面板数据估计控制年度和行业效应后不显著了是怎么回事 - Stata专版

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张无悔 发表于 2017-3-30 21:58:23 |只看作者 |坛友微信交流群|倒序 |AI写论文

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xtreg NCSit1 PLSit TTHit SIZEit TURit ROAit LEVit,fe r

Fixed-effects (within) regression             Number of obs    =    5735
Group variable: scode                         Number of groups =    2295

R-sq:  within  = 0.0090                      Obs per group: min =       1
   between = 0.0051                                     avg =    2.5
   overall = 0.0052                                     max =       7

                                             F(6,2294)       =    6.92
corr(u_i, Xb)  = -0.1275                      Prob > F          = 0.0000

                           (Std. Err. adjusted for 2295 clusters in scode)
------------------------------------------------------------------------------
         |             Robust
   NCSit1 |    Coef. Std. Err.    t P>|t|    [95% Conf. Interval]
-------------+----------------------------------------------------------------
   PLSit | .1286685 .0739497    1.74 0.082 -.0163467 .2736836
   TTHit |  -.0425337 .3374368 -0.13 0.900 -.7042467 .6191794
   SIZEit | .0917929 .0375607    2.44 0.015    .0181365 .1654494
   TURit | .088303 .0270974    3.26 0.001    .035165    .141441
   ROAit | .0286035 .0191251    1.50 0.135 -.0089008 .0661079
   LEVit | .0099275 .0026067    3.81 0.000    .0048158 .0150392
   _cons |  -2.232123 .8492968 -2.63 0.009 -3.897593 -.5666535
-------------+----------------------------------------------------------------
   sigma_u | .6522691
   sigma_e |  .87223187
      rho |  .35865739 (fraction of variance due to u_i)
------------------------------------------------------------------------------
这是没有控制年度和行业效应的结果。
. xtreg NCSit1 PLSit TTHit SIZEit TURit ROAit LEVit i.YEAR i.INDit ,fe r
note: 8.INDit omitted because of collinearity

Fixed-effects (within) regression             Number of obs    =    5735
Group variable: scode                         Number of groups =    2295

R-sq:  within  = 0.0538                      Obs per group: min =       1
   between = 0.0046                                     avg =    2.5
   overall = 0.0178                                     max =       7

                                             F(26,2294)       =       .
corr(u_i, Xb)  = -0.2788                      Prob > F          =       .

                           (Std. Err. adjusted for 2295 clusters in scode)
------------------------------------------------------------------------------
         |             Robust
   NCSit1 |    Coef. Std. Err.    t P>|t|    [95% Conf. Interval]
-------------+----------------------------------------------------------------
   PLSit |  -.0224927 .0758434 -0.30 0.767 -.1712215    .126236
   TTHit | .0439542 .3300332    0.13 0.894 -.6032405 .6911488
   SIZEit | .0799695 .0526968    1.52 0.129 -.0233689 .1833079
   TURit | .0105346 .0333708    0.32 0.752 -.0549056 .0759747
   ROAit | .0255821 .0168688    1.52 0.130 -.0074975 .0586618
   LEVit | .0128119 .0027959    4.58 0.000    .0073292 .0182946
         |
      YEAR |
   2009  | .4879119 .0482504 10.11 0.000    .393293 .5825309
   2010  | .3777443 .0513722    7.35 0.000    .2770034 .4784851
   2011  | .3257017 .0600346    5.43 0.000    .2079739 .4434296
   2012  | .480857 .0636767    7.55 0.000    .3559871 .6057269
   2013  | .2791681 .0775066    3.60 0.000    .1271777 .4311585
   2014  | .2678742 .0794785    3.37 0.001    .1120169 .4237315
         |
   INDit |
      2  |  -.0969802 .4569171 -0.21 0.832 -.9929941 .7990337
      3  |  -.3944993 .344898 -1.14 0.253 -1.070844 .2818451
      4  |  -.6434356 .4621729 -1.39 0.164 -1.549756 .2628849
      5  | .5139097 .4668446    1.10 0.271 -.4015719 1.429391
      6  |  -.4292383 .3731628 -1.15 0.250    -1.16101 .3025334
      7  | -.606547 .5549025 -1.09 0.274    -1.69471    .481616
      8  |       0  (omitted)
      9  |  -.5772952 .4198589 -1.37 0.169 -1.400638 .2460474
      10  |  -.6840716 .3833787 -1.78 0.075 -1.435877 .0677334
      11  | -.485339 .4471142 -1.09 0.278 -1.362129 .3914513
      12  |  -.3703138 .541834 -0.68 0.494 -1.432849 .6922219
      13  |  -.2720779 .5569235 -0.49 0.625 -1.364204 .8200483
      14  |  -1.614362 .4482173 -3.60 0.000 -2.493316 -.7354086
      15  |  -1.653838 .5446412 -3.04 0.002 -2.721879 -.5857973
      16  | -.563026 .4527019 -1.24 0.214 -1.450774 .3247219
      17  |  -.4427312 .3900296 -1.14 0.256 -1.207579 .3221164
         |
   _cons |  -1.906265 1.182558 -1.61 0.107    -4.22526 .4127301
-------------+----------------------------------------------------------------
   sigma_u |  .67858042
   sigma_e |  .85491726
      rho |  .38651067 (fraction of variance due to u_i)
控制后就不显著了，这是怎么回事啊，求大神指教。