How to present the first stage in 2sls when using ( biprobit )

hussein bataineh

Join Date: Apr 2023
Posts: 177

How to present the first stage in 2sls when using ( biprobit )

27 Feb 2025, 06:14

Hi please i need to present the full set of control variable for the first stage when i run biprobit

can you advice me how can i present the the full set of variable for the first stage when i run biprobit

HTML Code:

 .  biprobit (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_Diversit
> y_w Fund_Status_w FUNDING_RATIO_w Platn_Size_ CSR_Committee SustainabilityScore_w i.year i.ff_12 csopresence1)  (csopresence1 = CSO_Percentage), robust

Fitting comparison equation 1:

Iteration 0:  Log pseudolikelihood = -358.54602  
Iteration 1:  Log pseudolikelihood =   -329.264  
Iteration 2:  Log pseudolikelihood = -326.78258  
Iteration 3:  Log pseudolikelihood = -326.74249  
Iteration 4:  Log pseudolikelihood = -326.74237  
Iteration 5:  Log pseudolikelihood = -326.74237  

Fitting comparison equation 2:

Iteration 0:  Log pseudolikelihood = -1925.9727  
Iteration 1:  Log pseudolikelihood = -1705.2604  
Iteration 2:  Log pseudolikelihood = -1704.8319  
Iteration 3:  Log pseudolikelihood = -1704.8319  

Comparison:   Log pseudolikelihood = -2031.5742

Fitting full model:

Iteration 0:  Log pseudolikelihood = -2031.5742  (not concave)
Iteration 1:  Log pseudolikelihood = -2031.5152  (backed up)
Iteration 2:  Log pseudolikelihood = -2030.9562  
Iteration 3:  Log pseudolikelihood = -2030.1775  
Iteration 4:  Log pseudolikelihood = -2030.1553  
Iteration 5:  Log pseudolikelihood = -2030.1553  

Seemingly unrelated bivariate probit                    Number of obs =  3,167
                                                        Wald chi2(43) = 563.40
Log pseudolikelihood = -2030.1553                       Prob > chi2   = 0.0000

