Actual StataMP numerical output. Log header and machine paths omitted.

. * BEGIN calendar
. regress logacc trend i.month

      Source |       SS           df       MS      Number of obs   =       108
-------------+----------------------------------   F(12, 95)       =     31.06
       Model |  1.00244066        12  .083536722   Prob > F        =    0.0000
    Residual |  .255496381        95  .002689436   R-squared       =    0.7969
-------------+----------------------------------   Adj R-squared   =    0.7712
       Total |  1.25793704       107  .011756421   Root MSE        =    .05186

------------------------------------------------------------------------------
      logacc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       trend |   .0027471   .0001611    17.06   0.000     .0024274    .0030669
             |
       month |
          2  |  -.0426864   .0244475    -1.75   0.084    -.0912208    .0058479
          3  |   .0798245   .0244491     3.26   0.002      .031287     .128362
          4  |    .018485   .0244517     0.76   0.452    -.0300578    .0670277
          5  |   .0320983   .0244554     1.31   0.193    -.0164518    .0806484
          6  |   .0201919   .0244602     0.83   0.411    -.0283677    .0687515
          7  |   .0375825    .024466     1.54   0.128    -.0109887    .0861537
          8  |   .0539828   .0244729     2.21   0.030     .0053979    .1025677
          9  |   .0423611   .0244809     1.73   0.087    -.0062395    .0909618
         10  |   .0821134   .0244899     3.35   0.001     .0334949    .1307319
         11  |   .0712786   .0244999     2.91   0.005     .0226401    .1199171
         12  |   .0961571    .024511     3.92   0.000     .0474965    .1448177
             |
       _cons |   10.46857   .0190028   550.90   0.000     10.43084    10.50629
------------------------------------------------------------------------------

. * END calendar
. record calendar trend

. * BEGIN adjusted
. regress logacc trend i.month unem spdlaw beltlaw wkends, vce(robust)

Linear regression                               Number of obs     =        108
                                                F(16, 91)         =      51.37
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9101
                                                Root MSE          =     .03524

------------------------------------------------------------------------------
             |               Robust
      logacc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       trend |   .0011011   .0002676     4.12   0.000     .0005696    .0016326
             |
       month |
          2  |  -.0338346    .021402    -1.58   0.117    -.0763471    .0086779
          3  |    .076953   .0215727     3.57   0.001     .0341013    .1198046
          4  |   .0104562   .0189763     0.55   0.583    -.0272378    .0481503
          5  |   .0237075    .018758     1.26   0.210    -.0135529    .0609679
          6  |   .0219334   .0200891     1.09   0.278    -.0179711    .0618379
          7  |   .0499292   .0198585     2.51   0.014     .0104827    .0893756
          8  |   .0559523   .0193811     2.89   0.005     .0174541    .0944505
          9  |   .0420694   .0186208     2.26   0.026     .0050814    .0790574
         10  |    .081717   .0211651     3.86   0.000     .0396752    .1237588
         11  |   .0768721   .0199737     3.85   0.000     .0371969    .1165474
         12  |   .0990862    .021658     4.58   0.000     .0560653    .1421072
             |
        unem |  -.0212173   .0038238    -5.55   0.000    -.0288128   -.0136218
      spdlaw |  -.0537593   .0120059    -4.48   0.000    -.0776076    -.029911
     beltlaw |   .0954526   .0123682     7.72   0.000     .0708847    .1200206
      wkends |   .0033333   .0039443     0.85   0.400    -.0045016    .0111682
       _cons |   10.63986   .0681238   156.18   0.000     10.50454    10.77518
------------------------------------------------------------------------------

. * END adjusted
. record law beltlaw

. record unemployment unem

. * BEGIN season
. testparm i.month

 ( 1)  2.month = 0
 ( 2)  3.month = 0
 ( 3)  4.month = 0
 ( 4)  5.month = 0
 ( 5)  6.month = 0
 ( 6)  7.month = 0
 ( 7)  8.month = 0
 ( 8)  9.month = 0
 ( 9)  10.month = 0
 (10)  11.month = 0
 (11)  12.month = 0

       F( 11,    91) =   10.29
            Prob > F =    0.0000

. * END season
. format month_id %9.0g

. export delimited month_id year month totacc logacc trend unem spdlaw beltlaw wkends using "output/
> meeting_09_data.csv", replace
(file output/meeting_09_data.csv not found)
file output/meeting_09_data.csv saved

. 
. postclose results

. use "output/meeting_09_estimates.dta", clear

. export delimited using "output/meeting_09_estimates.csv", replace
(file output/meeting_09_estimates.csv not found)
file output/meeting_09_estimates.csv saved

. display "ECO603_MEETING_09_COMPLETE"
ECO603_MEETING_09_COMPLETE



