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RE: st: Interpretation of margins in the presence of fixed effects


From   Dana Shills <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: Interpretation of margins in the presence of fixed effects
Date   Fri, 6 Sep 2013 09:45:38 -0400

Hi Jed:

I understand the role of the constant but I am trying to figure what exactly the margins command is estimating in the presence of other dummies. So the model without the constant is the first one below. How do these age coefficients compare to the predictive margins in the model below that??

Thanks

Dana


. reg size ages1-ages9 i.inum, noconstant
 
      Source |       SS       df       MS              Number of obs =      97
-------------+------------------------------           F( 39,    58) =    3.34
       Model |  2853694.83    39  73171.6624           Prob> F      =  0.0000
    Residual |  1269729.17    58  21891.8822           R-squared     =  0.6921
-------------+------------------------------           Adj R-squared =  0.4850
       Total |     4123424    97  42509.5258           Root MSE      =  147.96
 
------------------------------------------------------------------------------
        size |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       ages1 |        134   147.9591     0.91   0.369    -162.1722    430.1722
       ages2 |   319.1145   161.2046     1.98   0.053    -3.571458    641.8005
       ages3 |   239.8429   165.3636     1.45   0.152    -91.16828    570.8542
       ages4 |   208.4776   162.3196     1.28   0.204    -116.4403    533.3955
       ages5 |   305.1386    168.829     1.81   0.076    -32.80939    643.0865
       ages6 |   353.9226   171.9741     2.06   0.044     9.679101    698.1661
       ages7 |   157.7671   170.1343     0.93   0.358    -182.7938    498.3279
       ages8 |   611.1547    176.773     3.46   0.001      257.305    965.0044
       ages9 |    729.833   196.4746     3.71   0.000     336.5464     1123.12
             |
        inum |
          2  |  -234.5949   168.2358    -1.39   0.169    -571.3555    102.1657
          3  |  -17.52719   160.0994    -0.11   0.913    -338.0009    302.9465
          4  |  -55.42242   169.1826    -0.33   0.744    -394.0781    283.2333
          5  |  -271.0341   187.8332    -1.44   0.154    -647.0231     104.955
          6  |  -118.9656   166.5016    -0.71   0.478    -452.2547    214.3236
          7  |  -95.84294   221.8941    -0.43   0.667    -540.0123    348.3264
          8  |  -206.4776    219.635    -0.94   0.351    -646.1248    233.1696
          9  |  -234.8429    195.681    -1.20   0.235    -626.5411    156.8552
         10  |   -83.4776    219.635    -0.38   0.705    -523.1248    356.1696
         11  |  -451.0993    188.756    -2.39   0.020    -828.9356   -73.26306
         12  |  -271.1145   218.8122    -1.24   0.220    -709.1148    166.8857
         13  |  -68.56328   168.2744    -0.41   0.685    -405.4011    268.2746
         14  |  -55.88331   171.9721    -0.32   0.746    -400.1229    288.3562
         15  |  -265.9787    191.091    -1.39   0.169     -648.489    116.5315
         16  |  -125.1974   175.2724    -0.71   0.478    -476.0432    225.6484
         17  |  -147.8429   221.8941    -0.67   0.508    -592.0123    296.3264
         18  |  -148.5633   168.2744    -0.88   0.381    -485.4011    188.2746
         19  |  -181.3566   181.0713    -1.00   0.321    -543.8101     181.097
         20  |  -297.1145   218.8122    -1.36   0.180    -735.1148    140.8857
         21  |  -13.84294   221.8941    -0.06   0.950    -458.0123    430.3264
         22  |  -193.3253   167.3785    -1.16   0.253    -528.3697    141.7191
         23  |  -160.5306   193.9322    -0.83   0.411    -548.7281    227.6669
         24  |  -145.7978   165.7959    -0.88   0.383    -477.6744    186.0788
         25  |     -109.5   181.2121    -0.60   0.548    -472.2354    253.2354
         26  |  -290.1386   224.4886    -1.29   0.201    -739.5012    159.2241
         27  |  -183.1603   191.4903    -0.96   0.343    -566.4698    200.1492
         28  |   -77.4776    219.635    -0.35   0.726    -517.1248    362.1696
         29  |  -120.0795   177.5111    -0.68   0.501    -475.4067    235.2476
         30  |  -346.9226   226.8633    -1.53   0.132    -801.0388    107.1937
         31  |  -204.4776    219.635    -0.93   0.356    -644.1248    235.1696
------------------------------------------------------------------------------


