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  • Problem with year dummy variable - Hausman and GMM models

    Dear Statalisters,


    I am trying to run a couple of models using the Hausman test and GMM model. In my models the credit risk index is used as a dependent variables and I have a lot of control variables which are accounting ratios including interaction variables. For the sake of the research I have added additional dummy variables. In particular, I have added country and year dummy variables. However, for some reason when I added both dummies the year dummy variables are omitted from the regressions. In addition for the hausman test I am getting an error when performing
    Code:
    hausman fe re
    .

    Please see below the results from stata for the hausman test:

    Code:
     xtreg llrgl official capital restrict pm ownership_concentration ownership_government ownership_foreign officialgo capitalgo restrictgo pmgo insitution cir deposit_asset netloantotalassets otherearningassets incomediversity  size tier1 fundingragility  luqidasset gdp_growth inflation islamic_d crisis_d d_iraq d_bahrain d_syrianarabrepublic d_palestinianterritories d_oman d_tunisia d_yemen d_saudiarabia d_jordan d_kuwait d_iran d_unitedarabemirates d_qatar d_lebanon d_egypt d_morocco d_libya d_algeria d_israel y2005 y2006 y2007 y2008 y2009 y2010 y2011 y2012 y2013 y2014 y2015 y2016 y2017 y2018,fe
    note: d_libya omitted because of collinearity
    note: y2005 omitted because of collinearity
    note: y2006 omitted because of collinearity
    note: y2007 omitted because of collinearity
    note: y2008 omitted because of collinearity
    note: y2009 omitted because of collinearity
    note: y2010 omitted because of collinearity
    note: y2011 omitted because of collinearity
    note: y2012 omitted because of collinearity
    note: y2013 omitted because of collinearity
    note: y2014 omitted because of collinearity
    note: y2015 omitted because of collinearity
    note: y2016 omitted because of collinearity
    note: y2017 omitted because of collinearity
    note: y2018 omitted because of collinearity
    
    Fixed-effects (within) regression               Number of obs      =      3123
    Group variable: y                               Number of groups   =        14
    
    R-sq:  within  = 0.2390                         Obs per group: min =       222
           between = 0.4194                                        avg =     223.1
           overall = 0.2495                                        max =       225
    
                                                    F(43,3066)         =     22.39
    corr(u_i, Xb)  = 0.0873                         Prob > F           =    0.0000
    
    ------------------------------------------------------------------------------
           llrgl |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
        official |   .0038839   .0011618     3.34   0.001     .0016059     .006162
         capital |   .0017966    .002141     0.84   0.401    -.0024014    .0059946
        restrict |   -.000398   .0011191    -0.36   0.722    -.0025922    .0017963
              pm |  -.0031331   .0017067    -1.84   0.066    -.0064795    .0002133
    ownership~on |   -.015646    .006095    -2.57   0.010    -.0275967   -.0036952
    ownership_~t |   .0091731   .0147464     0.62   0.534    -.0197407    .0380868
    ownership~gn |   .0069704   .0069392     1.00   0.315    -.0066354    .0205763
      officialgo |   .0117919   .0040388     2.92   0.004     .0038728     .019711
       capitalgo |  -.0184831   .0150556    -1.23   0.220    -.0480032    .0110371
      restrictgo |  -.0144018   .0102774    -1.40   0.161     -.034553    .0057494
            pmgo |   .0081386   .0156964     0.52   0.604    -.0226379    .0389151
      insitution |  -.0129137   .0059143    -2.18   0.029    -.0245101   -.0013174
             cir |   .0007281   .0001694     4.30   0.000     .0003959    .0010602
    deposit_as~t |  -.0173811   .0076586    -2.27   0.023    -.0323976   -.0023645
    netloantot~s |   .0182248   .0085225     2.14   0.033     .0015143    .0349353
    otherearni~s |   .0119137   .0081389     1.46   0.143    -.0040447     .027872
    incomedive~y |   .0053881   .0029405     1.83   0.067    -.0003775    .0111537
            size |   .0023331   .0007904     2.95   0.003     .0007833    .0038829
           tier1 |    .057377   .0116199     4.94   0.000     .0345933    .0801606
    fundingrag~y |  -.0207795   .0105469    -1.97   0.049    -.0414593   -.0000998
      luqidasset |    .074278   .0117199     6.34   0.000     .0512984    .0972576
      gdp_growth |  -.1989706   .0536171    -3.71   0.000    -.3040997   -.0938415
       inflation |   .0282101   .0329776     0.86   0.392    -.0364504    .0928706
       islamic_d |  -.0001455   .0043465    -0.03   0.973    -.0086678    .0083767
        crisis_d |  -.0338002   .0118988    -2.84   0.005    -.0571306   -.0104699
          d_iraq |  -.0048665   .0380815    -0.13   0.898    -.0795343    .0698013
       d_bahrain |   .0186222   .0375909     0.50   0.620    -.0550836    .0923281
    d_syrianar~c |    .124066   .0371815     3.34   0.001     .0511629    .1969692
    d_palestin~s |  -.0407704   .0385034    -1.06   0.290    -.1162654    .0347247
          d_oman |  -.0125223   .0383842    -0.33   0.744    -.0877837    .0627391
       d_tunisia |   .0202414   .0370801     0.55   0.585    -.0524629    .0929457
         d_yemen |   .1516515   .0394347     3.85   0.000     .0743303    .2289727
    d_saudiara~a |  -.0186832   .0370288    -0.50   0.614    -.0912869    .0539205
        d_jordan |   .0036143   .0373798     0.10   0.923    -.0696777    .0769063
        d_kuwait |   .0099159   .0378479     0.26   0.793    -.0642939    .0841258
          d_iran |   .0047275   .0369763     0.13   0.898    -.0677734    .0772284
    d_unitedar~s |   .0301234   .0373613     0.81   0.420    -.0431322    .1033791
         d_qatar |   .0018074   .0381207     0.05   0.962    -.0729373    .0765521
       d_lebanon |  -.0097472   .0371587    -0.26   0.793    -.0826056    .0631111
         d_egypt |   .0297313   .0364685     0.82   0.415    -.0417738    .1012364
       d_morocco |   .0069515    .037545     0.19   0.853    -.0666645    .0805674
         d_libya |  (omitted)
       d_algeria |  -.0164023    .036954    -0.44   0.657    -.0888594    .0560549
        d_israel |  -.0048745   .0386857    -0.13   0.900     -.080727    .0709779
           y2005 |  (omitted)
           y2006 |  (omitted)
           y2007 |  (omitted)
           y2008 |  (omitted)
           y2009 |  (omitted)
           y2010 |  (omitted)
           y2011 |  (omitted)
           y2012 |  (omitted)
           y2013 |  (omitted)
           y2014 |  (omitted)
           y2015 |  (omitted)
           y2016 |  (omitted)
           y2017 |  (omitted)
           y2018 |  (omitted)
           _cons |    .005008    .036791     0.14   0.892    -.0671296    .0771455
    -------------+----------------------------------------------------------------
         sigma_u |  .02898305
         sigma_e |  .08719826
             rho |  .09948621   (fraction of variance due to u_i)
    ------------------------------------------------------------------------------
    F test that all u_i=0:     F(13, 3066) =    -0.00            Prob > F = 1.0000

