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  • #1

    PPML with country fixed effect and year fixed effect

    Hello! I'm a Master's Candidate in Economics major, University of Indonesia

    I'm doing a research on the impact of Indonesian Nickel Ore Export Ban towards the export value of its Indonesian derivative products to the destination countries
    My theses's reviewer ask me to include country fixed effect and time fixed effect
    Time fixed effect result doesn't have any problem but I got a problem with regressing the country fixed effect

    I tried to use this following command:
    Code:
    ppmlhdfe EXPjtUSD EXBanIDNt ln_GDPIDNtUSD ln_GDPjtUSD ExchRateIDRjt ln_Distancej ln_NickelPricet Pandemic i.country
    EXBanIDNt and Pandemic are both dummy variables

    and this is the result I got
    ppmlhdfe EXPjtUSD EXBanIDNt ln_GDPIDNtUSD ln_GDPjtUSD ExchRateIDRjt ln_Distancej ln_NickelPricet Pandemic
    > i.country
    warning: dependent variable takes very low values after standardizing (3.5570e-09)
    Iteration 1: deviance = 2.6838e+11 eps = . iters = 1 tol = 1.0e-04 min(eta) = -5.78 P
    Iteration 2: deviance = 1.6289e+11 eps = 6.48e-01 iters = 1 tol = 1.0e-04 min(eta) = -10.42
    Iteration 3: deviance = 1.3927e+11 eps = 1.70e-01 iters = 1 tol = 1.0e-04 min(eta) = -21.56
    Iteration 4: deviance = 1.3485e+11 eps = 3.28e-02 iters = 1 tol = 1.0e-04 min(eta) = -32.11
    Iteration 5: deviance = 1.3423e+11 eps = 4.62e-03 iters = 1 tol = 1.0e-04 min(eta) = -37.19
    Iteration 6: deviance = 1.3413e+11 eps = 7.48e-04 iters = 1 tol = 1.0e-04 min(eta) = -38.71
    Iteration 7: deviance = 1.3410e+11 eps = 2.05e-04 iters = 1 tol = 1.0e-04 min(eta) = -39.70
    Iteration 8: deviance = 1.3410e+11 eps = 5.89e-05 iters = 1 tol = 1.0e-04 min(eta) = -40.65
    Iteration 9: deviance = 1.3409e+11 eps = 1.67e-05 iters = 1 tol = 1.0e-05 min(eta) = -41.51
    Iteration 10: deviance = 1.3409e+11 eps = 4.37e-06 iters = 1 tol = 1.0e-05 min(eta) = -42.19 S
    Iteration 11: deviance = 1.3409e+11 eps = 9.08e-07 iters = 1 tol = 1.0e-06 min(eta) = -42.56 S
    Iteration 12: deviance = 1.3409e+11 eps = 1.71e-07 iters = 1 tol = 1.0e-07 min(eta) = -42.65 S
    Iteration 13: deviance = 1.3409e+11 eps = 4.09e-08 iters = 1 tol = 1.0e-07 min(eta) = -42.66 S
    Iteration 14: deviance = 1.3409e+11 eps = 8.69e-09 iters = 1 tol = 1.0e-09 min(eta) = -42.66 S O

    (legend: p: exact partial-out s: exact solver h: step-halving o: epsilon below tolerance)
    Converged in 14 iterations and 14 HDFE sub-iterations (tol = 1.0e-08)
    warning: variance matrix is nonsymmetric or highly singular.

    PPML regression No. of obs = 2,080
    Residual df = 1,989
    Wald chi2(90) = 16738.13
    Deviance = 1.34094e+11 Prob > chi2 = 0.0000
    Log pseudolikelihood = -6.70470e+10 Pseudo R2 = 0.6446

    Robust
    EXPjtUSD Coefficient std. err. z P>z [95% conf. interval]

    EXBanIDNt -.2610554 . . . . .
    ln_GDPIDNtUSD -.5106122 . . . . .
    ln_GDPjtUSD 7.870495 . . . . .
    ExchRateIDRjt -.0002984 . . . . .
    ln_Distancej 5.267245 . . . . .
    ln_NickelPricet .3215061 . . . . .
    Pandemic .5252581 . . . . .