---------------------------------------------------------------------------------------
                      |               Robust
                      | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
----------------------+----------------------------------------------------------------
hard_final_Exact_new  |
          Firm_Size_w |  -.1346719   .0745992    -1.81   0.071    -.2808836    .0115398
                ROA_w |   1.946918   1.329454     1.46   0.143    -.6587632      4.5526
           Leverage_w |  -.7282058    .378328    -1.92   0.054    -1.469715    .0133033
   Market_book_four_w |  -.0006798   .0085561    -0.08   0.937    -.0174495    .0160899
    Non_pension_CFO_w |   -4.35556   1.799502    -2.42   0.016    -7.882518   -.8286009
            STD_CFO_w |   .8498084   2.625005     0.32   0.746    -4.295107    5.994723
 Board_Independence_w |   .0038096   .0050628     0.75   0.452    -.0061134    .0137326
          BoardSize_w |  -.0212048   .0238728    -0.89   0.374    -.0679947    .0255851
   Gender_Diversity_w |  -.0038736    .006345    -0.61   0.542    -.0163096    .0085624
        Fund_Status_w |  -3.688263   1.946652    -1.89   0.058     -7.50363    .1271043
      FUNDING_RATIO_w |   -.548908   .3974585    -1.38   0.167    -1.327912    .2300963
         Platn_Size_w |    .029275   .0661141     0.44   0.658    -.1003064    .1588563
        CSR_Committee |   .1171023    .126457     0.93   0.354    -.1307489    .3649535
SustainabilityScore_w |   .0023581   .0034981     0.67   0.500     -.004498    .0092143
                      |
                 year |
                2007  |  -.1893796   .4824649    -0.39   0.695    -1.134993    .7562342
                2008  |   .3703923   .4019114     0.92   0.357    -.4173396    1.158124
                2009  |   .5153293   .3911218     1.32   0.188    -.2512553    1.281914
                2010  |   .3656944   .4108336     0.89   0.373    -.4395247    1.170914
                2011  |   .0708561    .428661     0.17   0.869    -.7693042    .9110163
                2012  |   .3657888   .4044102     0.90   0.366    -.4268405    1.158418
                2013  |   .2803688   .4104458     0.68   0.495    -.5240901    1.084828
                2014  |    .360477   .4095485     0.88   0.379    -.4422233    1.163177
                2015  |   .3537351   .4137397     0.85   0.393    -.4571797     1.16465
                2016  |   .0784589    .423008     0.19   0.853    -.7506216    .9075393
                2017  |   .1262666   .4213481     0.30   0.764    -.6995605    .9520937
                2018  |   .3577145   .4153034     0.86   0.389    -.4562652    1.171694
                2019  |  -.0183752   .4474583    -0.04   0.967    -.8953773    .8586269
                2020  |   .2577183   .4336884     0.59   0.552    -.5922953    1.107732
                2021  |  -.1472962   .4668719    -0.32   0.752    -1.062348    .7677558
                2022  |   .1538622    .541226     0.28   0.776    -.9069212    1.214646
                      |
                ff_12 |
                   2  |   .1149295   .3525047     0.33   0.744     -.575967     .805826
                   3  |   .0547361   .2282032     0.24   0.810    -.3925339    .5020061
                   4  |   .0371616   .3826385     0.10   0.923     -.712796    .7871192
                   5  |  -.0179077   .2321963    -0.08   0.939    -.4730041    .4371887
                   6  |   .2384004    .231927     1.03   0.304    -.2161682     .692969
                   7  |   .6368554   .3566165     1.79   0.074       -.0621    1.335811
                   8  |   .0149633    .273617     0.05   0.956    -.5213161    .5512428
                   9  |   .6683979   .2549403     2.62   0.009     .1687241    1.168072
                  10  |   .1631866   .2537802     0.64   0.520    -.3342135    .6605867
                  11  |   .6306283    .234109     2.69   0.007     .1717832    1.089474
                  12  |   .1210401   .2556985     0.47   0.636    -.3801198       .6222
                      |
         csopresence1 |   1.244748   .4130107     3.01   0.003     .4352615    2.054234
                _cons |  -1.053993   .6796596    -1.55   0.121    -2.386101    .2781156
----------------------+----------------------------------------------------------------
csopresence1          |
       CSO_Percentage |   2.942302   .1429113    20.59   0.000     2.662201    3.222403
                _cons |  -1.364117   .0474742   -28.73   0.000    -1.457165   -1.271069
----------------------+----------------------------------------------------------------
              /athrho |   -.581801     .25471    -2.28   0.022    -1.081023   -.0825787
----------------------+----------------------------------------------------------------
                  rho |  -.5239732   .1847799                     -.7935783   -.0823915
---------------------------------------------------------------------------------------
Wald test of rho=0: chi2(1) = 5.21744                     Prob > chi2 = 0.0224

.

Tags: None

George Ford

Join Date: Aug 2014

Posts: 3337
#2

27 Feb 2025, 08:43

everything you've estimated is in the table. Do you mean present as in "present" in a paper?

Last edited by George Ford; 27 Feb 2025, 09:03.
Comment
hussein bataineh

Join Date: Apr 2023

Posts: 177
#3

27 Feb 2025, 09:02

Dear Professor,

Thank you for your response.

I am facing an issue where the reviewer has requested that I present the full first-stage regression, including all control variables. I am unsure of the best way to present it. Could you please advise me on how to approach this?
Comment
George Ford

Join Date: Aug 2014

Posts: 3337
#4

27 Feb 2025, 09:05

Just list both equations in the table. I predict you're going to get grief about the thinly specified csopresence1 model (and if you presented those results, that is already so).
Comment

hussein bataineh

Join Date: Apr 2023
Posts: 177

27 Feb 2025, 09:29

when i try to run the first stage separately i did not get the same results for the results when i use biprobit for example
CSO_Percentage | 2.942302 CSO_Percentage | 4.095399

HTML Code:

. probit csopresence1 CSO_Percentage Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gender_Diversi
> ty_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee SustainabilityScore_w i.year i.ff_12 if jon==0   , robust

Iteration 0:  Log pseudolikelihood = -1925.9727  
Iteration 1:  Log pseudolikelihood = -1466.0423  
Iteration 2:  Log pseudolikelihood = -1455.3724  
Iteration 3:  Log pseudolikelihood = -1455.3228  
Iteration 4:  Log pseudolikelihood = -1455.3228  

Probit regression                                       Number of obs =  3,167
                                                        Wald chi2(42) = 630.77
                                                        Prob > chi2   = 0.0000
Log pseudolikelihood = -1455.3228                       Pseudo R2     = 0.2444