    Code:
    Note: the rank of the differenced variance matrix (39) does not equal the number of coefficients being tested (43); be sure this is what you expect, or there may be problems computing the test.
            Examine the output of your estimators for anything unexpected and possibly consider scaling your variables so that the coefficients are on a similar scale.
    
                     ---- Coefficients ----
                 |      (b)          (B)            (b-B)     sqrt(diag(V_b-V_B))
                 |       fe           re         Difference          S.E.
    -------------+----------------------------------------------------------------
        official |    .0038839     .0038839        8.44e-16        4.00e-10
         capital |    .0017966     .0017966       -2.32e-16               .
        restrict |    -.000398     -.000398       -2.30e-16               .
              pm |   -.0031331    -.0031331       -5.79e-16        1.14e-09
    ownership~on |    -.015646     -.015646        2.05e-16        4.94e-10
    ownership_~t |    .0091731     .0091731        8.21e-15               .
    ownership~gn |    .0069704     .0069704       -3.91e-16        1.46e-09
      officialgo |    .0117919     .0117919       -7.74e-15               .
       capitalgo |   -.0184831    -.0184831        2.17e-14        1.15e-08
      restrictgo |   -.0144018    -.0144018        2.74e-14               .
            pmgo |    .0081386     .0081386       -4.00e-14               .
      insitution |   -.0129137    -.0129137       -3.24e-16        2.44e-09
             cir |    .0007281     .0007281        8.67e-18        7.72e-12
    deposit_as~t |   -.0173811    -.0173811       -4.50e-15        2.62e-09
    netloantot~s |    .0182248     .0182248        2.24e-15        1.23e-09
    otherearni~s |    .0119137     .0119137       -4.34e-17        1.27e-09
    incomedive~y |    .0053881     .0053881       -1.08e-16        4.20e-10
            size |    .0023331     .0023331        7.98e-17        1.18e-10
           tier1 |     .057377      .057377        3.96e-15        1.54e-09
    fundingrag~y |   -.0207795    -.0207795        1.12e-15               .
      luqidasset |     .074278      .074278        4.12e-15        1.13e-09
      gdp_growth |   -.1989706    -.1989706       -4.97e-15        7.06e-09
       inflation |    .0282101     .0282101       -1.88e-15        4.01e-09
       islamic_d |   -.0001455    -.0001455       -6.55e-16        3.73e-10
        crisis_d |   -.0338002    -.0338002        1.53e-15        6.16e-10
          d_iraq |   -.0048665    -.0048665       -8.98e-14        1.02e-07
       d_bahrain |    .0186222     .0186222       -9.13e-14        1.06e-07
    d_syrianar~c |     .124066      .124066       -9.34e-14        1.03e-07
    d_palestin~s |   -.0407704    -.0407704       -8.91e-14        1.03e-07
          d_oman |   -.0125223    -.0125223       -8.84e-14        1.08e-07
       d_tunisia |    .0202414     .0202414       -8.95e-14        1.06e-07
         d_yemen |    .1516515     .1516515       -9.02e-14        9.97e-08
    d_saudiara~a |   -.0186832    -.0186832       -9.16e-14        1.04e-07
        d_jordan |    .0036143     .0036143       -9.16e-14        1.07e-07
        d_kuwait |    .0099159     .0099159       -9.11e-14        1.07e-07
          d_iran |    .0047275     .0047275       -8.97e-14        1.01e-07
    d_unitedar~s |    .0301234     .0301234       -8.95e-14        1.07e-07
         d_qatar |    .0018074     .0018074       -8.97e-14        1.08e-07
       d_lebanon |   -.0097472    -.0097472       -9.09e-14        1.05e-07
         d_egypt |    .0297313     .0297313       -8.95e-14        1.03e-07
       d_morocco |    .0069515     .0069515       -8.74e-14        1.06e-07
       d_algeria |   -.0164023    -.0164023       -9.35e-14        1.03e-07
        d_israel |   -.0048745    -.0048745       -8.81e-14        1.09e-07
    ------------------------------------------------------------------------------
                               b = consistent under Ho and Ha; obtained from xtreg
                B = inconsistent under Ha, efficient under Ho; obtained from xtreg
    
