, 7181) = .
Prob > F = .
R-squared = 0.2191
Root MSE = .4255

(Std. Err. adjusted for 7,182 clusters in hhid)
------------------------------------------------------------------------------
| Robust
socialsecu~y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ageeea | .0001067 .0004339 0.25 0.806 -.0007439 .0009573
ageeea2 | 2.37e-07 1.14e-06 0.21 0.836 -2.00e-06 2.47e-06
ageeea3 | 3.86e-10 9.02e-10 0.43 0.668 -1.38e-09 2.16e-09
eea | .3885139 .0800113 4.86 0.000 .2316683 .5453596
ageeeaeea | -.0005564 .0007659 -0.73 0.468 -.0020578 .000945
ageeea2eea | 1.71e-06 1.98e-06 0.86 0.389 -2.18e-06 5.59e-06
ageeea3eea | -2.10e-09 1.59e-09 -1.32 0.186 -5.21e-09 1.02e-09
_cons | .1819229 .0476432 3.82 0.000 .0885282 .2753177
------------------------------------------------------------------------------



Can I ask a question? I am using regression discontinuity designs and ran some regressions. As you can see, I used the same sample and same weights. In the first equation, the linear and squared terms of the running variable are included in the regression and F-statistic of the regression is reported. However, in the second equation, the cubic term in addition to the linear and squared terms of the running variable is included in the regression and F-statistic of the regression is missing.

1. Could you please let me know the reason?

2. Can I use the estimates of the coefficients and standard errors without any problems?