using biprobit when we have two expected endogenous variable

[hussein bataineh]

Hi please I'm using biprobit because hard_final_Exact_new and csopresence1 are binary variable

when i run the code it give me that end of do-file varlist not allowed

can you advice me where is the problem and how can i solve it

  .
end of do-file

. do "C:\Users\lenovo\AppData\Local\Temp\STD5f90_000000.tmp"

. biprobit (hard_final_Exact_new =  csopresence1 CSOXWorkforceScore Firm_Size_w   ROA_w    
>   Leverage_w   Market_book_four_w   Non_pension_CFO_w   STD_CFO_w  Board_Independence_w Bo
> ardSize_w Gender_Diversity_w   Fund_Status_w  FUNDING_RATIO_w  Platn_Size_w     CSR_Commit
> tee   Environmental_Score_w  WorkforceScore_w   csravarage_w i.year    i.ff_12 ) (csoprese
> nce1 =  Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_
> Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w  
> CSR_Committee  Environmental_Score_w  WorkforceScore_w  csravarage_w  CSO_Percentage i.yea
> r i.ff_12)(CSOXWorkforceScore =  Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pensi
> on_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w  Fund_Status_w FUND
> ING_RATIO_w Platn_Size_w  CSR_Committee   Environmental_Score_w  WorkforceScore_w   csrava
> rage_w CSO_Percentage secondIV  i.year i.ff_12), vce(cluster id)
varlist not allowed
r(101);

end of do-file

r(101);

[Joerg Luedicke (StataCorp)]

It looks like you specified three equations. biprobit fits bivariate probit models and, thus, only supports two equations. I suggest to have a look at

help eprobit

as well as the corresponding manual entry. eprobit can fit models with more than one endogenous regressors, here is an example:

. webuse class10
(Class of 2010 profile)

. eprobit graduate i.roommate, endog(hsgpa   = income i.hscomp)            ///
                               endog(program = i.campus i.scholar, probit) ///
                               endog(income  = i.campus)

Iteration 0:  Log likelihood = -9157.2688  (not concave)
Iteration 1:  Log likelihood = -9156.7783  (backed up)
Iteration 2:  Log likelihood =  -9156.614  
Iteration 3:  Log likelihood = -9156.6119  
Iteration 4:  Log likelihood = -9156.5911  
Iteration 5:  Log likelihood = -9156.5856  
Iteration 6:  Log likelihood = -9156.5793  
Iteration 7:  Log likelihood = -9156.5772  
Iteration 8:  Log likelihood = -9156.5756  
Iteration 9:  Log likelihood = -9156.5753  
Iteration 10: Log likelihood = -9156.5751  
Iteration 11: Log likelihood = -9156.5751  

Extended probit regression                              Number of obs =  2,500
                                                        Wald chi2(4)  =  22.77
Log likelihood = -9156.5751                             Prob > chi2   = 0.0001

