-------------
       log:  P:\EUP Journal Article\Final Version and Data Files\EUP Journal Article OUTPUT LOG Year-On-Year FINAL.smcl
  log type:  smcl
 opened on:   8 Dec 2011, 14:04:05

. tsset ccode year, yearly
       panel variable:  ccode (strongly balanced)
        time variable:   year, 1979 to 2007
                delta:  1 year

. **TESTING FOR PANEL HETEROSKEDASTICITY**

.
. xtgls diffpubmanwagegrowth maastricht weightednai diffpubmanprogrowth L1.diffpubmanemploygrowth L1.NetGovtBorrowing L1.changeexportshare changefdi rightlegseats cent timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa, igls panels(heteroskedastic)
Iteration 1: tolerance = .38515831
Iteration 2: tolerance = .1380349
Iteration 3: tolerance = .0328237
Iteration 4: tolerance = .00679593
Iteration 5: tolerance = .00137502
Iteration 6: tolerance = .00028244
Iteration 7: tolerance = .00005985
Iteration 8: tolerance = .0000132
Iteration 9: tolerance = 3.043e-06
Iteration 10: tolerance = 8.207e-07
Iteration 11: tolerance = 2.449e-07
Iteration 12: tolerance = 7.319e-08


Cross-sectional time-series FGLS regression

Coefficients:  generalized least squares
Panels:        heteroskedastic
Correlation:   no autocorrelation

Estimated covariances      =        17          Number of obs      =       377
Estimated autocorrelations =         0          Number of groups   =        17
Estimated coefficients     =        27          Obs per group: min =         4
                                                               avg =  22.17647
                                                               max =        26
                                                Wald chi2(26)      =    110.57
Log likelihood             = -820.5556          Prob > chi2        =    0.0000

-------------+----------------------------------------------------------------
diff~egrowth |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  maastricht |   .2236777   .3667826     0.61   0.542    -.4952031    .9425585
 weightednai |  -.0783061   3.464295    -0.02   0.982    -6.868201    6.711588
diff~ogrowth |   .2569274   .0342027     7.51   0.000     .1898914    .3239634
diff~ygrowth |
         L1. |   .0212449   .0391663     0.54   0.588    -.0555197    .0980096
NetGovtBor~g |
         L1. |   .0356608    .041786     0.85   0.393    -.0462383    .1175598
changeexpo~e |
         L1. |   .0020942   .0188779     0.11   0.912    -.0349059    .0390942
   changefdi |   .0003734   .0058822     0.06   0.949    -.0111556    .0119024
rightlegse~s |   .0052076   .0104086     0.50   0.617    -.0151929    .0256082
        cent |   5.526797   2.721395     2.03   0.042     .1929605    10.86063
   timetrend |    .013608   .0155962     0.87   0.383    -.0169599    .0441759
         aus |  -1.630988   1.180154    -1.38   0.167    -3.944048    .6820706
         aut |  -4.407193   1.618894    -2.72   0.006    -7.580168   -1.234219
         bel |  -2.210408   .8842362    -2.50   0.012    -3.943479   -.4773372
         den |  -2.436062   .7112013    -3.43   0.001    -3.829991   -1.042133
         fin |  -1.487058   .7626453    -1.95   0.051    -2.981815    .0076995
         fra |  -1.577131   .6317575    -2.50   0.013    -2.815353   -.3389088
         ger |  -3.185496   .6670901    -4.78   0.000    -4.492968   -1.878023
         ire |  -1.176223   1.388307    -0.85   0.397    -3.897255     1.54481
         ita |  -.6785966   .8943629    -0.76   0.448    -2.431516    1.074323
         jap |  -.7163738    .611635    -1.17   0.242    -1.915156    .4824087
        neth |  -3.297589   .9620834    -3.43   0.001    -5.183238    -1.41194
         swe |  -2.128351   .9436856    -2.26   0.024    -3.977941   -.2787615
          uk |  -1.358441     .66134    -2.05   0.040    -2.654644   -.0622389
         can |  -.8037655   .5729192    -1.40   0.161    -1.926667    .3191354
        port |  -.8062693    1.01301    -0.80   0.426    -2.791733    1.179195
         spa |  -1.203788   .6842805    -1.76   0.079    -2.544953    .1373773
       _cons |  -.5158552   1.344834    -0.38   0.701    -3.151681    2.119971
-------------+----------------------------------------------------------------

