I am running a Fixed Effects regression to test the effect of a policy on firms' patent application. The outcome variable is number of patents.
I first run the simple model with FEs but without any controls:
Code:
Conditional fixed-effects Poisson regression Number of obs = 47,536
Group variable: firm_id Number of groups = 7,670
Obs per group:
min = 2
avg = 6.2
max = 9
Wald chi2(9) = 469.47
Log pseudolikelihood = -36500.224 Prob > chi2 = 0.0000
(Std. Err. adjusted for clustering on firm_id)
----------------------------------------------------------------------------------
| Robust
application_num | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
treated | -.0541731 .2172701 -0.25 0.803 -.4800147 .3716685
|
application_year |
1999 | .5463735 .1321019 4.14 0.000 .2874586 .8052884
2000 | 1.042662 .2174868 4.79 0.000 .6163956 1.468928
2001 | 1.35629 .3345565 4.05 0.000 .7005712 2.012008
2002 | 2.180516 .3422223 6.37 0.000 1.509772 2.851259
2003 | 2.626014 .3407459 7.71 0.000 1.958164 3.293864
2004 | 2.883888 .3663026 7.87 0.000 2.165948 3.601827
2005 | 3.217897 .3785679 8.50 0.000 2.475918 3.959877
2006 | 3.594803 .4207512 8.54 0.000 2.770146 4.41946
----------------------------------------------------------------------------------
I then add controls:
Code:
Conditional fixed-effects Poisson regression Number of obs = 45,948
Group variable: firm_id Number of groups = 7,583
Obs per group:
min = 2
avg = 6.1
max = 9
Wald chi2(13) = 1555.79
Log pseudolikelihood = -22604.768 Prob > chi2 = 0.0000
(Std. Err. adjusted for clustering on firm_id)
----------------------------------------------------------------------------------
| Robust
application_num | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
treated | .1731523 .0770954 2.25 0.025 .0220481 .3242564
total_assets_log | .324462 .0806509 4.02 0.000 .1663891 .4825349
total_profit_log | -.6414265 .1401608 -4.58 0.000 -.9161365 -.3667165
cum_claims_log | 1.192533 .0713113 16.72 0.000 1.052765 1.3323
age_log | -.1982098 .1659591 -1.19 0.232 -.5234837 .1270642
|
application_year |
1999 | .2394592 .0855993 2.80 0.005 .0716876 .4072308
2000 | .2442759 .0859471 2.84 0.004 .0758226 .4127292
2001 | .1151367 .1044195 1.10 0.270 -.0895217 .3197951
2002 | .1297499 .1482964 0.87 0.382 -.1609057 .4204054
2003 | .0002627 .1531101 0.00 0.999 -.2998277 .300353
2004 | -.2282316 .1756614 -1.30 0.194 -.5725216 .1160585
2005 | -.4450677 .2097618 -2.12 0.034 -.8561931 -.0339422
2006 | -.7040352 .2517939 -2.80 0.005 -1.197542 -.2105283
----------------------------------------------------------------------------------
Can anyone help me understand why this is the case? I know that often time adding controls turns a significant variable insignificant as the controls can absorb some explanation power. But I just can't figure out why in my case, a insignificant variable becomes significant once controls are added.
And which result shall I trust? Does the policy really have a significant impact on firms' patent application?
Thank you very much!
0 Response to Adding controls, insignificant treatment var turns significant
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