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



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

. * BEGIN distributed
. newey logacc unem L(1/2).unem trend i.month, lag(4)

Regression with Newey–West standard errors      Number of obs     =        106
Maximum lag = 4                                 F( 15,        90) =      20.39
                                                Prob > F          =     0.0000

------------------------------------------------------------------------------
             |             Newey–West
      logacc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        unem |
         --. |  -.0218345   .0073752    -2.96   0.004    -.0364866   -.0071823
         L1. |  -.0027711   .0075824    -0.37   0.716    -.0178349    .0122927
         L2. |   .0028242   .0079337     0.36   0.723    -.0129375    .0185858
             |
       trend |   .0018359   .0002514     7.30   0.000     .0013365    .0023352
             |
       month |
          2  |  -.0278513   .0173526    -1.61   0.112    -.0623254    .0066228
          3  |   .0858646   .0211742     4.06   0.000     .0437983    .1279309
          4  |   .0161909   .0224788     0.72   0.473    -.0284671     .060849
          5  |    .024709   .0236216     1.05   0.298    -.0222195    .0716375
          6  |   .0199826   .0238524     0.84   0.404    -.0274043    .0673695
          7  |   .0517578   .0243261     2.13   0.036     .0034297    .1000858
          8  |   .0574206   .0247672     2.32   0.023     .0082163     .106625
          9  |   .0372946   .0256213     1.46   0.149    -.0136065    .0881957
         10  |   .0792432   .0234326     3.38   0.001     .0326903    .1257961
         11  |   .0723805   .0203447     3.56   0.001     .0319622    .1127987
         12  |   .0954734    .026761     3.57   0.001     .0423079    .1486388
             |
       _cons |   10.67207   .0367848   290.12   0.000     10.59899    10.74515
------------------------------------------------------------------------------

. * END distributed
. record impact unem

. record lag1 L.unem

. record lag2 L2.unem

. * BEGIN cumulative
. lincom unem+L.unem+L2.unem

 ( 1)  unem + L.unem + L2.unem = 0

------------------------------------------------------------------------------
      logacc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |  -.0217814    .004154    -5.24   0.000    -.0300341   -.0135287
------------------------------------------------------------------------------

. * END cumulative
. * BEGIN persistence
. newey logacc L.logacc trend i.month, lag(4)

Regression with Newey–West standard errors      Number of obs     =        107
Maximum lag = 4                                 F( 13,        93) =      89.01
                                                Prob > F          =     0.0000

------------------------------------------------------------------------------
             |             Newey–West
      logacc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      logacc |
         L1. |   .6783359   .0825587     8.22   0.000     .5143906    .8422811
             |
       trend |   .0009218   .0002548     3.62   0.000     .0004158    .0014278
             |
       month |
          2  |   .0483082   .0297704     1.62   0.108      -.01081    .1074264
          3  |   .1997367   .0275006     7.26   0.000     .1451259    .2543474
          4  |   .0552554   .0260082     2.12   0.036     .0036083    .1069026
          5  |   .1104394   .0284036     3.89   0.000     .0540355    .1668434
          6  |   .0892604   .0262674     3.40   0.001     .0370985    .1414224
          7  |   .1146895   .0273063     4.20   0.000     .0604647    .1689143
          8  |   .1192549   .0261609     4.56   0.000     .0673045    .1712053
          9  |   .0964702   .0260498     3.70   0.000     .0447404       .1482
         10  |   .1440678   .0263677     5.46   0.000     .0917067    .1964288
         11  |   .1062293   .0262052     4.05   0.000     .0541909    .1582677
         12  |   .1384194   .0333721     4.15   0.000     .0721489    .2046899
             |
       _cons |   3.276324   .8753799     3.74   0.000     1.537993    5.014655
------------------------------------------------------------------------------

. * END persistence
. record persistence L.logacc

. 
. postclose results

. use "output/meeting_10_estimates.dta", clear

. export delimited using "output/meeting_10_estimates.csv", replace
(file output/meeting_10_estimates.csv not found)
file output/meeting_10_estimates.csv saved

. display "ECO603_MEETING_10_COMPLETE"
ECO603_MEETING_10_COMPLETE