        Test:  Ho:  difference in coefficients not systematic
    
                     chi2(39) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                              =    -0.00    chi2<0 ==> model fitted on these
                                            data fails to meet the asymptotic
                                            assumptions of the Hausman test;
                                            see suest for a generalized test
    Please see below the results from stata for the GMM model:

    Code:
     . xtdpdsys llrgl L(0/2).(official capital restrict pm ownership_concentration ownership_government ownership_foreign officialoc capitaloc restrictoc pmoc insitution cir deposit_asset netloantotalassets otherearningassets incomediversity  size tier1 fundingragility  luqidasset gdp_growth inflation) islamic_d d_iraq d_bahrain d_syrianarabrepublic d_palestinianterritories d_oman d_tunisia d_yemen d_saudiarabia d_jordan d_kuwait d_iran d_unitedarabemirates d_qatar d_lebanon d_egypt d_morocco d_libya d_algeria d_israel y2005 y2006 y2007 y2008 y2009 y2010 y2011 y2012 y2013 y2014 y2015 y2016 y2017 y2018, lags(3) maxldep(1) level(95.0) artests(3) vce(robust)
    note: d_libya dropped from div() because of collinearity
    note: y2005 dropped from div() because of collinearity
    note: y2006 dropped from div() because of collinearity
    note: y2007 dropped from div() because of collinearity
    note: y2008 dropped from div() because of collinearity
    note: y2009 dropped from div() because of collinearity
    note: y2010 dropped from div() because of collinearity
    note: y2011 dropped from div() because of collinearity
    note: y2012 dropped from div() because of collinearity
    note: y2013 dropped from div() because of collinearity
    note: y2014 dropped from div() because of collinearity
    note: y2015 dropped from div() because of collinearity
    note: y2016 dropped from div() because of collinearity
    note: y2017 dropped from div() because of collinearity
    note: y2018 dropped from div() because of collinearity
    note: d_libya dropped because of collinearity
    note: y2018 dropped because of collinearity
    
    System dynamic panel-data estimation         Number of obs         =      3002
    Group variable: y                            Number of groups      =        14
    Time variable: banks1
                                                 Obs per group:    min =       212
                                                                   avg =  214.4286
                                                                   max =       222
    