    country
    Aljazair -.1115996 . . . . .
    Amerika Serikat -29.89006 . . . . .
    Angola 2.995534 . . . . .
    Australia -8.749 . . . . .
    Austria -5.866425 . . . . .
    Bangladesh 6.584127 . . . . .
    Belanda -1.994256 . . . . .
    Belarus 17.25977 . . . . .
    Belgia .4469065 . . . . .
    Brazil -14.00681 . . . . .
    Brunei 29.71463 . . . . .
    Brunei 30.23168 . . . . .
    Bulgaria 14.97437 . . . . .
    Burma 13.98672 . . . . .
    Chili -5.974868 . . . . .
    China -19.6525 . . . . .
    Denmark -9.257653 . . . . .
    Ekuador 8.721974 . . . . .
    Estonia 20.91524 . . . . .
    Fiji 28.2642 . . . . .
    Finlandia -2.229176 . . . . .
    Ghana 3.015398 . . . . .
    Guinea 19.20981 . . . . .
    Hungaria -3.5081 . . . . .
    India -8.867043 . . . . .
    Inggris -14.51688 . . . . .
    Irak -.0102482 . . . . .
    Iran -5.160684 . . . . .
    Israel -.9351605 . . . . .
    Italia -7.245999 . . . . .
    Jepang -13.23711 . . . . .
    Jerman -17.22056 . . . . .
    Kamboja -4.73666 . . . . .
    Kanada -15.18242 . . . . .
    Kazakhstan -4.834557 . . . . .
    Kenya 10.52815 . . . . .
    Kep. Salomon 37.81915 . . . . .
    Kolumbia -4.909772 . . . . .
    Korea Selatan -5.509322 . . . . .
    Kuwait 17.84832 . . . . .
    Laos 19.36132 . . . . .
    Latvia 17.71634 . . . . .
    Lebanon 12.09906 . . . . .
    Lithuania 17.18603 . . . . .
    Malaysia 14.84972 . . . . .
    Malta 23.87813 . . . . .
    Maroko 2.483316 . . . . .
    Meksiko -14.13872 . . . . .
    Mesir -2.121025 . . . . .
    Nigeria -7.892472 . . . . .
    Norwegia -5.088919 . . . . .
    Oman 14.31529 . . . . .
    Pakistan 1.157468 . . . . .
    Panama 13.59495 . . . . .
    Papua Nugini 19.61104 . . . . .
    Paraguay 10.76716 . . . . .
    Perancis -16.15502 . . . . .
    Peru .404898 . . . . .
    Pilipina 3.899565 . . . . .
    Polandia -3.105256 . . . . .
    Portugal 2.994682 . . . . .
    Prancis -19.58036 . . . . .
    Qatar 3.246556 . . . . .
    Romania -.1952607 . . . . .
    Rusia -10.69308 . . . . .
    Saudi Arabia -5.312447 . . . . .
    Selandia Baru 3.406831 . . . . .
    Singapura 15.33509 . . . . .
    Slovenia 15.47403 . . . . .
    Spanyol -7.274483 . . . . .
    Sri Langka 13.76771 . . . . .
    Sudan 2.958472 . . . . .
    Swedia -8.595944 . . . . .
    Swiss -7.290057 . . . . .
    Taiwan 4.30245 . . . . .
    Thailand 7.414813 . . . . .
    Togo 18.82108 . . . . .
    Tunisia 13.1104 . . . . .
    Turki -4.954901 . . . . .
    Ukraina 7.698375 . . . . .
    Uni Emirate Arab .4707735 . . . . .
    Vietnam 10.43486 . . . . .
    Yunani 6.312664 . . . . .

    _cons -232.1298 . . . . .

    I don't know why the results of the probability and other terms not showing any number, only "."
    Some explanations would help me a lot

    Best Regards
    Tasyadhila
    Tags: None
  • #2
    [UPDATE]

    I drop the Distance variable and the result got better, the probability and other terms are showing number