------------------------------------------------------------------------------
             | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
graduate     |
    roommate |
        Yes  |   .2649872   .1070472     2.48   0.013     .0551785    .4747959
       hsgpa |    .991704   .5127353     1.93   0.053    -.0132387    1.996647
   1.program |   .3013238   .2576345     1.17   0.242    -.2036306    .8062782
      income |   .0915139   .4532201     0.20   0.840    -.7967812    .9798089
       _cons |  -3.352342   3.600962    -0.93   0.352     -10.4101    3.705413
-------------+----------------------------------------------------------------
program      |
      campus |
        Yes  |   .7429411   .0746664     9.95   0.000     .5965976    .8892846
             |
     scholar |
        Yes  |    .867744    .056963    15.23   0.000     .7560986    .9793894
       _cons |  -.8101765   .0724318   -11.19   0.000    -.9521401   -.6682128
-------------+----------------------------------------------------------------
hsgpa        |
      income |   .0886254   .0747613     1.19   0.236     -.057904    .2351548
             |
      hscomp |
   Moderate  |  -.1350668   .0114787   -11.77   0.000    -.1575646    -.112569
       High  |  -.2265422   .0190798   -11.87   0.000     -.263938   -.1891464
             |
       _cons |   2.572057    .407984     6.30   0.000     1.772423     3.37169
-------------+----------------------------------------------------------------
income       |
      campus |
        Yes  |  -.2135974   .1699571    -1.26   0.209    -.5467071    .1195124
       _cons |   5.635327   .1562698    36.06   0.000     5.329044     5.94161
-------------+----------------------------------------------------------------
 var(e.hsgpa)|   .0844054   .0580701                      .0219155    .3250791
var(e.income)|   9.513223   .2690743                      9.000199    10.05549
-------------+----------------------------------------------------------------
corr(e.pro~m,|
  e.graduate)|    .314269   .3712271     0.85   0.397    -.4478857    .8119082
corr(e.hsgpa,|
  e.graduate)|   .2356404   .6700412     0.35   0.725     -.817857    .9261494
corr(e.inc~e,|
  e.graduate)|   .2580026   1.200357     0.21   0.830    -.9783053    .9923989
corr(e.hsgpa,|
   e.program)|   .0856338   .1626911     0.53   0.599    -.2311275    .3859806
corr(e.inc~e,|
   e.program)|  -.2394089   .0248277    -9.64   0.000    -.2874341   -.1901829
corr(e.inc~e,|
     e.hsgpa)|  -.4330377   .6450717    -0.67   0.502     -.965397    .7977869
------------------------------------------------------------------------------

[hussein bataineh]

please i use eprobit but it give me

ote: csopresence1 omitted because of collinearity.
note: CSOXWorkforceScore omitted because of collinearity.

csopresence1 and CSOXWorkforceScore is presented in the begging of the table but they are omitted at the end of the table .

also I'm not sure how can i define endogeneity test from this table

eprobit (hard_final_Exact_new csopresence1 CSOXWorkforceScore Firm_Size_w ROA_w Leverage_w Market_book_four_w   Non_pension_CFO_w STD_CFO_w Board_Independence
> _w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w i.year i.ff_12),endogenous(c
> sopresence1 = Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FU
> NDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w CSO_Percentage i.year i.ff_12) endogenous(CSOXWorkforceScore = Firm_Size_w ROA
> _w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w  Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w C
> SR_Committee Environmental_Score_w WorkforceScore_w secondIV i.year i.ff_12)
note: csopresence1 omitted because of collinearity.
note: CSOXWorkforceScore omitted because of collinearity.

Iteration 0:  Log likelihood = -13204.545  
Iteration 1:  Log likelihood = -13121.909  
Iteration 2:  Log likelihood = -13114.688  
Iteration 3:  Log likelihood = -13114.629  
Iteration 4:  Log likelihood = -13114.555  
Iteration 5:  Log likelihood = -13114.553  
Iteration 6:  Log likelihood = -13114.553  

Extended probit regression                              Number of obs =  3,150
                                                        Wald chi2(44) = 493.09
Log likelihood = -13114.553                             Prob > chi2   = 0.0000