.
. estimates store hetero

.
. xtgls diffpubmanwagegrowth maastricht weightednai diffpubmanprogrowth L1.diffpubmanemploygrowth L1.NetGovtBorrowing L1.changeexportshare changefdi rightlegseats cent timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa

Cross-sectional time-series FGLS regression

Coefficients:  generalized least squares
Panels:        homoskedastic
Correlation:   no autocorrelation

Estimated covariances      =         1          Number of obs      =       377
Estimated autocorrelations =         0          Number of groups   =        17
Estimated coefficients     =        27          Obs per group: min =         4
                                                               avg =  22.17647
                                                               max =        26
                                                Wald chi2(26)      =    132.10
Log likelihood             = -894.1237          Prob > chi2        =    0.0000

-------------+----------------------------------------------------------------
diff~egrowth |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  maastricht |   .5534187   .5233636     1.06   0.290    -.4723551    1.579192
 weightednai |   -4.16367   4.441099    -0.94   0.348    -12.86807    4.540725
diff~ogrowth |   .3799793   .0394194     9.64   0.000     .3027187      .45724
diff~ygrowth |
         L1. |   .0298595   .0457553     0.65   0.514    -.0598193    .1195383
NetGovtBor~g |
         L1. |     .09065    .051011     1.78   0.076    -.0093296    .1906297
changeexpo~e |
         L1. |  -.0055805   .0292499    -0.19   0.849    -.0629092    .0517483
   changefdi |  -.0007475   .0080169    -0.09   0.926    -.0164603    .0149654
rightlegse~s |  -.0119971   .0128117    -0.94   0.349    -.0371076    .0131133
        cent |   6.485144   3.709688     1.75   0.080    -.7857119      13.756
   timetrend |   .0282685   .0209714     1.35   0.178    -.0128347    .0693718
         aus |  -2.318465    1.03496    -2.24   0.025     -4.34695   -.2899804
         aut |  -5.816381   2.183139    -2.66   0.008    -10.09526   -1.537506
         bel |   -3.41172   1.635324    -2.09   0.037    -6.616897   -.2065433
         den |  -3.220081   .9449334    -3.41   0.001    -5.072116   -1.368046
         fin |  -2.393958   .9605357    -2.49   0.013    -4.276573   -.5113425
         fra |  -1.930965   .8255438    -2.34   0.019    -3.549001   -.3129289
         ger |  -3.971802   .9697594    -4.10   0.000    -5.872495   -2.071108
         ire |  -.8605357   1.031069    -0.83   0.404    -2.881393    1.160322
         ita |  -1.636984   .9849086    -1.66   0.096    -3.567369    .2934017
         jap |  -.5807447   .7636981    -0.76   0.447    -2.077565     .916076
        neth |  -4.379101   1.296659    -3.38   0.001    -6.920506   -1.837697
         swe |  -2.972779   1.199543    -2.48   0.013     -5.32384   -.6217168
          uk |  -1.554987   .7262691    -2.14   0.032    -2.978448   -.1315254
         can |  -1.216544   .7820224    -1.56   0.120     -2.74928    .3161921
        port |  -2.077775     1.2936    -1.61   0.108    -4.613185    .4576347
         spa |  -2.387158   1.086551    -2.20   0.028    -4.516759    -.257558
       _cons |   1.050205    1.80919     0.58   0.562    -2.495743    4.596153
-------------+----------------------------------------------------------------

.
. local df = e(N_g) - 1

.
. lrtest hetero . , df(`df')

Likelihood-ratio test                                  LR chi2(16) =    147.14
(Assumption: . nested in hetero)                       Prob > chi2 =    0.0000

.
. **TESTING FOR SERIAL CORRELATION**

.
. xtserial diffpubmanwagegrowth maastricht weightednai diffpubmanprogrowth lagdiffemploymentgrowth lagborrowing lagexports changefdi  rightlegseats cent timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa

