[Jan Geurst]

reghdfe bda announcement_eligible l_lnassets l_roa, absorb(indus incorp) vce(cluster c)
(converged in 9 iterations)

HDFE Linear regression                            Number of obs   =      3,944
Absorbing 2 HDFE groups                           F(   3,    492) =       5.04
Statistics robust to heteroskedasticity           Prob > F        =     0.0019
                                                  R-squared       =     0.4422
                                                  Adj R-squared   =     0.4317
                                                  Within R-sq.    =     0.2642
Number of clusters (c)       =        493         Root MSE        =     0.3304

                                             (Std. Err. adjusted for 493 clusters in c)
---------------------------------------------------------------------------------------
                      |               Robust
                  bda |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
announcement_eligible |   .0797131   .0234105     3.41   0.001     .0337163      .12571
           l_lnassets |  -.0348046   .0159292    -2.18   0.029    -.0661023   -.0035069
                l_roa |  -3.438988   1.468924    -2.34   0.020    -6.325126   -.5528497
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------------------------+
          Absorbed FE |  Num. Coefs.  =   Categories  -   Redundant     |
----------------------+-------------------------------------------------|
                indus |           56              56              0     |
               incorp |           15              16              1     |
------------------------------------------------------------------------+

reghdfe bda announcement_eligible l_lnassets l_roa, absorb(c indus incorp) vce(cluster c)
(converged in 3 iterations)

HDFE Linear regression                            Number of obs   =      3,944
Absorbing 3 HDFE groups                           F(   3,    492) =       0.93
Statistics robust to heteroskedasticity           Prob > F        =     0.4281
                                                  R-squared       =     0.8968
                                                  Adj R-squared   =     0.8796
                                                  Within R-sq.    =     0.0389
Number of clusters (c)       =        493         Root MSE        =     0.1521

                                             (Std. Err. adjusted for 493 clusters in c)
---------------------------------------------------------------------------------------
                      |               Robust
                  bda |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
announcement_eligible |    .004275   .0071644     0.60   0.551    -.0098017    .0183516
           l_lnassets |  -.0143254   .0292794    -0.49   0.625    -.0718535    .0432027
                l_roa |  -.8736434   .5363002    -1.63   0.104    -1.927365    .1800779
---------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------------------------+
          Absorbed FE |  Num. Coefs.  =   Categories  -   Redundant     |
----------------------+-------------------------------------------------|
                    c |            0             493            493 *   |
                indus |           55              56              1     |
               incorp |           15              16              1     |
------------------------------------------------------------------------+
* = fixed effect nested within cluster; treated as redundant for DoF computation

.

Even I omit announcement, I am coping with the same problem. What do you think is the cause of the high r-squared and the non-significant results if I include firm specific fixed effects(c)?

[Carlo Lazzaro]

Jan:
thanks for using CODE delimiters.
The usual reason for high R-sq and non-significant coefficients is quasi-extreme multicollinearity, which sounds like a warning about your model specification.