-------------------------------------------------------------------------------------------------------------------
                                                  | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
--------------------------------------------------+----------------------------------------------------------------
hard_final_Exact_new                              |
                                     csopresence1 |    3.62564   .6545321     5.54   0.000     2.342781      4.9085
                               CSOXWorkforceScore |  -.0195763   .0106287    -1.84   0.065    -.0404082    .0012556
                                      Firm_Size_w |  -.0202174   .0612674    -0.33   0.741    -.1402993    .0998645
                                            ROA_w |   1.405963   1.027171     1.37   0.171    -.6072552    3.419181
                                       Leverage_w |  -.7194351   .3146144    -2.29   0.022    -1.336068   -.1028022
                               Market_book_four_w |   -.004823   .0047826    -1.01   0.313    -.0141967    .0045508
                                Non_pension_CFO_w |  -2.348013   1.358883    -1.73   0.084    -5.011374    .3153483
                                        STD_CFO_w |  -3.253714   2.175345    -1.50   0.135    -7.517311    1.009883
                             Board_Independence_w |   .0009876   .0042611     0.23   0.817    -.0073639    .0093391
                                      BoardSize_w |  -.0312087   .0178173    -1.75   0.080    -.0661299    .0037126
                               Gender_Diversity_w |  -.0055562   .0043716    -1.27   0.204    -.0141243    .0030119
                                    Fund_Status_w |  -4.132857   1.415855    -2.92   0.004    -6.907881   -1.357833
                                  FUNDING_RATIO_w |    -.29619   .3073107    -0.96   0.335    -.8985079    .3061279
                                     Platn_Size_w |  -.1099762   .0513196    -2.14   0.032    -.2105608   -.0093916
                                    CSR_Committee |  -.1011871   .1019336    -0.99   0.321    -.3009734    .0985991
                            Environmental_Score_w |  -.0042896   .0020408    -2.10   0.036    -.0082894   -.0002898
                                 WorkforceScore_w |   .0035072   .0035897     0.98   0.329    -.0035286    .0105429
                                                  |
                                             year |
                                            2007  |  -.0193727    .328358    -0.06   0.953    -.6629425    .6241971
                                            2008  |   .1731632   .2753203     0.63   0.529    -.3664548    .7127811
                                            2009  |   .3452598   .2815986     1.23   0.220    -.2066633     .897183
                                            2010  |   .2713281   .2793476     0.97   0.331    -.2761832    .8188395
                                            2011  |   .0477404   .2847521     0.17   0.867    -.5103635    .6058443
                                            2012  |   .1714409    .286481     0.60   0.550    -.3900516    .7329333
                                            2013  |   .0380858   .2917381     0.13   0.896    -.5337104    .6098821
                                            2014  |   .0975896   .2911974     0.34   0.738    -.4731467     .668326
                                            2015  |    .066806   .2925848     0.23   0.819    -.5066497    .6402617
                                            2016  |  -.1708587   .2939168    -0.58   0.561    -.7469251    .4052076
                                            2017  |   -.149642   .2990734    -0.50   0.617     -.735815    .4365311
                                            2018  |  -.0485731   .3139577    -0.15   0.877    -.6639189    .5667728
                                            2019  |  -.2282967   .3083104    -0.74   0.459    -.8325741    .3759806
                                            2020  |  -.0168951   .3296028    -0.05   0.959    -.6629048    .6291145
                                            2021  |  -.2526893   .3285798    -0.77   0.442    -.8966939    .3913153
                                            2022  |  -.1562966   .4272527    -0.37   0.715    -.9936964    .6811033
                                                  |
                                            ff_12 |
                                               2  |   .3305003   .2518557     1.31   0.189    -.1631277    .8241283
