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  • Results insignificant after using year dummy variables.

    Hi everyone!
    I have a question regarding year dummy variables. I am trying to investigate the impact of Trade liberalisation on female labour force participation rate in 14 developing Asian countries and am therefore running a Fixed Effects regression. The first regression I run is without any year dummy variables and solely includes the Control Variables and the explanatory variable. The code is shown below.
    Code:
    xtreg FLFPR FR FUR GDPpc TO, fe robust
    This gave me the following result where TO is significant at the 5% level.
    Code:
    Fixed-effects (within) regression               Number of obs     =        403
    Group variable: CountryNum                      Number of groups  =         14
    
    R-sq:                                           Obs per group:
         within  = 0.0876                                         min =         26
         between = 0.2218                                         avg =       28.8
         overall = 0.1360                                         max =         29
    
                                                    F(4,13)           =       2.91
    corr(u_i, Xb)  = -0.4371                        Prob > F          =     0.0639
    
                                (Std. Err. adjusted for 14 clusters in CountryNum)
    ------------------------------------------------------------------------------
                 |               Robust
           FLFPR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
              FR |  -.7364388   .7314433    -1.01   0.332    -2.316626    .8437484
             FUR |    .083618   .2047825     0.41   0.690    -.3587877    .5260237
           GDPpc |   .0001044   .0000646     1.62   0.130    -.0000352     .000244
              TO |  -.0282203   .0121169    -2.33   0.037    -.0543972   -.0020434
           _cons |   54.80075   3.269936    16.76   0.000     47.73648    61.86501
    -------------+----------------------------------------------------------------
         sigma_u |  19.497251
         sigma_e |  2.4764401
             rho |  .98412337   (fraction of variance due to u_i)
    ------------------------------------------------------------------------------
    However, when I add a dummy variable for each year (minus 1) that is in my sample, i.e, from 1990 to 2018, the coefficient on TO becomes insignificant.
    Code:
    xtreg FLFPR FR FUR GDPpc TO y1 y2 y3 y4 y5 y6 y7 y8 y9 y10 y11 y12 y13 y14 y15 y16 y17 y18 y19 y20 y21 y22 y23 y24 y25 y26 y27 y28, fe robust
    Code:
    Fixed-effects (within) regression               Number of obs     =        403
    Group variable: CountryNum                      Number of groups  =         14
    
    R-sq:                                           Obs per group:
         within  = 0.1396                                         min =         26
         between = 0.0039                                         avg =       28.8
         overall = 0.0003                                         max =         29
    
                                                    F(13,13)          =          .
    corr(u_i, Xb)  = -0.1276                        Prob > F          =          .
    
                                (Std. Err. adjusted for 14 clusters in CountryNum)
    ------------------------------------------------------------------------------
                 |               Robust
           FLFPR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
              FR |  -1.708764     .96501    -1.77   0.100    -3.793541    .3760136
             FUR |   .0074997   .1827171     0.04   0.968    -.3872366     .402236
           GDPpc |   .0001995   .0000496     4.02   0.001     .0000923    .0003066
              TO |  -.0247951   .0168391    -1.47   0.165    -.0611737    .0115836
              y1 |   3.389236   2.208276     1.53   0.149    -1.381454    8.159926
              y2 |   3.233488   2.046978     1.58   0.138     -1.18874    7.655715
              y3 |   2.842947    1.78705     1.59   0.136    -1.017741    6.703634
              y4 |    2.85432   1.773783     1.61   0.132    -.9777045    6.686345
              y5 |   2.955971   1.664716     1.78   0.099    -.6404285    6.552371
              y6 |     2.5787   1.498052     1.72   0.109    -.6576454    5.815045
              y7 |   2.636164   1.457976     1.81   0.094    -.5136015     5.78593
              y8 |   2.565584   1.569233     1.63   0.126    -.8245376    5.955705
              y9 |   3.053849   1.642985     1.86   0.086    -.4956048    6.603303
             y10 |   2.601952   1.472541     1.77   0.101    -.5792797    5.783184
             y11 |    2.50133   1.517437     1.65   0.123    -.7768944    5.779554
             y12 |   2.761161   1.551812     1.78   0.099    -.5913241    6.113647
             y13 |   2.263491   1.601462     1.41   0.181    -1.196258    5.723241
             y14 |   2.026965   1.640635     1.24   0.239    -1.517411    5.571341
             y15 |   1.769197   1.743178     1.01   0.329     -1.99671    5.535105
             y16 |   1.714858    1.81088     0.95   0.361     -2.19731    5.627027
             y17 |    1.45597   1.706395     0.85   0.409    -2.230472    5.142411
             y18 |   1.589595   1.560558     1.02   0.327    -1.781786    4.960976
             y19 |   1.325755   1.502858     0.88   0.394    -1.920973    4.572483
             y20 |   1.340527   1.423183     0.94   0.363    -1.734073    4.415128
             y21 |   1.286046    1.29986     0.99   0.341    -1.522132    4.094223
             y22 |   1.401393   1.278901     1.10   0.293    -1.361506    4.164291
             y23 |   .9731538   1.114448     0.87   0.398    -1.434464    3.380772
             y24 |   .4656153   .7664366     0.61   0.554     -1.19017    2.121401
             y25 |   .2296892   .6472401     0.35   0.728    -1.168588    1.627966
             y26 |   .3651207   .6224359     0.59   0.568    -.9795703    1.709812
             y27 |   .2646698   .4753703     0.56   0.587    -.7623053    1.291645
             y28 |   .3260597   .3253869     1.00   0.335     -.376896    1.029015
           _cons |   55.61924   3.822775    14.55   0.000     47.36063    63.87784
    -------------+----------------------------------------------------------------
         sigma_u |  19.066549
         sigma_e |  2.4973914
             rho |  .98313287   (fraction of variance due to u_i)
    ------------------------------------------------------------------------------
    This is also the case for some other variables that I am using as explanatory variables in separate regressions for the same research.
    Does anyone have any insight on why this might be the outcome and what it implies in terms of the yearly trends and the relationship between the explanatory and outcome variables?

    Additionally I also wanted to confirm whether it is necessary/helpful to add year dummy variables when one is using a Fixed Effects model?

    Thank you!

  • #2
    Using FE for time, units, and both at once changes the estimand you're estimating. I direct everyone to this paper on the matter which hasn't really caused econ instructors to change their thinking much, but here it is. The short answer is "no, don't use both".

    I wouldn't hunt statistical significance with a shotgun, thus spoke the Book of Kennedy, verse 7. In my opinion, statistical significance is stupid and is easily influenced by this like sample size, estimator and various other aspects of your data. You have a very small sample size, so it isn't surprising that your results are quite sensitive to small changes in your model.

    In short, if I were you, I'd focus on the substantive meaning of my results. Abandon statistical significance, and consider the implications of adding unit or time dummies in your model.




    Oh, and don't add in 30 year variables, just use i.year, Stata's time series notation.

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