Wooldridge test for autocorrelation in panel data
H0: no first-order autocorrelation
    F(  1,      15) =      5.275
           Prob > F =      0.0365

.
. ***RESULTS FOR YEAR-ON-YEAR MODELS, TABLE 1**

.
.  **MODEL 1**

.
. xtpcse diffpubmanwagegrowth maastricht emu diffpubmanprogrowth L1.diffpubmanemploygrowth L1.NetGovtBorrowing L1.changeexportshare changefdi rightlegseats cent timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa, corr(psar)

Number of gaps in sample:  6
(note: computations for rho restarted at each gap)
(note: estimates of rho outside [-1,1] bounded to be in the range [-1,1])
(note: the number of observations per panel, e(n_sigma) = 1,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 22.176471; you may want to consider the pairwise option)

Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:   ccode                         Number of obs      =       377
Time variable:    year                          Number of groups   =        17
Panels:           correlated (unbalanced)       Obs per group: min =         4
Autocorrelation:  panel-specific AR(1)                         avg =  22.17647
Sigma computed by  casewise selection                          max =        26
Estimated covariances      =       153          R-squared          =    0.2788
Estimated autocorrelations =        17          Wald chi2(17)      =  3.32e+06
Estimated coefficients     =        27          Prob > chi2        =    0.0000

-------------+----------------------------------------------------------------
             |           Panel-corrected
diff~egrowth |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  maastricht |   .2443543   .2533931     0.96   0.335    -.2522871    .7409957
         emu |   .6130743   .3376173     1.82   0.069    -.0486434    1.274792
diff~ogrowth |    .385745   .0356364    10.82   0.000     .3158989    .4555911
diff~ygrowth |
         L1. |   .0249513   .0331859     0.75   0.452    -.0400919    .0899945
NetGovtBor~g |
         L1. |   .0478858   .0221451     2.16   0.031     .0044822    .0912895
changeexpo~e |
         L1. |   .0006178   .0194441     0.03   0.975    -.0374919    .0387275
   changefdi |   -.001763   .0031801    -0.55   0.579    -.0079958    .0044698
rightlegse~s |  -.0090995   .0059635    -1.53   0.127    -.0207878    .0025889
        cent |   5.233724   1.980234     2.64   0.008     1.352536    9.114912
   timetrend |   .0036853   .0173648     0.21   0.832     -.030349    .0377197
         aus |  -1.901479   .6241979    -3.05   0.002    -3.124885   -.6780738
         aut |  -4.862663   1.158444    -4.20   0.000    -7.133172   -2.592154
         bel |  -2.827235   .7449088    -3.80   0.000    -4.287229    -1.36724
         den |   -2.84155   .3698981    -7.68   0.000    -3.566537   -2.116563
         fin |  -1.727822   .8027753    -2.15   0.031    -3.301233   -.1544118
         fra |  -1.914687   .2558489    -7.48   0.000    -2.416141   -1.413232
         ger |  -3.708429   .6170387    -6.01   0.000    -4.917803   -2.499055
         ire |  -1.027784   1.601321    -0.64   0.521    -4.166315    2.110747
         ita |   -1.42922   .5198356    -2.75   0.006    -2.448079   -.4103606
         jap |  -.6321568   .4156219    -1.52   0.128    -1.446761    .1824471
        neth |  -3.898953    .714597    -5.46   0.000    -5.299537   -2.498369
         swe |  -2.268926   1.214124    -1.87   0.062    -4.648565    .1107129
          uk |  -1.442312   .3212238    -4.49   0.000    -2.071899   -.8127253
         can |  -1.179956   .3607874    -3.27   0.001    -1.887086   -.4728256
        port |  -1.069056   .6640147    -1.61   0.107    -2.370501    .2323885
         spa |  -2.091022   .5117769    -4.09   0.000    -3.094086   -1.087958
       _cons |    .977614   .9426277     1.04   0.300    -.8699024     2.82513
-------------+----------------------------------------------------------------
        rhos = -.0679804  .2178766 -.0837541  .2672649  .1819162 ...   .396531
------------------------------------------------------------------------------