                                               3  |   .3671818   .1897286     1.94   0.053    -.0046794    .7390429
                                               4  |   .3005963   .2860438     1.05   0.293    -.2600392    .8612318
                                               5  |   .1542638   .1852734     0.83   0.405    -.2088654     .517393
                                               6  |    .335421   .1655866     2.03   0.043     .0108772    .6599649
                                               7  |   .3979261   .2643474     1.51   0.132    -.1201854    .9160376
                                               8  |   .3794511   .2207636     1.72   0.086    -.0532376    .8121397
                                               9  |   .5663671   .1938926     2.92   0.003     .1863447    .9463896
                                              10  |   .2198385   .1792963     1.23   0.220    -.1315758    .5712528
                                              11  |   .5720728   .1723374     3.32   0.001     .2342977     .909848
                                              12  |   .3499237   .1909227     1.83   0.067    -.0242779    .7241253
                                                  |
                                     csopresence1 |          0  (omitted)
                               CSOXWorkforceScore |          0  (omitted)
                                            _cons |  -.1999581   .7682271    -0.26   0.795    -1.705656    1.305739
--------------------------------------------------+----------------------------------------------------------------
csopresence1                                      |
                                      Firm_Size_w |  -.0242525   .0119557    -2.03   0.043    -.0476851   -.0008198
                                            ROA_w |   -.104083   .2023663    -0.51   0.607    -.5007137    .2925477
                                       Leverage_w |    .188254   .0648786     2.90   0.004     .0610944    .3154136
                               Market_book_four_w |   .0016101   .0011016     1.46   0.144     -.000549    .0037691
                                Non_pension_CFO_w |  -.0047269   .2512092    -0.02   0.985    -.4970879    .4876342
                                        STD_CFO_w |   1.738426   .4486992     3.87   0.000     .8589921     2.61786
                             Board_Independence_w |   .0011274   .0008279     1.36   0.173    -.0004952    .0027501
                                      BoardSize_w |   .0116387   .0037798     3.08   0.002     .0042303     .019047
                               Gender_Diversity_w |   .0029264   .0009073     3.23   0.001      .001148    .0047047
                                    Fund_Status_w |   .7796628   .3186903     2.45   0.014     .1550413    1.404284
                                  FUNDING_RATIO_w |   .0032378   .0594915     0.05   0.957    -.1133634    .1198389
                                     Platn_Size_w |   .0599893   .0094045     6.38   0.000     .0415568    .0784218
                                    CSR_Committee |   .0681514   .0199811     3.41   0.001     .0289891    .1073137
                            Environmental_Score_w |   .0016468   .0004345     3.79   0.000     .0007952    .0024984
                                 WorkforceScore_w |   .0013187   .0004113     3.21   0.001     .0005125    .0021248
                                   CSO_Percentage |   .7553426   .0503176    15.01   0.000     .6567219    .8539633
                                                  |
                                             year |
                                            2007  |  -.0463646   .0440523    -1.05   0.293    -.1327055    .0399763
                                            2008  |  -.0197847   .0439185    -0.45   0.652    -.1058634     .066294
                                            2009  |  -.0612077   .0444622    -1.38   0.169     -.148352    .0259366
                                            2010  |  -.0791662    .045183    -1.75   0.080    -.1677233    .0093908
                                            2011  |  -.0697056   .0457815    -1.52   0.128    -.1594357    .0200244
                                            2012  |   -.057152   .0463029    -1.23   0.217     -.147904    .0336001
                                            2013  |  -.0487728   .0463615    -1.05   0.293    -.1396397     .042094