---------------------------------------------------------------------------------------
                      |               Robust
         csopresence1 | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
----------------------+----------------------------------------------------------------
       CSO_Percentage |   4.095399    .530269     7.72   0.000      3.05609    5.134707
          Firm_Size_w |  -.0826777   .0436644    -1.89   0.058    -.1682584     .002903
                ROA_w |  -.2753003   .7784768    -0.35   0.724    -1.801087    1.250486
           Leverage_w |   .6292146   .2451732     2.57   0.010      .148684    1.109745
   Market_book_four_w |   .0061946   .0040713     1.52   0.128     -.001785    .0141741
    Non_pension_CFO_w |   -.180476   .9790716    -0.18   0.854    -2.099421    1.738469
            STD_CFO_w |   6.269256   1.707672     3.67   0.000     2.922281    9.616232
 Board_Independence_w |   .0027636   .0040084     0.69   0.491    -.0050928      .01062
          BoardSize_w |   .0381123   .0150663     2.53   0.011      .008583    .0676417
   Gender_Diversity_w |   .0110899   .0034783     3.19   0.001     .0042726    .0179072
        Fund_Status_w |   2.930541   1.128549     2.60   0.009     .7186252    5.142457
      FUNDING_RATIO_w |   .1110752   .2048478     0.54   0.588     -.290419    .5125694
         Platn_Size_w |   .2188181   .0348702     6.28   0.000     .1504738    .2871624
        CSR_Committee |   .3716688   .0805491     4.61   0.000     .2137954    .5295421
SustainabilityScore_w |   .0111112   .0019687     5.64   0.000     .0072525    .0149698
                      |
                 year |
                2007  |   .0527945   .2813542     0.19   0.851    -.4986496    .6042387
                2008  |   .2150963   .2771113     0.78   0.438     -.328032    .7582245
                2009  |   .0180816   .2786012     0.06   0.948    -.5279668    .5641299
                2010  |  -.0770438   .2759185    -0.28   0.780    -.6178341    .4637465
                2011  |  -.0805264   .2798334    -0.29   0.774    -.6289898     .467937
                2012  |  -.0862275   .2799829    -0.31   0.758    -.6349839    .4625288
                2013  |  -.1092091   .2821516    -0.39   0.699    -.6622161    .4437978
                2014  |  -.1786789    .287689    -0.62   0.535    -.7425389    .3851811
                2015  |  -.2266117   .2957641    -0.77   0.444    -.8062988    .3530753
                2016  |    -.22535   .3037069    -0.74   0.458    -.8206046    .3699046
                2017  |  -.3998856   .3139916    -1.27   0.203    -1.015298    .2155266
                2018  |  -.5312557   .3323835    -1.60   0.110    -1.182715     .120204
                2019  |   -.739034   .3500845    -2.11   0.035    -1.425187   -.0528809
                2020  |  -.9364127   .3728389    -2.51   0.012    -1.667163   -.2056619
                2021  |  -1.118816   .3876189    -2.89   0.004    -1.878535   -.3590972
                2022  |  -.9797391   .4289539    -2.28   0.022    -1.820473   -.1390049
                      |
                ff_12 |
                   2  |  -.2994916   .2134947    -1.40   0.161    -.7179336    .1189504
                   3  |   .1324175   .1628053     0.81   0.416     -.186675      .45151
                   4  |   .3098926    .216236     1.43   0.152    -.1139221    .7337073
                   5  |  -.0127904   .1452137    -0.09   0.930    -.2974039    .2718232
                   6  |   .5177288   .1738367     2.98   0.003     .1770152    .8584425
                   7  |   .5840342   .2215961     2.64   0.008     .1497139    1.018354
                   8  |   .1944407   .1762285     1.10   0.270    -.1509609    .5398422
                   9  |   .2814484    .187301     1.50   0.133    -.0856548    .6485516
                  10  |   .5520697   .1763659     3.13   0.002     .2063989    .8977405
                  11  |   .3456728   .1781982     1.94   0.052    -.0035893    .6949349
                  12  |   .5301091   .1906951     2.78   0.005     .1563536    .9038645
                      |
                _cons |  -4.688069    .541573    -8.66   0.000    -5.749532   -3.626605
---------------------------------------------------------------------------------------

Comment

George Ford

Join Date: Aug 2014

Posts: 3337
#6

27 Feb 2025, 09:40

biprobit does not "fill in" the exogenous variables like ivreg and others. You have to do that.
Comment
hussein bataineh