    Number of instruments =    510               Wald chi2(13)         =     44.58
                                                 Prob > chi2           =    0.0000
    One-step results
    ------------------------------------------------------------------------------
                 |               Robust
           llrgl |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
           llrgl |
             L1. |  -.0720103   .0134389    -5.36   0.000    -.0983501   -.0456704
             L2. |    -.07831   .0182692    -4.29   0.000     -.114117    -.042503
             L3. |  -.0687702    .024946    -2.76   0.006    -.1176636   -.0198769
                 |
        official |
             --. |   .0065155   .0012069     5.40   0.000     .0041501    .0088809
             L1. |  -.0002886   .0006123    -0.47   0.637    -.0014887    .0009116
             L2. |   .0027929   .0010561     2.64   0.008     .0007231    .0048628
                 |
         capital |
             --. |   .0038683   .0030165     1.28   0.200     -.002044    .0097805
             L1. |  -.0049698   .0019284    -2.58   0.010    -.0087494   -.0011903
             L2. |  -.0062805   .0019119    -3.28   0.001    -.0100279   -.0025332
                 |
        restrict |
             --. |  -.0011405   .0009409    -1.21   0.225    -.0029846    .0007036
             L1. |   .0032487   .0011625     2.79   0.005     .0009701    .0055272
             L2. |   .0006031   .0018838     0.32   0.749     -.003089    .0042952
                 |
              pm |
             --. |  -.0081911   .0031125    -2.63   0.008    -.0142916   -.0020907
             L1. |  -.0002275   .0010763    -0.21   0.833     -.002337     .001882
             L2. |   .0036995   .0020319     1.82   0.069     -.000283     .007682
                 |
    ownership~on |
             --. |  -.0365876   .0092236    -3.97   0.000    -.0546656   -.0185096
             L1. |  -.0434792   .0091653    -4.74   0.000     -.061443   -.0255155
             L2. |  -.0291278   .0061178    -4.76   0.000    -.0411185    -.017137
                 |
    ownership_~t |
             --. |   .0048043   .0149779     0.32   0.748    -.0245517    .0341604
             L1. |   .0260584   .0062811     4.15   0.000     .0137477    .0383691
             L2. |   .0133432   .0132522     1.01   0.314    -.0126305     .039317
                 |
    ownership~gn |
             --. |   .0177407   .0058556     3.03   0.002      .006264    .0292174
             L1. |   .0319297   .0054232     5.89   0.000     .0213004     .042559
             L2. |   .0290427   .0071238     4.08   0.000     .0150804    .0430051
                 |
      officialoc |
             --. |  -.0011751   .0023378    -0.50   0.615     -.005757    .0034069
             L1. |  -.0030297    .002214    -1.37   0.171    -.0073691    .0013097
             L2. |  -.0045838    .003761    -1.22   0.223    -.0119552    .0027877
                 |
       capitaloc |
             --. |  -.0153738   .0054804    -2.81   0.005    -.0261151   -.0046325
             L1. |   .0090006   .0032483     2.77   0.006     .0026341    .0153671
             L2. |   .0132169   .0047842     2.76   0.006     .0038401    .0225937
                 |
      restrictoc |
             --. |   .0029544   .0017102     1.73   0.084    -.0003975    .0063062
             L1. |   .0027091    .002037     1.33   0.184    -.0012834    .0067016
             L2. |  -.0012103   .0039326    -0.31   0.758    -.0089181    .0064975
                 |
            pmoc |
             --. |   .0156747   .0045994     3.41   0.001       .00666    .0246893
             L1. |  -.0034071   .0016834    -2.02   0.043    -.0067065   -.0001078
             L2. |  -.0021397     .00477    -0.45   0.654    -.0114888    .0072094
                 |
      insitution |
             --. |  -.0211662   .0208455    -1.02   0.310    -.0620226    .0196902
             L1. |   .0119093   .0035016     3.40   0.001     .0050463    .0187722
             L2. |   .0052585   .0027133     1.94   0.053    -.0000594    .0105764
                 |
             cir |
             --. |   .0009334     .00044     2.12   0.034      .000071    .0017958
             L1. |   .0001617   .0004034     0.40   0.689     -.000629    .0009523
             L2. |   .0032874   .0015368     2.14   0.032     .0002754    .0062995
                 |
    deposit_as~t |
             --. |  -.0246839   .0154901    -1.59   0.111     -.055044    .0056762
             L1. |   .0022668   .0079698     0.28   0.776    -.0133537    .0178874
             L2. |   .0298863   .0085744     3.49   0.000     .0130808    .0466917
                 |
    netloantot~s |
             --. |    .001794   .0172069     0.10   0.917     -.031931    .0355189
             L1. |  -.0373464   .0074955    -4.98   0.000    -.0520373   -.0226554
             L2. |  -.0422985   .0073345    -5.77   0.000    -.0566739   -.0279231
                 |
    otherearni~s |
             --. |   .0167225    .012556     1.33   0.183    -.0078869    .0413318
             L1. |   .0122556    .006932     1.77   0.077    -.0013309    .0258422
             L2. |   .0180018    .007668     2.35   0.019     .0029728    .0330309
                 |
    incomedive~y |
             --. |    .004903   .0062479     0.78   0.433    -.0073427    .0171486
             L1. |   .0030614   .0028427     1.08   0.282    -.0025102     .008633
             L2. |   .0048744    .002613     1.87   0.062     -.000247    .0099958
                 |
            size |
             --. |   .0053278   .0013465     3.96   0.000     .0026887     .007967
             L1. |  -.0001408   .0011165    -0.13   0.900    -.0023292    .0020475
             L2. |  -.0024609   .0008979    -2.74   0.006    -.0042208    -.000701
                 |
           tier1 |