.
. **WALD TEST FOR MODEL 1 BETWEEN EMU AND MAASTRICHT DUMMY**

.
. test maastricht=emu

 ( 1)  maastricht - emu = 0

           chi2(  1) =    6.73
         Prob > chi2 =    0.0095

.
. **MODEL 2**

.
. xtpcse diffpubmanwagegrowth maastricht weightednai diffpubmanprogrowth L1.diffpubmanemploygrowth L1.NetGovtBorrowing L1.changeexportshare changefdi rightlegseats cent timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa, corr(psar)

Number of gaps in sample:  6
(note: computations for rho restarted at each gap)
(note: estimates of rho outside [-1,1] bounded to be in the range [-1,1])
(note: the number of observations per panel, e(n_sigma) = 1,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 22.176471; you may want to consider the pairwise option)

Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:   ccode                         Number of obs      =       377
Time variable:    year                          Number of groups   =        17
Panels:           correlated (unbalanced)       Obs per group: min =         4
Autocorrelation:  panel-specific AR(1)                         avg =  22.17647
Sigma computed by  casewise selection                          max =        26
Estimated covariances      =       153          R-squared          =    0.2828
Estimated autocorrelations =        17          Wald chi2(17)      =  3.73e+07
Estimated coefficients     =        27          Prob > chi2        =    0.0000

-------------+----------------------------------------------------------------
             |           Panel-corrected
diff~egrowth |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  maastricht |    .280849   .1836595     1.53   0.126     -.079117    .6408149
 weightednai |  -5.919986   1.648118    -3.59   0.000    -9.150237   -2.689735
diff~ogrowth |   .3880969    .035649    10.89   0.000      .318226    .4579677
diff~ygrowth |
         L1. |   .0248187   .0331019     0.75   0.453    -.0400597    .0896972
NetGovtBor~g |
         L1. |   .0536909   .0235612     2.28   0.023     .0075117    .0998701
changeexpo~e |
         L1. |  -.0019709   .0198787    -0.10   0.921    -.0409325    .0369906
   changefdi |  -.0017701   .0032608    -0.54   0.587    -.0081611    .0046209
rightlegse~s |   -.009011   .0048487    -1.86   0.063    -.0185142    .0004923
        cent |   5.104224   2.156256     2.37   0.018     .8780397    9.330409
   timetrend |   .0127284   .0111058     1.15   0.252    -.0090386    .0344954
         aus |  -2.119577   .6999726    -3.03   0.002    -3.491498   -.7476556
         aut |  -4.918423   1.186754    -4.14   0.000    -7.244419   -2.592427
         bel |  -3.109333   .6928746    -4.49   0.000    -4.467342   -1.751324
         den |  -3.002316   .3766883    -7.97   0.000    -3.740611    -2.26402
         fin |  -2.094977   .8672326    -2.42   0.016    -3.794722   -.3952327
         fra |  -2.078561   .3036839    -6.84   0.000     -2.67377   -1.483351
         ger |  -3.712959   .6707359    -5.54   0.000    -5.027577   -2.398341
         ire |  -1.293797   1.670752    -0.77   0.439    -4.568412    1.980817
         ita |  -1.793683   .6066744    -2.96   0.003    -2.982743   -.6046231
         jap |  -.7591395   .4783338    -1.59   0.113    -1.696656    .1783774
        neth |  -3.948455   .7224905    -5.47   0.000    -5.364511     -2.5324
         swe |  -2.538311   1.337878    -1.90   0.058    -5.160504    .0838818
          uk |  -1.552838   .4099171    -3.79   0.000    -2.356261   -.7494152
         can |  -1.394344   .4382481    -3.18   0.001    -2.253295   -.5353939
        port |  -1.355641   .6774808    -2.00   0.045    -2.683479   -.0278028
         spa |  -2.301221   .5424136    -4.24   0.000    -3.364332    -1.23811
       _cons |   1.751234   1.071368     1.63   0.102    -.3486085    3.851077
-------------+----------------------------------------------------------------
        rhos = -.0795559  .2137123 -.1261477   .282686  .2021417 ...  .4560395
------------------------------------------------------------------------------

