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  • different in the number of observation in simple probit model and 2 SLS

    im using simple probit model in my study , and use 2 SLS for robustness but i noticed that simple probit model give me lower number of observation as compared to 2sls , im using similar variable in both probit and 2sls, where is the problem and is there a way we can have similar number of observation in both simple probit model and 2 SLS
    HTML Code:
    
    
    .  probit   hard_final_Exact_new  csopresence1 Firm_Size_w   ROA_four_w     ACTUAL_RETURN_w DCAPEX_w TAX_rate_w  KZ_one_w    DDIVi_w   Leverage_w   Book_Market_s_w UNION  dividends_w  FREE_CASH_FLOW_w CASH_FLOW_VOLATILITY_w   G
    > overnance_Score_w   Fund_Status_w  FUNDING_RATIO_w  Platn_Size_w  Pension_contrib_four_w   CSR_Committee  SustainabilityScore_w   i.year    i.SIC_WRDS_2  ,  robust cluster (id)
    
    note: 2005.year != 0 predicts failure perfectly;
          2005.year omitted and 185 obs not used.
    
    note: 2006.year != 0 predicts failure perfectly;
          2006.year omitted and 187 obs not used.
    
    note: 14.SIC_WRDS_2 != 0 predicts failure perfectly;
          14.SIC_WRDS_2 omitted and 34 obs not used.
    
    note: 21.SIC_WRDS_2 != 0 predicts failure perfectly;
          21.SIC_WRDS_2 omitted and 30 obs not used.
    
    note: 27.SIC_WRDS_2 != 0 predicts failure perfectly;
          27.SIC_WRDS_2 omitted and 10 obs not used.
    
    note: 34.SIC_WRDS_2 != 0 predicts failure perfectly;
          34.SIC_WRDS_2 omitted and 74 obs not used.
    
    note: 40.SIC_WRDS_2 != 0 predicts failure perfectly;
          40.SIC_WRDS_2 omitted and 47 obs not used.
    
    note: 42.SIC_WRDS_2 != 0 predicts failure perfectly;
          42.SIC_WRDS_2 omitted and 16 obs not used.
    
    note: 53.SIC_WRDS_2 != 0 predicts failure perfectly;
          53.SIC_WRDS_2 omitted and 16 obs not used.
    
    note: 56.SIC_WRDS_2 != 0 predicts failure perfectly;
          56.SIC_WRDS_2 omitted and 15 obs not used.
    
    note: 58.SIC_WRDS_2 != 0 predicts failure perfectly;
          58.SIC_WRDS_2 omitted and 22 obs not used.
    
    note: 59.SIC_WRDS_2 != 0 predicts failure perfectly;
          59.SIC_WRDS_2 omitted and 7 obs not used.
    
    note: 70.SIC_WRDS_2 != 0 predicts failure perfectly;
          70.SIC_WRDS_2 omitted and 1 obs not used.
    
    note: 72.SIC_WRDS_2 != 0 predicts failure perfectly;
          72.SIC_WRDS_2 omitted and 4 obs not used.
    
    note: 87.SIC_WRDS_2 != 0 predicts failure perfectly;
          87.SIC_WRDS_2 omitted and 21 obs not used.
    
    note: 99.SIC_WRDS_2 != 0 predicts failure perfectly;
          99.SIC_WRDS_2 omitted and 23 obs not used.
    
    Iteration 0:  Log pseudolikelihood =  -337.5774  
    Iteration 1:  Log pseudolikelihood = -297.80791  
    Iteration 2:  Log pseudolikelihood =  -292.6912  
    Iteration 3:  Log pseudolikelihood = -292.60433  
    Iteration 4:  Log pseudolikelihood = -292.60431  
    
    Probit regression                                       Number of obs =  2,644
                                                            Wald chi2(57) =      .
                                                            Prob > chi2   =      .
    Log pseudolikelihood = -292.60431                       Pseudo R2     = 0.1332
    