                                            2014  |  -.0623158   .0468293    -1.33   0.183    -.1540995     .029468
                                            2015  |  -.0648011   .0475338    -1.36   0.173    -.1579656    .0283634
                                            2016  |   -.046683   .0483587    -0.97   0.334    -.1414644    .0480984
                                            2017  |  -.0698096   .0490828    -1.42   0.155      -.16601    .0263909
                                            2018  |   -.078786   .0506476    -1.56   0.120    -.1780534    .0204814
                                            2019  |  -.1187675   .0524668    -2.26   0.024    -.2216005   -.0159344
                                            2020  |  -.1429304   .0546785    -2.61   0.009    -.2500983   -.0357624
                                            2021  |  -.1731701   .0565263    -3.06   0.002    -.2839596   -.0623806
                                            2022  |  -.1476812   .0797664    -1.85   0.064    -.3040205    .0086582
                                                  |
                                            ff_12 |
                                               2  |  -.0808951   .0565663    -1.43   0.153     -.191763    .0299728
                                               3  |   -.080876   .0335659    -2.41   0.016    -.1466639   -.0150881
                                               4  |   -.060874   .0459147    -1.33   0.185    -.1508651    .0291171
                                               5  |  -.0523346   .0369463    -1.42   0.157     -.124748    .0200788
                                               6  |   .0237859   .0360985     0.66   0.510    -.0469658    .0945377
                                               7  |   .0858057   .0616916     1.39   0.164    -.0351077     .206719
                                               8  |   -.082434   .0347522    -2.37   0.018     -.150547    -.014321
                                               9  |   .0017417   .0473273     0.04   0.971     -.091018    .0945015
                                              10  |   .0512381   .0373062     1.37   0.170    -.0218807    .1243568
                                              11  |  -.0031056   .0400661    -0.08   0.938    -.0816338    .0754225
                                              12  |    .005702   .0364474     0.16   0.876    -.0657336    .0771375
                                                  |
                                            _cons |  -.5871001   .1251618    -4.69   0.000    -.8324127   -.3417874
--------------------------------------------------+----------------------------------------------------------------
CSOXWorkforceScore                                |
                                      Firm_Size_w |   -1.45258   .8895303    -1.63   0.102    -3.196027    .2908674
                                            ROA_w |  -17.08271   15.05493    -1.13   0.257    -46.58982    12.42441
                                       Leverage_w |   13.94534   4.829811     2.89   0.004     4.479083    23.41159
                               Market_book_four_w |   .0485275   .0819527     0.59   0.554    -.1120968    .2091519
                                Non_pension_CFO_w |   24.49099   18.68842     1.31   0.190    -12.13765    61.11962
                                        STD_CFO_w |   114.3302   33.37992     3.43   0.001     48.90674    179.7536
                             Board_Independence_w |   .0960169   .0615946     1.56   0.119    -.0247063    .2167401
                                      BoardSize_w |   1.053613   .2811936     3.75   0.000     .5024837    1.604742
                               Gender_Diversity_w |   .2863913   .0674799     4.24   0.000     .1541331    .4186495
                                    Fund_Status_w |   46.56486   23.70617     1.96   0.050     .1016229    93.02809
                                  FUNDING_RATIO_w |   2.398658   4.426382     0.54   0.588    -6.276891    11.07421
                                     Platn_Size_w |   4.031717   .6997755     5.76   0.000     2.660183    5.403252
                                    CSR_Committee |   2.735231   1.486323     1.84   0.066    -.1779081    5.648369
                            Environmental_Score_w |   .1310309   .0323238     4.05   0.000     .0676775    .1943843
                                 WorkforceScore_w |   .1023211   .0319825     3.20   0.001     .0396366    .1650056