             --. |   .0557879   .0399342     1.40   0.162    -.0224816    .1340575
             L1. |   .0089834   .0094663     0.95   0.343    -.0095703     .027537
             L2. |  -.0081272    .012323    -0.66   0.510    -.0322798    .0160254
                 |
    fundingrag~y |
             --. |  -.0137474   .0202517    -0.68   0.497    -.0534401    .0259453
             L1. |    .013207    .007402     1.78   0.074    -.0013007    .0277148
             L2. |  -.0438212   .0148157    -2.96   0.003    -.0728594    -.014783
                 |
      luqidasset |
             --. |    .063275   .0210067     3.01   0.003     .0221026    .1044474
             L1. |  -.0185627   .0088667    -2.09   0.036    -.0359411   -.0011842
             L2. |  -.0228082   .0121122    -1.88   0.060    -.0465476    .0009313
                 |
      gdp_growth |
             --. |  -.1616009   .0655264    -2.47   0.014    -.2900304   -.0331715
             L1. |   -.068083   .0405274    -1.68   0.093    -.1475153    .0113492
             L2. |   .0375714   .0295712     1.27   0.204    -.0203872    .0955299
                 |
       inflation |
             --. |   .0621679   .0416688     1.49   0.136    -.0195013    .1438372
             L1. |   .0034605   .0201256     0.17   0.863    -.0359849     .042906
             L2. |  -.0002403   .0192849    -0.01   0.990    -.0380379    .0375574
                 |
       islamic_d |  -.0088367   .0065511    -1.35   0.177    -.0216766    .0040032
          d_iraq |  -.0327112   .0312407    -1.05   0.295    -.0939418    .0285193
       d_bahrain |  -.0197094   .0341569    -0.58   0.564    -.0866557    .0472369
    d_syrianar~c |   .1092054   .0347429     3.14   0.002     .0411106    .1773003
    d_palestin~s |   -.084552   .0333312    -2.54   0.011    -.1498801    -.019224
          d_oman |  -.0345785   .0403136    -0.86   0.391    -.1135917    .0444347
       d_tunisia |  -.0261018   .0286541    -0.91   0.362    -.0822629    .0300592
         d_yemen |   .1522827    .044021     3.46   0.001     .0660032    .2385623
    d_saudiara~a |   -.052151   .0282122    -1.85   0.065    -.1074458    .0031439
        d_jordan |  -.0510955   .0364478    -1.40   0.161    -.1225318    .0203408
        d_kuwait |  -.0289475   .0391319    -0.74   0.459    -.1056447    .0477496
          d_iran |  -.0526926   .0225709    -2.33   0.020    -.0969308   -.0084544
    d_unitedar~s |  -.0067234   .0446717    -0.15   0.880    -.0942782    .0808315
         d_qatar |  -.0256242   .0423957    -0.60   0.546    -.1087184    .0574699
       d_lebanon |  -.0507059   .0278181    -1.82   0.068    -.1052285    .0038167
         d_egypt |  -.0154882   .0171722    -0.90   0.367     -.049145    .0181687
       d_morocco |  -.0321215   .0265507    -1.21   0.226    -.0841599     .019917
       d_algeria |  -.0541153   .0227641    -2.38   0.017     -.098732   -.0094985
        d_israel |  -.0374811   .0492382    -0.76   0.447    -.1339861     .059024
           y2005 |  -.2519929    .168552    -1.50   0.135    -.5823487    .0783629
           y2006 |   .2225337   .3511054     0.63   0.526    -.4656203    .9106877
           y2007 |  -.5279423   .5005273    -1.05   0.292    -1.508958    .4530732
           y2008 |   .0713399   .1432226     0.50   0.618    -.2093712    .3520511
           y2009 |  -.1282115   .0722088    -1.78   0.076     -.269738    .0133151
           y2010 |  -.0649722   .0404767    -1.61   0.108     -.144305    .0143606
           y2011 |  -.0113741   .0357232    -0.32   0.750    -.0813903     .058642
           y2012 |   .0532066   .0593346     0.90   0.370    -.0630871    .1695003
           y2013 |    .016194   .0294777     0.55   0.583    -.0415812    .0739692
           y2014 |  -.0936169   .1024164    -0.91   0.361    -.2943495    .1071156
           y2015 |     .16353   .1270816     1.29   0.198    -.0855453    .4126053
           y2016 |   .0290089   .0293962     0.99   0.324    -.0286066    .0866244
           y2017 |  -.0045228   .0340795    -0.13   0.894    -.0713174    .0622719
           _cons |   .1022204   .0505126     2.02   0.043     .0032176    .2012233
    ------------------------------------------------------------------------------
    Instruments for differenced equation
            GMM-type: L(2/2).llrgl
            Standard: D.official LD.official L2D.official D.capital LD.capital L2D.capital D.restrict LD.restrict L2D.restrict D.pm LD.pm L2D.pm D.ownership_concentration LD.ownership_concentration
                      L2D.ownership_concentration D.ownership_government LD.ownership_government L2D.ownership_government D.ownership_foreign LD.ownership_foreign L2D.ownership_foreign D.officialoc
                      LD.officialoc L2D.officialoc D.capitaloc LD.capitaloc L2D.capitaloc D.restrictoc LD.restrictoc L2D.restrictoc D.pmoc LD.pmoc L2D.pmoc D.insitution LD.insitution L2D.insitution
                      D.cir LD.cir L2D.cir D.deposit_asset LD.deposit_asset L2D.deposit_asset D.netloantotalassets LD.netloantotalassets L2D.netloantotalassets D.otherearningassets
                      LD.otherearningassets L2D.otherearningassets D.incomediversity LD.incomediversity L2D.incomediversity D.size LD.size L2D.size D.tier1 LD.tier1 L2D.tier1 D.fundingragility
                      LD.fundingragility L2D.fundingragility D.luqidasset LD.luqidasset L2D.luqidasset D.gdp_growth LD.gdp_growth L2D.gdp_growth D.inflation LD.inflation L2D.inflation D.islamic_d
                      D.d_iraq D.d_bahrain D.d_syrianarabrepublic D.d_palestinianterritories D.d_oman D.d_tunisia D.d_yemen D.d_saudiarabia D.d_jordan D.d_kuwait D.d_iran D.d_unitedarabemirates
                      D.d_qatar D.d_lebanon D.d_egypt D.d_morocco D.d_algeria D.d_israel
    Instruments for level equation
            GMM-type: LD.llrgl
            Standard: _cons
    