Join Date: Apr 2023

Posts: 177
#7

27 Feb 2025, 11:36

Thanks . i understand this . please do you have any idea on how to present the full first-stage regression, including all control variables i tried different way but i did not get similar value that is given
csopresence1 | CSO_Percentage | 2.942302
Comment
George Ford

Join Date: Aug 2014

Posts: 3337
#8

27 Feb 2025, 12:04

Most obviously, include all the Xs in both but the IV only in csopresence1 within biprobit
Comment

hussein bataineh

Join Date: Apr 2023
Posts: 177

27 Feb 2025, 14:12

please professor i did this can you check if i have a problem please

HTML Code:

. biprobit (hard_final_Exact_new = csopresence1 Firm_Size_w ROA_w Leverage_w Market_book_four_w Non_pension_CFO_w STD_CFO_w Board_Independence_w BoardSize_w Gen
> der_Diversity_w Fund_Status_w FUNDING_RATIO_w Platn_Size_w CSR_Committee SustainabilityScore_w i.year i.ff_12) (csopresence1 = CSO_Percentage 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 SustainabilityScore_w i.year i.ff_12), vce(cluster id)

Fitting comparison equation 1:

Iteration 0:  Log pseudolikelihood = -358.54602  
Iteration 1:  Log pseudolikelihood =   -329.264  
Iteration 2:  Log pseudolikelihood = -326.78258  
Iteration 3:  Log pseudolikelihood = -326.74249  
Iteration 4:  Log pseudolikelihood = -326.74237  
Iteration 5:  Log pseudolikelihood = -326.74237  

Fitting comparison equation 2:

Iteration 0:  Log pseudolikelihood = -1925.9727  
Iteration 1:  Log pseudolikelihood = -1466.0423  
Iteration 2:  Log pseudolikelihood = -1455.3724  
Iteration 3:  Log pseudolikelihood = -1455.3228  
Iteration 4:  Log pseudolikelihood = -1455.3228  

Comparison:   Log pseudolikelihood = -1782.0652

Fitting full model:

Iteration 0:  Log pseudolikelihood = -1782.0652  
Iteration 1:  Log pseudolikelihood = -1782.0645  
Iteration 2:  Log pseudolikelihood = -1782.0645  

Seemingly unrelated bivariate probit                    Number of obs =  3,167
                                                        Wald chi2(84) = 415.43
Log pseudolikelihood = -1782.0645                       Prob > chi2   = 0.0000