                                                 (Std. err. adjusted for 237 clusters in id)
    ----------------------------------------------------------------------------------------
                           |               Robust
      hard_final_Exact_new | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
    -----------------------+----------------------------------------------------------------
              csopresence1 |    .245147   .1331708     1.84   0.066     -.015863    .5061569
               Firm_Size_w |  -.1941079   .1072464    -1.81   0.070     -.404307    .0160911
                ROA_four_w |  -10.58928   3.778324    -2.80   0.005    -17.99466   -3.183905
           ACTUAL_RETURN_w |   .4034757   .6440019     0.63   0.531    -.8587448    1.665696
                  DCAPEX_w |   2.002871   5.252902     0.38   0.703    -8.292629    12.29837
                TAX_rate_w |  -.1749159   .2404614    -0.73   0.467    -.6462116    .2963798
                  KZ_one_w |  -.1907202   .1732844    -1.10   0.271    -.5303514    .1489109
                   DDIVi_w |   60069.89   56149.84     1.07   0.285    -49981.78    170121.5
                Leverage_w |   .3842207   .6674419     0.58   0.565    -.9239413    1.692383
           Book_Market_s_w |  -.1723398    .266929    -0.65   0.519    -.6955109    .3508314
                     UNION |   .2296813   .3402251     0.68   0.500    -.4371477    .8965103
               dividends_w |  -5.172418   8.528672    -0.61   0.544    -21.88831    11.54347
          FREE_CASH_FLOW_w |   9.642757   3.886048     2.48   0.013     2.026243    17.25927
    CASH_FLOW_VOLATILITY_w |   -1.58963   3.036793    -0.52   0.601    -7.541634    4.362375
        Governance_Score_w |   .0061239   .0030816     1.99   0.047     .0000841    .0121637
             Fund_Status_w |  -4.486872   2.270805    -1.98   0.048    -8.937569   -.0361752
           FUNDING_RATIO_w |  -.5698927    .497172    -1.15   0.252    -1.544332    .4045464
              Platn_Size_w |   .0982426   .0861868     1.14   0.254    -.0706804    .2671656
    Pension_contrib_four_w |  -34.27454   9.654765    -3.55   0.000    -53.19753   -15.35155
             CSR_Committee |   .0040745   .1523626     0.03   0.979    -.2945508    .3026998
     SustainabilityScore_w |   .0056061    .004342     1.29   0.197    -.0029041    .0141163
                           |
                      year |
                     2005  |          0  (empty)
                     2006  |          0  (empty)
                     2007  |   .0981057    .518615     0.19   0.850     -.918361    1.114572
                     2008  |   .6003759   .5297405     1.13   0.257    -.4378963    1.638648
                     2009  |   .7712078   .4796599     1.61   0.108    -.1689083    1.711324
                     2010  |   .5279603   .4875362     1.08   0.279    -.4275931    1.483514
                     2011  |   .3039659   .5128367     0.59   0.553    -.7011756    1.309107
                     2012  |   .5377841   .4906285     1.10   0.273    -.4238301    1.499398
                     2013  |    .489606   .4928414     0.99   0.320    -.4763455    1.455557
                     2014  |   .5007029   .4941323     1.01   0.311    -.4677786    1.469184
                     2015  |   .6566197   .5030296     1.31   0.192    -.3293002     1.64254
                     2016  |   .2306135   .5077614     0.45   0.650    -.7645805    1.225808
                     2017  |   .1866728   .5247172     0.36   0.722     -.841754      1.2151
                     2018  |   .7011734   .5147613     1.36   0.173    -.3077402    1.710087
                     2019  |   .1755237   .5298538     0.33   0.740    -.8629706    1.214018
                     2020  |   .5185666   .5260135     0.99   0.324    -.5124008    1.549534
                     2021  |   .0585739   .5433806     0.11   0.914    -1.006432     1.12358
                     2022  |    .608939   .6708943     0.91   0.364    -.7059897    1.923868
                           |
                SIC_WRDS_2 |
                       13  |  -.2534915   .5557995    -0.46   0.648    -1.342839    .8358555
                       14  |          0  (empty)
                       20  |  -1.011071   .5092042    -1.99   0.047    -2.009093   -.0130493
                       21  |          0  (empty)
                       23  |   -.531122   .5353144    -0.99   0.321    -1.580319     .518075
                       26  |    -1.1323   .5950166    -1.90   0.057    -2.298511     .033911
                       27  |          0  (empty)
                       28  |  -1.073077   .4702449    -2.28   0.022     -1.99474   -.1514135
                       29  |  -.4664316   .4577622    -1.02   0.308    -1.363629    .4307657
                       34  |          0  (empty)
                       35  |  -1.206367   .5181649    -2.33   0.020    -2.221951   -.1907821
                       36  |  -1.043549   .4478865    -2.33   0.020    -1.921391   -.1657079
                       37  |  -.9559336   .4690026    -2.04   0.042    -1.875162   -.0367054
                       38  |  -.8042331   .3636136    -2.21   0.027    -1.516903   -.0915637
                       39  |   .9773447   .3434948     2.85   0.004     .3041073    1.650582
                       40  |          0  (empty)
                       42  |          0  (empty)
                       45  |  -.3590596   .4311532    -0.83   0.405    -1.204104    .4859851
                       48  |  -.5363866   .5469089    -0.98   0.327    -1.608308    .5355351
                       49  |   -1.09889   .4560841    -2.41   0.016    -1.992798   -.2049815
                       50  |   .0804174   .4649994     0.17   0.863    -.8309646    .9917994
                       51  |   .4085554   .3061336     1.33   0.182    -.1914555    1.008566
                       53  |          0  (empty)
                       54  |   .0898594   .2167635     0.41   0.678    -.3349893    .5147081
                       55  |   1.379211   .3314835     4.16   0.000     .7295153    2.028907
                       56  |          0  (empty)
                       58  |          0  (empty)
                       59  |          0  (empty)
                       60  |  -.3744984   .4478895    -0.84   0.403    -1.252346    .5033489
                       61  |   .0536955   .6961353     0.08   0.939    -1.310705    1.418096
                       62  |  -.0241014   .5053409    -0.05   0.962    -1.014551    .9663485
                       63  |  -.4153976   .4293481    -0.97   0.333    -1.256904    .4261092
                       64  |  -.2902573   .4808914    -0.60   0.546    -1.232787    .6522724
                       70  |          0  (empty)
                       72  |          0  (empty)
                       73  |  -.8807843   .3951758    -2.23   0.026    -1.655315   -.1062541
                       80  |  -.1506552   .5541873    -0.27   0.786    -1.236842     .935532
                       87  |          0  (empty)
                       99  |          0  (empty)
                           |
                     _cons |  -.2584988   1.021271    -0.25   0.800    -2.260153    1.743156
    ----------------------------------------------------------------------------------------
    