                                         secondIV |   .8351057   .0380885    21.93   0.000     .7604537    .9097578
                                                  |
                                             year |
                                            2007  |  -3.021009    3.27464    -0.92   0.356    -9.439185    3.397168
                                            2008  |  -.6574135   3.256744    -0.20   0.840    -7.040515    5.725688
                                            2009  |  -3.481136   3.293277    -1.06   0.290     -9.93584    2.973568
                                            2010  |   -4.56494   3.341156    -1.37   0.172    -11.11349    1.983606
                                            2011  |  -3.752765   3.375139    -1.11   0.266    -10.36792    2.862386
                                            2012  |  -3.218531   3.403883    -0.95   0.344    -9.890019    3.452956
                                            2013  |  -3.046026   3.394636    -0.90   0.370     -9.69939    3.607339
                                            2014  |   -3.73461   3.415044    -1.09   0.274    -10.42797    2.958753
                                            2015  |   -4.73432   3.446644    -1.37   0.170    -11.48962    2.020977
                                            2016  |  -2.883719   3.487807    -0.83   0.408    -9.719696    3.952257
                                            2017  |  -4.236793    3.51604    -1.20   0.228    -11.12811    2.654519
                                            2018  |   -6.02447    3.59402    -1.68   0.094    -13.06862     1.01968
                                            2019  |  -9.070023   3.702171    -2.45   0.014    -16.32614   -1.813902
                                            2020  |  -10.46992   3.834513    -2.73   0.006    -17.98543   -2.954413
                                            2021  |  -12.98153   3.959538    -3.28   0.001    -20.74208   -5.220975
                                            2022  |  -11.26388   5.760981    -1.96   0.051    -22.55519      .02744
                                                  |
                                            ff_12 |
                                               2  |  -1.603671   4.208402    -0.38   0.703    -9.851987    6.644645
                                               3  |  -6.117639   2.464838    -2.48   0.013    -10.94863   -1.286645
                                               4  |  -6.475988   3.375053    -1.92   0.055    -13.09097    .1389936
                                               5  |  -4.931746   2.738931    -1.80   0.072    -10.29995    .4364602
                                               6  |   4.234956   2.637026     1.61   0.108    -.9335198    9.403432
                                               7  |   7.313542   4.566509     1.60   0.109    -1.636651    16.26374
                                               8  |  -6.006869   2.526608    -2.38   0.017    -10.95893   -1.054809
                                               9  |  -1.588215   3.488903    -0.46   0.649    -8.426341     5.24991
                                              10  |   5.530014   2.724785     2.03   0.042     .1895333    10.87049
                                              11  |  -.0330502   2.940761    -0.01   0.991    -5.796836    5.730736
                                              12  |   2.892394   2.641661     1.09   0.274    -2.285166    8.069954
                                                  |
                                            _cons |     -51.68   9.282641    -5.57   0.000    -69.87364   -33.48636
--------------------------------------------------+----------------------------------------------------------------
                               var(e.csopresence1)|   .1544736    .003894                       .147027    .1622974
                         var(e.CSOXWorkforceScore)|   854.9292   21.57317                      813.6751    898.2749
--------------------------------------------------+----------------------------------------------------------------
       corr(e.csopresence1,e.hard_final_Exact_new)|  -.8209715   .1127438    -7.28   0.000    -.9505654   -.4478186
 corr(e.CSOXWorkforceScore,e.hard_final_Exact_new)|  -.7458797   .1224931    -6.09   0.000    -.9060009    -.399007
         corr(e.CSOXWorkforceScore,e.csopresence1)|   .9552211   .0015624   611.37   0.000     .9520543    .9581832
-------------------------------------------------------------------------------------------------------------------