                                            (Std. err. adjusted for 270 clusters in id)
---------------------------------------------------------------------------------------
                      |               Robust
                      | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
----------------------+----------------------------------------------------------------
hard_final_Exact_new  |
         csopresence1 |   .3152266   .3339991     0.94   0.345    -.3393997    .9698529
          Firm_Size_w |  -.1467564    .080254    -1.83   0.067    -.3040512    .0105385
                ROA_w |   2.193484   1.398075     1.57   0.117    -.5466925     4.93366
           Leverage_w |  -.7439438   .4339545    -1.71   0.086    -1.594479    .1065914
   Market_book_four_w |   -.000411   .0091251    -0.05   0.964    -.0182958    .0174739
    Non_pension_CFO_w |  -4.842973    1.87981    -2.58   0.010    -8.527333   -1.158612
            STD_CFO_w |   1.086406   3.068045     0.35   0.723    -4.926852    7.099664
 Board_Independence_w |   .0037052   .0058595     0.63   0.527    -.0077793    .0151896
          BoardSize_w |  -.0204817    .026524    -0.77   0.440    -.0724678    .0315044
   Gender_Diversity_w |  -.0044648   .0069074    -0.65   0.518    -.0180031    .0090734
        Fund_Status_w |  -3.918271    2.01911    -1.94   0.052    -7.875653    .0391116
      FUNDING_RATIO_w |  -.5748567   .4266943    -1.35   0.178    -1.411162    .2614488
         Platn_Size_w |   .0336964   .0685723     0.49   0.623    -.1007028    .1680957
        CSR_Committee |   .1018301   .1405885     0.72   0.469    -.1737184    .3773786
SustainabilityScore_w |   .0028798   .0035769     0.81   0.421    -.0041307    .0098903
                      |
                 year |
                2007  |  -.2119614   .4923392    -0.43   0.667    -1.176929    .7530056
                2008  |   .3450573   .4108714     0.84   0.401    -.4602359     1.15035
                2009  |   .5394935   .4018606     1.34   0.179    -.2481388    1.327126
                2010  |   .3875197   .4206317     0.92   0.357    -.4369034    1.211943
                2011  |   .0836426   .4430605     0.19   0.850      -.78474    .9520253
                2012  |   .4401625   .4144162     1.06   0.288    -.3720783    1.252403
                2013  |   .3433902   .4236944     0.81   0.418    -.4870355    1.173816
                2014  |   .4480432   .4219323     1.06   0.288    -.3789288    1.275015
                2015  |   .4820207   .4280139     1.13   0.260    -.3568711    1.320913
                2016  |   .2146203    .442422     0.49   0.628    -.6525109    1.081752
                2017  |   .2984009   .4414414     0.68   0.499    -.5668083     1.16361
                2018  |   .6068453   .4356134     1.39   0.164    -.2469413    1.460632
                2019  |   .2566849   .4647392     0.55   0.581    -.6541871    1.167557
                2020  |   .6151624   .4508715     1.36   0.172    -.2685295    1.498854
                2021  |   .2196148   .4955982     0.44   0.658    -.7517398    1.190969
                2022  |   .5431234   .5861571     0.93   0.354    -.6057234     1.69197
                      |
                ff_12 |
                   2  |    .036112   .4055824     0.09   0.929    -.7588149    .8310389
                   3  |  -.1680803   .2319064    -0.72   0.469    -.6226084    .2864478
                   4  |  -.2041554   .4103835    -0.50   0.619    -1.008492    .6001815
                   5  |  -.1098819   .2537509    -0.43   0.665    -.6072245    .3874607
                   6  |   .0103067   .2427675     0.04   0.966     -.465509    .4861223
                   7  |   .4634633   .3939189     1.18   0.239    -.3086034     1.23553
                   8  |   -.247637   .2743804    -0.90   0.367    -.7854127    .2901387
                   9  |   .5313202   .2305514     2.30   0.021     .0794477    .9831927
                  10  |  -.0641802   .2617027    -0.25   0.806     -.577108    .4487476
                  11  |   .4615996   .2428327     1.90   0.057    -.0143437     .937543
                  12  |  -.1524394   .2522312    -0.60   0.546    -.6468035    .3419247
                      |
                _cons |  -.7211021   .7882861    -0.91   0.360    -2.266114    .8239102
----------------------+----------------------------------------------------------------
csopresence1          |
       CSO_Percentage |   4.097164   .7725676     5.30   0.000     2.582959    5.611369
          Firm_Size_w |  -.0826413    .107395    -0.77   0.442    -.2931316     .127849
                ROA_w |  -.2759582   1.305821    -0.21   0.833     -2.83532    2.283404
           Leverage_w |   .6291451   .5211223     1.21   0.227    -.3922358    1.650526
   Market_book_four_w |   .0061947   .0057151     1.08   0.278    -.0050068    .0173961
    Non_pension_CFO_w |  -.1793599   1.622919    -0.11   0.912    -3.360223    3.001504
            STD_CFO_w |   6.267636   3.062809     2.05   0.041     .2646393    12.27063
 Board_Independence_w |   .0027626   .0077701     0.36   0.722    -.0124666    .0179918
          BoardSize_w |   .0381073   .0315113     1.21   0.227    -.0236538    .0998684
   Gender_Diversity_w |   .0110848   .0066307     1.67   0.095     -.001911    .0240807
        Fund_Status_w |   2.929538   2.583395     1.13   0.257    -2.133822    7.992899
      FUNDING_RATIO_w |   .1110227   .4702417     0.24   0.813    -.8106342     1.03268
         Platn_Size_w |   .2187839   .0775289     2.82   0.005       .06683    .3707377
        CSR_Committee |   .3717636   .1438248     2.58   0.010     .0898721    .6536551
SustainabilityScore_w |   .0111086   .0044349     2.50   0.012     .0024164    .0198008
                      |
                 year |
                2007  |   .0528134   .2516107     0.21   0.834    -.4403345    .5459612
                2008  |   .2152776    .276712     0.78   0.437     -.327068    .7576232
                2009  |   .0179564   .2871953     0.06   0.950    -.5449361    .5808489
                2010  |  -.0770191   .2857521    -0.27   0.788     -.637083    .4830448
                2011  |  -.0805339   .2968668    -0.27   0.786    -.6623822    .5013144
                2012  |  -.0864767   .3064472    -0.28   0.778    -.6871021    .5141487
                2013  |  -.1092725   .3069064    -0.36   0.722     -.710798     .492253
                2014  |  -.1788678   .3164986    -0.57   0.572    -.7991936     .441458
                2015  |  -.2269573   .3392105    -0.67   0.503    -.8917976     .437883
                2016  |  -.2255846    .366468    -0.62   0.538    -.9438488    .4926795
                2017  |  -.4001706   .3804211    -1.05   0.293    -1.145782    .3454412
                2018  |  -.5316931   .4177477    -1.27   0.203    -1.350464    .2870774
                2019  |  -.7396007   .4600043    -1.61   0.108    -1.641193    .1619912
                2020  |  -.9370515   .5014094    -1.87   0.062    -1.919796    .0456928
                2021  |   -1.11947   .5177187    -2.16   0.031     -2.13418   -.1047595
                2022  |  -.9805104   .5497434    -1.78   0.074    -2.057988    .0969669
                      |
                ff_12 |
                   2  |  -.2990782   .4377046    -0.68   0.494    -1.156963    .5588071
                   3  |   .1328814   .3484097     0.38   0.703    -.5499892    .8157519
                   4  |   .3102424   .4843799     0.64   0.522    -.6391249     1.25961
                   5  |  -.0126701   .3381138    -0.04   0.970    -.6753611    .6500208
                   6  |   .5181254   .3479638     1.49   0.136    -.1638712    1.200122
                   7  |   .5844582   .5153666     1.13   0.257    -.4256417    1.594558
                   8  |   .1949192   .3615213     0.54   0.590    -.5136495     .903488
                   9  |   .2816968   .3669591     0.77   0.443    -.4375299    1.000923
                  10  |   .5524157   .3591533     1.54   0.124    -.1515118    1.256343
                  11  |   .3459657   .3684671     0.94   0.348    -.3762166    1.068148
                  12  |   .5305484    .375262     1.41   0.157    -.2049517    1.266049
                      |
                _cons |  -4.688385   1.110861    -4.22   0.000    -6.865633   -2.511137
----------------------+----------------------------------------------------------------
              /athrho |  -.0085882   .1921508    -0.04   0.964    -.3851969    .3680204
----------------------+----------------------------------------------------------------
                  rho |   -.008588   .1921366                     -.3672121     .352259
---------------------------------------------------------------------------------------
Wald test of rho=0: chi2(1) = .001998                     Prob > chi2 = 0.9644