    .
    end of do-file
    
    . do "C:\Users\lenovo\AppData\Local\Temp\STD1fa0_000000.tmp"
    
    . * drop if industry identifier is missing
    . drop if SIC_WRDS_2 == .
    (411 observations deleted)
    
    .
    .
    . * Count the number of firms in each industry in each year where the cso presence variable is equal to 1
    . capture bys SIC_WRDS_2 year : egen Instrumental_based_on_CSO_Count = count(csopresence1 / (csopresence1==1))
    
    .
    . * Count the total number of firms in each industry and each year where cso is not missing
    .  bys SIC_WRDS_2 year : egen total_firms_industry_year = count(csopresence1)
    
    .
    . * The percentage of firms in each industry in each year where the cso presence variable is equal to 1
    . gen CSO_Percentage = Instrumental_based_on_CSO_Count / total_firms_industry_year
    (2,925 missing values generated)
    
    .
    end of do-file
    
    . do "C:\Users\lenovo\AppData\Local\Temp\STD1fa0_000000.tmp"
    
    .
    . ssc install  ivreg2
    checking ivreg2 consistency and verifying not already installed...
    all files already exist and are up to date.
    
    .
    . ivreg2  hard_final_Exact_new   Firm_Size_w   ROA_four_w     ACTUAL_RETURN_w DCAPEX_w TAX_rate_w  KZ_one_w    DDIVi_w   Leverage_w   Book_Market_s_w UNION  dividends_w  FREE_CASH_FLOW_w  CASH_FLOW_VOLATILITY_w  Governance_Scor
    > e_w   Fund_Status_w  FUNDING_RATIO_w  Platn_Size_w  Pension_contrib_four_w FREE_CASH_FLOW_w CASH_FLOW_VOLATILITY_w   CSR_Committee  SustainabilityScore_w    i.year    i.SIC_WRDS_2 (csopresence1 = CSO_Percentage )   , partial
    > (i.SIC_WRDS_2  i.year CSR_Committee   )   first endog(csopresence1) robust cluster (id)
    Warning - duplicate variables detected
    Duplicates:         FREE_CASH_FLOW_w CASH_FLOW_VOLATILITY_w
    
    First-stage regressions
    -----------------------
    
    
    First-stage regression of csopresence1:
    