    Code:
    . ppmlhdfe EXPjtUS EXBanINDt GDPINDtUS GDPjtUS ExchjtjIDR NickelGlobalPricemt Pandemic i.negara
warning: dependent variable takes very low values after standardizing (3.5570e-09)
Iteration 1:   deviance = 2.5054e+11  eps = .         iters = 1    tol = 1.0e-04  min(eta) =  -4.76  P   
Iteration 2:   deviance = 1.5743e+11  eps = 5.91e-01  iters = 1    tol = 1.0e-04  min(eta) =  -6.41      
Iteration 3:   deviance = 1.4137e+11  eps = 1.14e-01  iters = 1    tol = 1.0e-04  min(eta) =  -8.58      
Iteration 4:   deviance = 1.3974e+11  eps = 1.16e-02  iters = 1    tol = 1.0e-04  min(eta) = -10.77      
Iteration 5:   deviance = 1.3949e+11  eps = 1.82e-03  iters = 1    tol = 1.0e-04  min(eta) = -12.27      
Iteration 6:   deviance = 1.3942e+11  eps = 4.91e-04  iters = 1    tol = 1.0e-04  min(eta) = -13.26      
Iteration 7:   deviance = 1.3940e+11  eps = 1.34e-04  iters = 1    tol = 1.0e-04  min(eta) = -14.06      
Iteration 8:   deviance = 1.3940e+11  eps = 3.60e-05  iters = 1    tol = 1.0e-04  min(eta) = -14.62      
Iteration 9:   deviance = 1.3939e+11  eps = 9.27e-06  iters = 1    tol = 1.0e-05  min(eta) = -14.84      
Iteration 10:  deviance = 1.3939e+11  eps = 2.33e-06  iters = 1    tol = 1.0e-06  min(eta) = -14.87   S  
Iteration 11:  deviance = 1.3939e+11  eps = 5.43e-07  iters = 1    tol = 1.0e-06  min(eta) = -15.72   S  
Iteration 12:  deviance = 1.3939e+11  eps = 1.26e-07  iters = 1    tol = 1.0e-07  min(eta) = -16.63   S  
Iteration 13:  deviance = 1.3939e+11  eps = 3.09e-08  iters = 1    tol = 1.0e-07  min(eta) = -17.42   S  
Iteration 14:  deviance = 1.3939e+11  eps = 6.16e-09  iters = 1    tol = 1.0e-09  min(eta) = -17.96   S O
------------------------------------------------------------------------------------------------------------
(legend: p: exact partial-out   s: exact solver   h: step-halving   o: epsilon below tolerance)
Converged in 14 iterations and 14 HDFE sub-iterations (tol = 1.0e-08)