.
. **MODEL 3**

.
. xtpcse diffpubmanwagegrowth maastricht weightednai diffpubmanprogrowth L1.diffpubmanemploygrowth L1.NetGovtBorrowing L1.changeexportshare changefdi rightlegseats wcoord timetrend aus aut bel den fin fra ger ire ita jap neth swe uk can port spa, corr(psar)
(note: the number of observations per panel, e(n_sigma) = 2,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 23.411765; you may want to consider the pairwise option)

Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:   ccode                         Number of obs      =       398
Time variable:    year                          Number of groups   =        17
Panels:           correlated (unbalanced)       Obs per group: min =         4
Autocorrelation:  panel-specific AR(1)                         avg =  23.41176
Sigma computed by  casewise selection                          max =        26
Estimated covariances      =       153          R-squared          =    0.2722
Estimated autocorrelations =        17          Wald chi2(20)      =  84681.52
Estimated coefficients     =        27          Prob > chi2        =    0.0000

-------------+----------------------------------------------------------------
             |           Panel-corrected
diff~egrowth |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  maastricht |  -.1060793   .3106656    -0.34   0.733    -.7149726     .502814
 weightednai |   -4.64544   1.962365    -2.37   0.018    -8.491604   -.7992748
diff~ogrowth |   .3830409   .0330566    11.59   0.000     .3182511    .4478307
diff~ygrowth |
         L1. |   .0401324   .0388579     1.03   0.302    -.0360276    .1162925
NetGovtBor~g |
         L1. |   .0560215   .0343596     1.63   0.103    -.0113221     .123365
changeexpo~e |
         L1. |   .0134178   .0176349     0.76   0.447     -.021146    .0479817
   changefdi |  -.0012399    .004881    -0.25   0.799    -.0108065    .0083268
rightlegse~s |  -.0191295    .005708    -3.35   0.001    -.0303169    -.007942
      wcoord |   .4454635   .1571411     2.83   0.005     .1374726    .7534545
   timetrend |   .0096318    .013837     0.70   0.486    -.0174882    .0367518
         aus |  -2.114493   .7542232    -2.80   0.005    -3.592743    -.636243
         aut |  -3.455968   .7455507    -4.64   0.000    -4.917221   -1.994716
         bel |  -3.448539   .9257195    -3.73   0.000    -5.262916   -1.634163
         den |  -3.176037     .39057    -8.13   0.000     -3.94154   -2.410534
         fin |  -2.776312   .7590009    -3.66   0.000    -4.263927   -1.288698
         fra |  -2.508571   .8007677    -3.13   0.002    -4.078047   -.9390948
         ger |  -3.977913   .6238994    -6.38   0.000    -5.200734   -2.755093
         ire |  -1.330085   1.223923    -1.09   0.277     -3.72893    1.068761
         ita |  -2.328207   .9370445    -2.48   0.013     -4.16478    -.491633
         jap |  -2.261033   .5811566    -3.89   0.000    -3.400079   -1.121987
        neth |  -3.836295   .5784963    -6.63   0.000    -4.970127   -2.702463
         swe |  -2.472399   .9548231    -2.59   0.010    -4.343818     -.60098
          uk |  -1.480683   .4340831    -3.41   0.001     -2.33147   -.6298955
         can |  -1.437362   .7028382    -2.05   0.041      -2.8149   -.0598249
        port |  -2.236957   .8298528    -2.70   0.007    -3.863438   -.6104752
         spa |  -2.740167   .6182039    -4.43   0.000    -3.951824   -1.528509
       _cons |    2.99819   .8174934     3.67   0.000     1.395932    4.600448
-------------+----------------------------------------------------------------
        rhos = -.0333061  .2519194 -.1784455  .2717103  .1126737 ...  .5146096
------------------------------------------------------------------------------

. log close
       log:  P:\EUP Journal Article\Final Version and Data Files\EUP Journal Article OUTPUT LOG Year-On-Year FINAL.smcl
  log type:  smcl
 closed on:   8 Dec 2011, 14:05:01
-------------