    . estat abond
    artests not computed for one-step system estimator with vce(gmm)
    
    Arellano-Bond test for zero autocorrelation in first-differenced errors
      +-----------------------+
      |Order |  z     Prob > z|
      |------+----------------|
      |   1  |-3.1031  0.0019 |
      |   2  | .83236  0.4052 |
      |   3  | .77904  0.4360 |
      +-----------------------+
    Can you please advise what is the reason of this collinearity of the y dummy variables and why the hausman test is omitting them. Is there any way to fix this? I tried to use
    Code:
    hausman fe re, sigmaless
    command but it still doesn't work.

    I would really appreciate your help if you have any recommendations or comments.
    Best Regards,
    Petko Bachvarov

  • #2
    Petko:
    - as expected, the -fe- estimator wipes out time-invariant variables. it seems to be the issue with your year dummies, that should have been gathered together in -i.year- (ie, the panel -tempvar- that you should have used in -xtset-);
    - as expected, the -hausman- test focuses on the coefficients that are common to both -fe- and -re- specifications. In addition, the error message thrown by Stata is related to coefficients that have the same value for both -fe- and -re- specifications (as such, no -sqrt(diag(V_b-V_B)) S.E:- can be calculated, and Stata reports a missing value (.)).
    Kind regards,
    Carlo
    (StataNow 18.5)

    Comment


    • #3
      Hello Carlo,

      Thank you for your answer.
      I tried to change the xtset by setting the following -tempvar-

      Code:
      . encode banks, gen(banks1)
      
      . xtset banks1 year, yearly
             panel variable:  banks1 (unbalanced)
              time variable:  year, 2005 to 2018
                      delta:  1 year
      My panel data includes banks, countries and years. However, my main focus is on the banks and the years. In this case I am setting an "xtset" of banks and year.
      This way the dummy variables are working, however the country dummy variables are not. Please see below

      Code:
      note: islamic_d omitted because of collinearity
      note: d_iraq omitted because of collinearity
      note: d_bahrain omitted because of collinearity
      note: d_syrianarabrepublic omitted because of collinearity
      note: d_palestinianterritories omitted because of collinearity
      note: d_oman omitted because of collinearity
      note: d_tunisia omitted because of collinearity
      note: d_yemen omitted because of collinearity
      note: d_saudiarabia omitted because of collinearity
      note: d_jordan omitted because of collinearity
      note: d_kuwait omitted because of collinearity
      note: d_unitedarabemirates omitted because of collinearity
      note: d_qatar omitted because of collinearity
      note: d_lebanon omitted because of collinearity
      note: d_egypt omitted because of collinearity
      note: d_morocco omitted because of collinearity
      note: d_libya omitted because of collinearity
      note: d_israel omitted because of collinearity
      note: y2009 omitted because of collinearity
      note: y2018 omitted because of collinearity
      
      Fixed-effects (within) regression               Number of obs      =      3123
      Group variable: banks1                          Number of groups   =       225
      
      R-sq:  within  = 0.2176                         Obs per group: min =         1
             between = 0.1904                                        avg =      13.9
             overall = 0.2078                                        max =        14
      
                                                      F(38,2860)         =     20.93
      corr(u_i, Xb)  = 0.0493                         Prob > F           =    0.0000
      