PPML regression                                   No. of obs      =      2,080
                                                  Residual df     =      1,990
                                                  Wald chi2(89)   =   11325.56
Deviance             =  1.39393e+11               Prob > chi2     =     0.0000
Log pseudolikelihood = -6.96967e+10               Pseudo R2       =     0.6305
-------------------------------------------------------------------------------------
                    |               Robust
            EXPjtUS | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          EXBanINDt |  -.3153367    .431953    -0.73   0.465    -1.161949    .5312758
          GDPINDtUS |   3.24e-12   2.26e-12     1.43   0.152    -1.19e-12    7.67e-12
            GDPjtUS |   4.12e-13   1.45e-13     2.83   0.005     1.27e-13    6.97e-13
         ExchjtjIDR |  -9.549194   8.119171    -1.18   0.240    -25.46248    6.364088
NickelGlobalPricemt |   .0000343   .0000714     0.48   0.631    -.0001057    .0001743
           Pandemic |   .6521554    .698013     0.93   0.350    -.7159249    2.020236
                    |
             negara |
          Aljazair  |  -3.752628   1.101659    -3.41   0.001     -5.91184   -1.593417
   Amerika Serikat  |  -5.760756   2.904674    -1.98   0.047    -11.45381   -.0676992
            Angola  |  -6.830673   1.263774    -5.40   0.000    -9.307625    -4.35372
         Australia  |  -2.689184   .9011427    -2.98   0.003    -4.455391    -.922977
           Austria  |  -7.265089    1.28812    -5.64   0.000    -9.789757    -4.74042
        Bangladesh  |  -.1331601    1.01311    -0.13   0.895     -2.11882      1.8525
           Belanda  |   2.461212   .9550627     2.58   0.010     .5893239    4.333101
           Belarus  |  -2.437102   .9976954    -2.44   0.015    -4.392549   -.4816554
            Belgia  |   .9052063   .8971202     1.01   0.313    -.8531169    2.663529
            Brazil  |   .8768563   .9067285     0.97   0.334    -.9002989    2.654012
            Brunei  |  -6.728021   1.081417    -6.22   0.000     -8.84756   -4.608482
           Brunei   |   -6.21098   .9827001    -6.32   0.000    -8.137036   -4.284923
          Bulgaria  |  -.2973734    .903022    -0.33   0.742    -2.067264    1.472517
             Burma  |  -2.745393   1.130551    -2.43   0.015    -4.961232   -.5295531
             Chili  |  -4.459043   1.363087    -3.27   0.001    -7.130645   -1.787442
             China  |   .7129879   2.064497     0.35   0.730    -3.333351    4.759327
           Denmark  |  -8.842983   1.049389    -8.43   0.000    -10.89975   -6.786218
           Ekuador  |   .0458829   .9345264     0.05   0.961    -1.785755    1.877521
           Estonia  |   -2.18543    1.02564    -2.13   0.033    -4.195647   -.1752133
              Fiji  |  -7.245235   .9123981    -7.94   0.000    -9.033503   -5.456968
         Finlandia  |  -7.337256   1.244349    -5.90   0.000    -9.776135   -4.898377
             Ghana  |    -10.499   .8161903   -12.86   0.000     -12.0987   -8.899297
            Guinea  |  -1.108634   3.168876    -0.35   0.726    -7.319518    5.102249
          Hungaria  |   -9.25845   1.096743    -8.44   0.000    -11.40803   -7.108873
             India  |    3.11711   .9095957     3.43   0.001     1.334336    4.899885
           Inggris  |  -1.210647   .9193697    -1.32   0.188    -3.012578    .5912845
              Irak  |   -4.18043   1.559374    -2.68   0.007    -7.236747   -1.124114
              Iran  |   1.730735    4.11815     0.42   0.674    -6.340691    9.802161
            Israel  |  -1.591067   1.001344    -1.59   0.112    -3.553665    .3715312
            Italia  |    3.28174   .9214949     3.56   0.000     1.475643    5.087837
            Jepang  |   3.478185   1.009112     3.45   0.001     1.500361    5.456009
            Jerman  |  -2.550915   1.081797    -2.36   0.018    -4.671198   -.4306325
           Kamboja  |   -1.96226     2.9188    -0.67   0.501    -7.683002    3.758482
            Kanada  |  -3.020721   .9171142    -3.29   0.001    -4.818232   -1.223211
        Kazakhstan  |  -9.672477   .9740554    -9.93   0.000    -11.58159   -7.763364
             Kenya  |  -1.149019   .9465047    -1.21   0.225    -3.004134     .706096
      Kep. Salomon  |  -7.616336   .9643931    -7.90   0.000    -9.506512    -5.72616
          Kolumbia  |   1.053889   2.089651     0.50   0.614    -3.041751     5.14953
     Korea Selatan  |   4.761598   1.293996     3.68   0.000     2.225412    7.297784
            Kuwait  |  -2.418159   1.158172    -2.09   0.037    -4.688134   -.1481846
              Laos  |   -3.44444   5.615441    -0.61   0.540     -14.4505    7.561622
            Latvia  |  -4.226868   1.226672    -3.45   0.001    -6.631101   -1.822635
           Lebanon  |  -2.197293   1.339779    -1.64   0.101    -4.823211    .4286256
         Lithuania  |  -1.346107   1.040571    -1.29   0.196    -3.385588     .693374
          Malaysia  |   3.506235   .9229968     3.80   0.000     1.697195    5.315276
             Malta  |  -4.054716   1.286714    -3.15   0.002    -6.576628   -1.532803
            Maroko  |  -4.121303    1.04771    -3.93   0.000    -6.174777   -2.067829
           Meksiko  |  -1.125311   .8810176    -1.28   0.202    -2.852074    .6014516
             Mesir  |  -1.404797   1.133535    -1.24   0.215    -3.626485    .8168914
           Nigeria  |  -3.415905   .9918975    -3.44   0.001    -5.359989   -1.471822
          Norwegia  |   -2.82404   .9600037    -2.94   0.003    -4.705613   -.9424674
              Oman  |  -6.635723   1.213792    -5.47   0.000    -9.014712   -4.256735
          Pakistan  |  -1.664226   1.039165    -1.60   0.109    -3.700952    .3725004
            Panama  |   .6137207   1.288823     0.48   0.634    -1.912327    3.139768
      Papua Nugini  |  -6.106651   1.188099    -5.14   0.000    -8.435282   -3.778019
          Paraguay  |   1.615679   3.726352     0.43   0.665    -5.687837    8.919194
          Perancis  |  -3.192297   1.020624    -3.13   0.002    -5.192683   -1.191911
              Peru  |  -.7199769   1.022675    -0.70   0.481    -2.724384     1.28443
          Pilipina  |  -1.641575   .9724335    -1.69   0.091     -3.54751    .2643593
          Polandia  |   .6162372   .8732663     0.71   0.480    -1.095333    2.327808
          Portugal  |  -2.203713   1.060699    -2.08   0.038    -4.282646   -.1247808
           Prancis  |  -6.617601     1.3065    -5.07   0.000    -9.178293   -4.056909
             Qatar  |  -4.444163   .9704603    -4.58   0.000     -6.34623   -2.542096
           Romania  |  -4.278705   1.288951    -3.32   0.001    -6.805003   -1.752408
             Rusia  |   .6429546   .8768307     0.73   0.463    -1.075602    2.361511
      Saudi Arabia  |   -1.55668   1.189414    -1.31   0.191    -3.887889    .7745289
     Selandia Baru  |  -3.571227   .8994885    -3.97   0.000    -5.334192   -1.808262
         Singapura  |   .9782505   .8725409     1.12   0.262    -.7318982    2.688399
          Slovenia  |  -2.208369   1.020155    -2.16   0.030    -4.207836   -.2089019
           Spanyol  |   .8821859   .8738823     1.01   0.313    -.8305919    2.594964
        Sri Langka  |  -1.257297    .848263    -1.48   0.138    -2.919862    .4052678
             Sudan  |  -9.442556   1.085034    -8.70   0.000    -11.56918   -7.315929
            Swedia  |  -4.361981    .965856    -4.52   0.000    -6.255024   -2.468938
             Swiss  |  -2.899139   1.290531    -2.25   0.025    -5.428533   -.3697448
            Taiwan  |   5.046001   .8777218     5.75   0.000     3.325697    6.766304
          Thailand  |   2.328834   .8814096     2.64   0.008      .601303    4.056365
              Togo  |  -9.915135   .9209559   -10.77   0.000    -11.72018   -8.110095
           Tunisia  |  -2.656044   .9094262    -2.92   0.003    -4.438486   -.8736011
             Turki  |   2.438084    .936579     2.60   0.009     .6024233    4.273745
           Ukraina  |  -1.157391   1.021496    -1.13   0.257    -3.159487    .8447042
  Uni Emirate Arab  |   -.732742   .8524323    -0.86   0.390    -2.403479    .9379947
           Vietnam  |    18.2835   12.22286     1.50   0.135    -5.672854    42.23986
            Yunani  |   -.394628   .9614312    -0.41   0.681    -2.278999    1.489743
                    |
              _cons |    9.65055   2.752145     3.51   0.000     4.256446    15.04465
-------------------------------------------------------------------------------------
    But if I may ask, is there any possible way to run the country fixed effect and still include the Distance variable?