>> Case II: WITH INDUSTRY DUMMIES
>>
>> . reg size i.agedum i.inum
>>
>> Source | SS df MS Number of obs = 97
>> -------------+------------------------------ F( 38, 58) = 1.67
>> Model | 1385935.82 38 36471.9953 Prob> F = 0.0390
>> Residual | 1269729.17 58 21891.8822 R-squared = 0.5219
>> -------------+------------------------------ Adj R-squared = 0.2086
>> Total | 2655664.99 96 27663.177 Root MSE = 147.96
>>
>> ------------------------------------------------------------------------------
>> size | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>> agedum |
>> 2 | 185.1145 63.99243 2.89 0.005 57.01978 313.2093
>> 3 | 105.8429 73.84605 1.43 0.157 -41.97599 253.6619
>> 4 | 74.4776 66.75151 1.12 0.269 -59.14007 208.0953
>> 5 | 171.1386 81.31018 2.10 0.040 8.378543 333.8986
>> 6 | 219.9226 87.65383 2.51 0.015 44.46437 395.3808
>> 7 | 23.76708 83.98693 0.28 0.778 -144.351 191.8852
>> 8 | 477.1547 96.73068 4.93 0.000 283.5272 670.7822
>> 9 | 595.833 129.2686 4.61 0.000 337.0737 854.5923
>> |
>> inum |
>> 2 | -234.5949 168.2358 -1.39 0.169 -571.3555 102.1657
>> 3 | -17.52719 160.0994 -0.11 0.913 -338.0009 302.9465
>> 4 | -55.42242 169.1826 -0.33 0.744 -394.0781 283.2333
>> 5 | -271.0341 187.8332 -1.44 0.154 -647.0231 104.955
>> 6 | -118.9656 166.5016 -0.71 0.478 -452.2547 214.3236
>> 7 | -95.84294 221.8941 -0.43 0.667 -540.0123 348.3264
>> 8 | -206.4776 219.635 -0.94 0.351 -646.1248 233.1696
>> 9 | -234.8429 195.681 -1.20 0.235 -626.5411 156.8552
>> 10 | -83.4776 219.635 -0.38 0.705 -523.1248 356.1696
>> 11 | -451.0993 188.756 -2.39 0.020 -828.9356 -73.26306
>> 12 | -271.1145 218.8122 -1.24 0.220 -709.1148 166.8857
>> 13 | -68.56328 168.2744 -0.41 0.685 -405.4011 268.2746
>> 14 | -55.88331 171.9721 -0.32 0.746 -400.1229 288.3562
>> 15 | -265.9787 191.091 -1.39 0.169 -648.489 116.5315
>> 16 | -125.1974 175.2724 -0.71 0.478 -476.0432 225.6484
>> 17 | -147.8429 221.8941 -0.67 0.508 -592.0123 296.3264
>> 18 | -148.5633 168.2744 -0.88 0.381 -485.4011 188.2746
>> 19 | -181.3566 181.0713 -1.00 0.321 -543.8101 181.097
>> 20 | -297.1145 218.8122 -1.36 0.180 -735.1148 140.8857
>> 21 | -13.84294 221.8941 -0.06 0.950 -458.0123 430.3264
>> 22 | -193.3253 167.3785 -1.16 0.253 -528.3697 141.7191
>> 23 | -160.5306 193.9322 -0.83 0.411 -548.7281 227.6669
>> 24 | -145.7978 165.7959 -0.88 0.383 -477.6744 186.0788
>> 25 | -109.5 181.2121 -0.60 0.548 -472.2354 253.2354
>> 26 | -290.1386 224.4886 -1.29 0.201 -739.5012 159.2241
>> 27 | -183.1603 191.4903 -0.96 0.343 -566.4698 200.1492
>> 28 | -77.4776 219.635 -0.35 0.726 -517.1248 362.1696
>> 29 | -120.0795 177.5111 -0.68 0.501 -475.4067 235.2476
>> 30 | -346.9226 226.8633 -1.53 0.132 -801.0388 107.1937
>> 31 | -204.4776 219.635 -0.93 0.356 -644.1248 235.1696
>> |
>> _cons | 134 147.9591 0.91 0.369 -162.1722 430.1722
>> ------------------------------------------------------------------------------
>>
>> . margins agedum
>>
>> Predictive margins Number of obs = 97
>> Model VCE : OLS
>>
>> Expression : Linear prediction, predict()
>>
>> ------------------------------------------------------------------------------
>> | Delta-method
>> | Margin Std. Err. z P>|z| [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>> agedum |
>> 1 | -22.27385 49.35852 -0.45 0.652 -119.0148 74.46706
>> 2 | 162.8407 40.73507 4.00 0.000 83.00143 242.68
>> 3 | 83.56909 47.28917 1.77 0.077 -9.115992 176.2542
>> 4 | 52.20375 41.96549 1.24 0.214 -30.0471 134.4546
>> 5 | 148.8647 66.87327 2.23 0.026 17.7955 279.9339
>> 6 | 197.6487 71.66732 2.76 0.006 57.18337 338.1141
>> 7 | 1.493234 70.09108 0.02 0.983 -135.8828 138.8692
>> 8 | 454.8808 75.76749 6.00 0.000 306.3793 603.3824
>> 9 | 573.5592 111.6518 5.14 0.000 354.7258 792.3926
>> 		 	   		  
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