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  • Autocorrelation is a minor concern

    I have a panel data of 27 countries from 1995-2016 (unbalanced panel). I am confused how to interpret whether autocorrelation is a minor concern or not and whether to use the command robust. Can you please help me interpret my results? Is correlation a concern and I need to use -robust-?

    I use the command -regress-
    Regression without -robust-:

    Code:
          Source |       SS       df       MS              Number of obs =     299
    -------------+------------------------------           F( 18,   280) =   19.12
           Model |   14.153387    18  .786299278           Prob > F      =  0.0000
        Residual |  11.5164346   280  .041130124           R-squared     =  0.5514
    -------------+------------------------------           Adj R-squared =  0.5225
           Total |  25.6698216   298  .086140341           Root MSE      =  .20281
    
    -----------------------------------------------------------------------------------
              lnPATR1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    ------------------+----------------------------------------------------------------
          preelection |   -.034093   .0394657    -0.86   0.388    -.1117801    .0435942
          lninflation |  -.0082857   .0260905    -0.32   0.751    -.0596442    .0430727
                lngdp |  -.0214539   .0155474    -1.38   0.169    -.0520585    .0091507
       lnurbanisation |   .5635988   .1471487     3.83   0.000     .2739406    .8532571
                 left |   .1474364   .0380318     3.88   0.000     .0725718     .222301
                right |   .1450968   .0386415     3.75   0.000      .069032    .2211616
         lndependency |   2.259958   4.325274     0.52   0.602    -6.254226    10.77414
      lndependencyold |    -4.3537   12.34348    -0.35   0.725    -28.65151    19.94411
    lndependencyyoung |  -2.010141   .9168129    -2.19   0.029    -3.814862   -.2054197
         lnpopbelow14 |          0  (omitted)
            lnpop1564 |          0  (omitted)
      lnpop65andabove |    3.49226   12.26131     0.28   0.776     -20.6438    27.62832
             eurozone |  -.0949131   .0304085    -3.12   0.002    -.1547713   -.0350549
                   eu |  -.2019194   .0575086    -3.51   0.001    -.3151235   -.0887153
            lngovtexp |  -.6823006   .1670674    -4.08   0.000    -1.011168    -.353433
               lnwage |   .0640134   .0635835     1.01   0.315    -.0611489    .1891758
            plurality |  -.1916017   .0437287    -4.38   0.000    -.2776804    -.105523
         proportional |  -.3352688   .0839047    -4.00   0.000    -.5004329   -.1701047
                lnpit |   .2566626   .0407955     6.29   0.000     .1763578    .3369675
          lncorporate |   .2705219   .0618869     4.37   0.000     .1486993    .3923445
                _cons |    4.06789   10.44516     0.39   0.697    -16.49312     24.6289
    -----------------------------------------------------------------------------------

    Wooldridge Serial Correlation test gives:

    Code:
    Wooldridge test for autocorrelation in panel data
    H0: no first-order autocorrelation
        F(  1,      18) =     12.043
               Prob > F =      0.0027
    Results with -robust- :

    Code:
    Linear regression                                      Number of obs =     299
                                                           F( 18,   280) =   39.24
                                                           Prob > F      =  0.0000
                                                           R-squared     =  0.5514
                                                           Root MSE      =  .20281
    
    -----------------------------------------------------------------------------------
                      |               Robust
              lnPATR1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    ------------------+----------------------------------------------------------------
          preelection |   -.034093   .0403675    -0.84   0.399    -.1135553    .0453693
          lninflation |  -.0082857   .0280417    -0.30   0.768     -.063485    .0469135
                lngdp |  -.0214539   .0127689    -1.68   0.094     -.046589    .0036813
       lnurbanisation |   .5635988   .1326198     4.25   0.000     .3025404    .8246572
                 left |   .1474364   .0290717     5.07   0.000     .0902096    .2046633
                right |   .1450968   .0329821     4.40   0.000     .0801725    .2100211
         lndependency |   2.259958   3.854314     0.59   0.558    -5.327153    9.847069
      lndependencyold |    -4.3537   10.82639    -0.40   0.688    -25.66514    16.95774
    lndependencyyoung |  -2.010141   .8918769    -2.25   0.025    -3.765776   -.2545055
         lnpopbelow14 |          0  (omitted)
            lnpop1564 |          0  (omitted)
      lnpop65andabove |    3.49226   10.73778     0.33   0.745    -17.64477    24.62929
             eurozone |  -.0949131   .0345734    -2.75   0.006    -.1629698   -.0268564
                   eu |  -.2019194   .0646812    -3.12   0.002    -.3292426   -.0745963
            lngovtexp |  -.6823006   .1725209    -3.95   0.000    -1.021903   -.3426978
               lnwage |   .0640134   .0667391     0.96   0.338    -.0673606    .1953875
            plurality |  -.1916017   .0433451    -4.42   0.000    -.2769254   -.1062781
         proportional |  -.3352688   .0718241    -4.67   0.000    -.4766526    -.193885
                lnpit |   .2566626   .0354634     7.24   0.000      .186854    .3264712
          lncorporate |   .2705219   .0661607     4.09   0.000     .1402863    .4007575
                _cons |    4.06789   9.097983     0.45   0.655    -13.84124    21.97702
    -----------------------------------------------------------------------------------
    Last edited by Drishta Tengur; 17 Apr 2017, 16:05.

  • #2
    Drishta:
    I would consider -xtreg- with clustered standard errors.
    Kind regards,
    Carlo
    (Stata 18.0 SE)

    Comment


    • #3
      You might also consider xtregar.

      Comment

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