Comment

George Ford

Join Date: Aug 2014

Posts: 3337
#10

27 Feb 2025, 15:22

That's a sensible way to do it.

Note that /atrho and the Wald test are nowhere near significant (a test of exogeneity), so you could just estimate the first equation and ignore endogeneity.
Comment
hussein bataineh

Join Date: Apr 2023

Posts: 177
#11

28 Feb 2025, 12:06

Thank you, Professor, for all your support. I would like to ask for your advice—unfortunately, the biprobit model does not yield significant results, similar to my primary regression. Do you think using cfprobit would be a possible approach?
Comment
George Ford

Join Date: Aug 2014

Posts: 3337
#12

28 Feb 2025, 15:26

might as well try it
Comment
George Ford

Join Date: Aug 2014

Posts: 3337
#13

28 Feb 2025, 16:03

It will likely tell you the same -- csopresence1 is not endogenous. Just run it straight with probit.
Comment
hussein bataineh

Join Date: Apr 2023

Posts: 177
#14

28 Feb 2025, 16:33

Thank you for your feedback. Based on the results, the Wald test for ρ=0\rho = 0ρ=0 and the estimate for /athrho/athrho/athrho are not significant, indicating that the error terms of the two equations are uncorrelated. This suggests that csopresence1 is not endogenous in the hard_final_Exact_new equation.

Given this, I understand that a standard probit model would be an appropriate estimation method, as there is no statistical evidence necessitating the use of a bivariate probit to account for endogeneity. Please let me know if you have any further recommendations on this approach.
Comment
George Ford

Join Date: Aug 2014

Posts: 3337
#15

01 Mar 2025, 07:44

your can mention that your instrument (CSO_percentage) has an F equivalent of 28.1. While not precise, some people use the F>10 rule in non-linear IV models.
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How to present the first stage in 2sls when using ( biprobit )

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