.
end of do-file

.

[Joerg Luedicke (StataCorp)]

Regarding the variables csopresence1 and CSOXWorkforceScore,notice that eprobit adds the endogenous regressors to the outcome equation automatically. Since you have added them manually, they now appeared in the outcome equation twice and so one of each is dropped.

Testing the correlation among error terms of the three equations provides an endogeneity test. The pairwise correlations are shown at the bottom of the output table. To test endogeneity for the whole system, you could perform a joint test on these correlations like so:

. webuse class10
(Class of 2010 profile)

. 
. eprobit graduate i.roommate, endog(hsgpa   = income i.hscomp)            ///
>                              endog(program = i.campus i.scholar, probit)

Iteration 0:  Log likelihood = -2887.0183  
Iteration 1:  Log likelihood = -2881.6235  
Iteration 2:  Log likelihood =   -2881.52  
Iteration 3:  Log likelihood = -2881.5197  
Iteration 4:  Log likelihood = -2881.5197  

Extended probit regression                             Number of obs =   2,500
                                                       Wald chi2(3)  = 1030.62
Log likelihood = -2881.5197                            Prob > chi2   =  0.0000

--------------------------------------------------------------------------------------------
                           | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
graduate                   |
                  roommate |
                      Yes  |   .2553803   .0528329     4.83   0.000     .1518297    .3589308
                     hsgpa |    4.22006    .148054    28.50   0.000     3.929879    4.510241
                 1.program |   .3732847   .1573866     2.37   0.018     .0648127    .6817567
                     _cons |  -12.43725   .4840316   -25.70   0.000    -13.38593   -11.48856
---------------------------+----------------------------------------------------------------
program                    |
                    campus |
                      Yes  |    .736175   .0737572     9.98   0.000     .5916134    .8807365
                           |
                   scholar |
                      Yes  |   .8783584   .0570291    15.40   0.000     .7665834    .9901333
                     _cons |  -.8053548   .0721709   -11.16   0.000    -.9468072   -.6639024
---------------------------+----------------------------------------------------------------
hsgpa                      |
                    income |   .0495944   .0016795    29.53   0.000     .0463026    .0528862
                           |
                    hscomp |
                 Moderate  |  -.1019225   .0118928    -8.57   0.000     -.125232    -.078613
                     High  |  -.1798728   .0193535    -9.29   0.000     -.217805   -.1419405
                           |
                     _cons |   2.760418   .0128848   214.24   0.000     2.735164    2.785672
---------------------------+----------------------------------------------------------------
               var(e.hsgpa)|   .0688874   .0019571                      .0651563    .0728321
---------------------------+----------------------------------------------------------------
 corr(e.program,e.graduate)|   .3145515   .0949262     3.31   0.001     .1185469    .4869622
   corr(e.hsgpa,e.graduate)|  -.4916316   .0459043   -10.71   0.000    -.5762686    -.396561
    corr(e.hsgpa,e.program)|  -.0125938   .0266912    -0.47   0.637    -.0648255    .0397067
--------------------------------------------------------------------------------------------

. 
. test (_b[/corr(e.program,e.graduate)] = 0) ///
>      (_b[/corr(e.hsgpa,e.graduate)]   = 0) ///
>      (_b[/corr(e.hsgpa,e.program)]    = 0)

 ( 1)  [/]corr(e.program,e.graduate) = 0
 ( 2)  [/]corr(e.hsgpa,e.graduate) = 0
 ( 3)  [/]corr(e.hsgpa,e.program) = 0

           chi2(  3) =  146.67
         Prob > chi2 =    0.0000

If unsure about the parameter handles, replay your results using the coeflegend option, that is:

eprobit, coeflegend

[hussein bataineh]

thanks for you advice can you please advice me how i can added

robust cluster (id)

i tried many way but non of them worked

[Joerg Luedicke (StataCorp)]

For problems like these, simply look at the help file which shows all the options available for a given command, including available variance estimators. In your case, you would add

... , ... vce(cluster id)

[hussein bataineh]

actually i run it but it show an error

eprobit (hard_final_Exact_new  Firm_Size_w ROA_w Leverage_w Market_book_four_w   Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity
> _w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w i.year i.ff_12),endogenous(csopresence1 = Firm_Size_w ROA_w
>  Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_
> Committee Environmental_Score_w WorkforceScore_w CSO_Percentage i.year i.ff_12) endogenous(CSOXWorkforceScore = Firm_Size_w ROA_w Leverage_w Market_book_four_
> w Non_pension_CFO_w STD_CFO_w  Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Scor
> e_w WorkforceScore_w secondIV i.year i.ff_12) , vce(cluster id)
invalid 'vce' 
r(198);

end of do-file

[hussein bataineh]

please i added vce(cluster id) for the endogenous variable but i could not added it for the outcome equation . is there a reason and can we added them

Thanks

eprobit (hard_final_Exact_new Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w i.year i.ff_12) ,endogenous(csopresence1 = Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w CSO_Percentage i.year i.ff_12)vce (cluster id) endogenous(CSOXWorkforceScore = Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee Environmental_Score_w WorkforceScore_w secondIV i.year i.ff_12) vce (cluster id)

[Joerg Luedicke (StataCorp)]

The chosen variance estimator applies to the entire system, yielding a full variance-covariance matrix. It would not make a lot of sense to use different variance estimators for each of the equations, certainly not in the given full maximum likelihood context. Thus, the vce() option can only be specified once, and the specification applies to the whole system of equations.

[hussein bataineh]

THANKS joerg