      ------------------------------------------------------------------------------
             llrgl |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
      -------------+----------------------------------------------------------------
          official |   .0048081   .0012591     3.82   0.000     .0023391     .007277
           capital |   .0013011   .0024069     0.54   0.589    -.0034184    .0060206
          restrict |  -.0013564   .0013054    -1.04   0.299    -.0039161    .0012033
                pm |  -.0042232   .0019675    -2.15   0.032     -.008081   -.0003653
      ownership~on |  -.0339676   .0121792    -2.79   0.005    -.0578486   -.0100867
      ownership_~t |   .0477545   .0170709     2.80   0.005      .014282     .081227
      ownership~gn |   .0096088   .0101461     0.95   0.344    -.0102855    .0295031
        officialoc |   .0022932   .0027629     0.83   0.407    -.0031244    .0077107
         capitaloc |  -.0036979   .0051591    -0.72   0.474    -.0138138     .006418
        restrictoc |   .0023979   .0029243     0.82   0.412     -.003336    .0081318
              pmoc |   .0013221   .0041313     0.32   0.749    -.0067785    .0094227
        insitution |  -.0157631   .0055084    -2.86   0.004    -.0265639   -.0049623
               cir |   .0004832   .0001621     2.98   0.003     .0001653     .000801
      deposit_as~t |  -.0356347   .0097261    -3.66   0.000    -.0547057   -.0165638
      netloantot~s |   .0336121   .0092717     3.63   0.000     .0154322     .051792
      otherearni~s |   .0221188   .0086959     2.54   0.011     .0050679    .0391697
      incomedive~y |   .0031741   .0028769     1.10   0.270    -.0024669    .0088151
              size |   .0024676   .0011789     2.09   0.036      .000156    .0047792
             tier1 |   .0753218   .0117424     6.41   0.000     .0522974    .0983463
      fundingrag~y |  -.0198194   .0126736    -1.56   0.118    -.0446697    .0050309
        luqidasset |   .0964352   .0135478     7.12   0.000     .0698707    .1229997
        gdp_growth |  -.1879923   .0494793    -3.80   0.000     -.285011   -.0909737
         inflation |   .0315428   .0305729     1.03   0.302    -.0284043    .0914899
         islamic_d |  (omitted)
          crisis_d |  -.0484592    .010745    -4.51   0.000    -.0695279   -.0273905
            d_iraq |  (omitted)
         d_bahrain |  (omitted)
      d_syrianar~c |  (omitted)
      d_palestin~s |  (omitted)
            d_oman |  (omitted)
         d_tunisia |  (omitted)
           d_yemen |  (omitted)
      d_saudiara~a |  (omitted)
          d_jordan |  (omitted)
          d_kuwait |  (omitted)
            d_iran |    .025003   .0531607     0.47   0.638    -.0792341    .1292401
      d_unitedar~s |  (omitted)
           d_qatar |  (omitted)
         d_lebanon |  (omitted)
           d_egypt |  (omitted)
         d_morocco |  (omitted)
           d_libya |  (omitted)
         d_algeria |  -.0133738   .0532211    -0.25   0.802    -.1177294    .0909817
          d_israel |  (omitted)
             y2005 |  -.0527017   .0111379    -4.73   0.000    -.0745409   -.0308625
             y2006 |  -.0517473   .0112297    -4.61   0.000    -.0737665   -.0297281
             y2007 |  -.0570635   .0111374    -5.12   0.000    -.0789016   -.0352254
             y2008 |    .000748   .0078864     0.09   0.924    -.0147156    .0162116
             y2009 |  (omitted)
             y2010 |  -.0408644   .0108198    -3.78   0.000    -.0620798    -.019649
             y2011 |  -.0077364   .0103352    -0.75   0.454    -.0280017    .0125288
             y2012 |   .0039433   .0105493     0.37   0.709    -.0167417    .0246283
             y2013 |   .0164501   .0104056     1.58   0.114    -.0039531    .0368532
             y2014 |   .0131326   .0102823     1.28   0.202    -.0070289     .033294
             y2015 |   .0138912   .0100608     1.38   0.167     -.005836    .0336184
             y2016 |   .0168457   .0094128     1.79   0.074    -.0016109    .0353023
             y2017 |   .0142737   .0092721     1.54   0.124     -.003907    .0324544
             y2018 |  (omitted)
             _cons |   .0337503   .0113562     2.97   0.003     .0114832    .0560174
      -------------+----------------------------------------------------------------
           sigma_u |  .05284913
           sigma_e |  .08055737
               rho |  .30089141   (fraction of variance due to u_i)
      ------------------------------------------------------------------------------
      F test that all u_i=0:     F(224, 2860) =     3.33           Prob > F = 0.0000
      Is there any way to make the settings (xtset) so that both dummies can work in the fixed effect model or should I considered that it is a random effect?
      Thank you very much for the help in advance.