    Best regards,
    Tasyadhila

    Comment

    • #3
      Dear Tasyadhila Larasati,

      You are not using the ppmlhdfe command correctly: the fixed effects should be "absorbed"; please check the help file. Anyway, if you only have one exporter in your data, the distance variable will be collinear with importer fixed effects and its effect cannot be identified; that is, the effects of distance are accounted for by the fixed effects.

      Best wishes,

      Joao

      Comment

      • #4
        Dear Professor Joao Santos Silva,

        I'm sorry for the late reply. Thank you so much for the suggestion and your explanation about the distance variable! I will definitely look up the help file that you've mentioned.

        Once again, thank you for kindly responding to my post.

        Best regards,
        Tasyadhila
        • 1 like

        Comment

        • #5
          Dear Tasyadhila Larasati


          Can you give me some hint about how you estimated country-specific coefficients/log likelihood ratios?

          Example , for
          negara, Aljazair, Amerika Serikat , Angola , Australia , Austria etc.

          Last edited by Patrick Amoatey; 16 Oct 2023, 05:42.

          Comment

          • #6
            Dear Dr Joao Santos Silva


            Can you give me some hint about how Tasyadhila Larasati estimated country-specific coefficients/log likelihood ratios? which command i use in order to obtain country specific coefficients . Thanks .

            Example , for
            negara, Aljazair, Amerika Serikat , Angola , Australia , Austria etc.

            Comment

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