      Kind Regards,
      Petko

      Comment


      • #4
        Petko:
        as we know, -fe- machinery wipes out time-invariant variables.
        This is the destiny of countries, if banks (as expected) do not change country during the time horizon the T dimension of your panel dataset stretches over.
        In order to decide which specification fits your data better, I would go -xtreg,re- and then -hausman-, just to start with.
        I would also consider whether default standard errors are correrct in your case.
        If you detect heteroskedasticity and/or autocorrelation, you should impose -robust- or -vce(cluster clusterid)- (they do the very same job under -xtreg-) standard errors and switch from -hausman- to the community-contributed module -xtoverid-, as -hausman- does not support non-default standard errors.
        See also the community-contributed module -mundlak-.
        Kind regards,
        Carlo
        (StataNow 18.5)

        Comment


        • #5
          Carlo Lazzaro

          I had the same problem of collinearity using panel data. In my sureg model, some variables have been omitted because of collinearity.
          Could you advice me about how to solve this probelm ?
          Best

          Comment


          • #6
            Patrice:
            please share what you typed and what Stata gave you back (as per FAQ). Thanks.
            Kind regards,
            Carlo
            (StataNow 18.5)

            Comment


            • #7
              carlo alberto

              Here is the code

              sureg $eq1 $eq2 $eq3 $eq4 $eq5 $eq6 $eq7 $eq8, constr(1-581) isure nolog small

              below the error message :

              /*
              note: PrinLRDryerYtot omitted because of collinearity
              note: PrinLEqryerYtot omitted because of collinearity
              note: PrinLBuryerYtot omitted because of collinearity
              note: PrinLOryerYtot omitted because of collinearity
              note: PrinyeYtot omitted because of collinearity
              note: PrinyerYtotrYtot omitted because of collinearity
              note: PrinLBurRDrYtotr omitted because of collinearity
              note: PrinLBurBurYtotr omitted because of collinearity
              note: PrinLBurOrYtotr omitted because of collinearity
              note: PrinLOrRDrYtotr omitted because of collinearity
              note: PrinLOrBurYtotr omitted because of collinearity
              note: PrinyerRDrYtotr omitted because of collinearity
              note: PrinyerEqrYtotr omitted because of collinearity
              note: PrinyerBurYtotr omitted because of collinearity
              note: PrinyerOrYtotr omitted because of collinearity
              note: PrinYtotrRDrYtotr omitted because of collinearity
              note: PrinYtotrBurYtotr omitted because of collinearity
              note: PrinO omitted because of collinearity
              note: LBuryerYtot omitted because of collinearity
              note: LOryerYtot omitted because of collinearity
              note: yeYtot omitted because of collinearity
              note: yerYtotrYtot omitted because of collinearity
              note: yerRDrYtotr omitted because of collinearity
              note: yerOrYtotr omitted because of collinearity
              note: LBuryerYtot omitted because of collinearity
              note: LOryerYtot omitted because of collinearity
              note: yeYtot omitted because of collinearity
              note: yerYtotrYtot omitted because of collinearity
              note: yerRDrYtotr omitted because of collinearity
              note: yerOrYtotr omitted because of collinearity
              note: LBuryerYtot omitted because of collinearity
              note: LOryerYtot omitted because of collinearity
              note: yeYtot omitted because of collinearity
              note: yerYtotrYtot omitted because of collinearity
              note: yerRDrYtotr omitted because of collinearity
              note: yerOrYtotr omitted because of collinearity
              note: term3RDPMi omitted because of collinearity
              note: term3EqPMi omitted because of collinearity
              note: term3BulPMi omitted because of collinearity
              note: term3OtePMi omitted because of collinearity
              redundant or inconsistent constraints
              r(412);

              end of do-file

              r(412);

              Comment


              • #8
                Patrice:
                unfortunately, you do not post -sureg- table.
                The only advice that I can provide is to check the right-hand side of your regression equation(s).
                Kind regards,
                Carlo
                (StataNow 18.5)

                Comment


                • #9
                  Dear Carlo :
                  I'm trying to estimate general leontiel cost variable function with 3 variables inputs (Labor, energy, intermediate inputs) and 4 fixe inputs (R&D, technologys information, material, and Building) using panel data.
                  Here is the sureg table

                  sureg (Ct $term1 $term2 $term3 $term4 $term5 $term6) (CSLabour $term1_labor $term2_labor $term3_labor $term4_labor $term5_labor $term6_labor) (CSNenergie $term1_energie $term2_energie $term3_energie $term4_energie $term5_energie $term6_energie) ///
                  (CSMinput $term1_minput $term2_minput $term3_minput $term4_minput $term5_minput $term6_minput) (PrixObsRD $term1RD $term2RD $term3RD $term4RD) (PrixObsEq $term1Eq $term2Eq $term3Eq $term4Eq) (PrixObsBul $term1Bul $term2Bul $term3Bul $term4Bul) (PrixObsOtech $term1Otec $term2Otec $term3Otec $term4Otec), constr(1-584) isure nolog small

                  Thanks.

                  Comment

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