    Statistics robust to heteroskedasticity and clustering on id
    Number of obs =                   3336
    Number of clusters (id) =          263
    ----------------------------------------------------------------------------------------
                           |               Robust
              csopresence1 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
    -----------------------+----------------------------------------------------------------
            CSO_Percentage |   1.097992   .0907797    12.10   0.000     .9200013    1.275983
               Firm_Size_w |   .0121108     .02667     0.45   0.650    -.0401809    .0644024
                ROA_four_w |  -.1025899   .7043419    -0.15   0.884    -1.483588    1.278408
           ACTUAL_RETURN_w |  -.0670515   .0799868    -0.84   0.402    -.2238811    .0897782
                  DCAPEX_w |   .8024182   .5033664     1.59   0.111    -.1845285    1.789365
                TAX_rate_w |   .0011333   .0314563     0.04   0.971    -.0605428    .0628094
                  KZ_one_w |   .0479463   .0252224     1.90   0.057    -.0015071    .0973997
                   DDIVi_w |  -4128.335   7197.016    -0.57   0.566    -18239.47    9982.802
                Leverage_w |  -.2111824   .1469058    -1.44   0.151    -.4992196    .0768547
           Book_Market_s_w |  -.0231991   .0605911    -0.38   0.702    -.1419996    .0956014
                     UNION |  -.0992665   .1675468    -0.59   0.554    -.4277743    .2292413
               dividends_w |   1.089643   1.323025     0.82   0.410    -1.504403    3.683689
          FREE_CASH_FLOW_w |   .4497031   .6689588     0.67   0.501    -.8619195    1.761326
    CASH_FLOW_VOLATILITY_w |   1.150295   .8068628     1.43   0.154    -.4317149    2.732305
        Governance_Score_w |  -.0000811   .0006863    -0.12   0.906    -.0014268    .0012646
             Fund_Status_w |   .6693949   .6632205     1.01   0.313    -.6309766    1.969766
           FUNDING_RATIO_w |  -.0515603   .1082133    -0.48   0.634    -.2637333    .1606128
              Platn_Size_w |   .0495668   .0200231     2.48   0.013     .0103076     .088826
    Pension_contrib_four_w |   .1194941   1.410955     0.08   0.933    -2.646956    2.885944
     SustainabilityScore_w |    .001427   .0009573     1.49   0.136      -.00045     .003304
    ----------------------------------------------------------------------------------------
    
    --------------------
    
    Estimates efficient for homoskedasticity only
    Statistics robust to heteroskedasticity and clustering on id
    
    Number of clusters (id) =          263                Number of obs =     3336
                                                          F( 20,   262) =     1.70
                                                          Prob > F      =   0.0338
    Total (centered) SS     =  70.44989142                Centered R2   =  -0.0192
    Total (uncentered) SS   =  70.44989142                Uncentered R2 =  -0.0192
    Residual SS             =  71.79926397                Root MSE      =    .1467
    
    ----------------------------------------------------------------------------------------
                           |               Robust
      hard_final_Exact_new | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
    -----------------------+----------------------------------------------------------------
              csopresence1 |   .0801542   .0264878     3.03   0.002      .028239    .1320694
               Firm_Size_w |  -.0078716   .0055547    -1.42   0.156    -.0187586    .0030154
                ROA_four_w |  -.3641893   .1255164    -2.90   0.004     -.610197   -.1181817
           ACTUAL_RETURN_w |   .0085612   .0451347     0.19   0.850    -.0799012    .0970235
                  DCAPEX_w |   .0200928   .1687929     0.12   0.905    -.3107352    .3509209
                TAX_rate_w |  -.0069881   .0133136    -0.52   0.600    -.0330823    .0191061
                  KZ_one_w |  -.0116238    .009556    -1.22   0.224    -.0303532    .0071057
                   DDIVi_w |   4011.996   4007.044     1.00   0.317    -3841.667    11865.66
                Leverage_w |   .0193079   .0389954     0.50   0.621    -.0571216    .0957374
           Book_Market_s_w |  -.0119774   .0154124    -0.78   0.437    -.0421851    .0182303
                     UNION |   .0093873   .0289523     0.32   0.746    -.0473582    .0661328
               dividends_w |  -.2672219   .4100998    -0.65   0.515    -1.071003    .5365589
          FREE_CASH_FLOW_w |   .2570271   .1226137     2.10   0.036     .0167086    .4973455
    CASH_FLOW_VOLATILITY_w |  -.0511036   .1569072    -0.33   0.745    -.3586361    .2564289
        Governance_Score_w |   .0002583   .0001433     1.80   0.071    -.0000225    .0005392
             Fund_Status_w |  -.3053186   .1467278    -2.08   0.037    -.5928998   -.0177373
           FUNDING_RATIO_w |  -.0054256   .0238981    -0.23   0.820     -.052265    .0414138
              Platn_Size_w |   .0000947   .0041335     0.02   0.982    -.0080069    .0081963
    Pension_contrib_four_w |  -1.295574    .416823    -3.11   0.002    -2.112532   -.4786159
     SustainabilityScore_w |   .0000651   .0001901     0.34   0.732    -.0003074    .0004376
    ----------------------------------------------------------------------------------------
    
    
    .

  • #2
    between your command above and the probit results are a bunch of "notes"; here is a copy of the first one:
    note: 2005.year != 0 predicts failure perfectly;
    2005.year omitted and 185 obs not used.
    this means that you have a bunch of variables, or particular values for some categorical variables, that predict the outcome perfectly and Stata drops not only those values (variables) but also the associated observations (185 in the quoted note) - so, yes, you have fewer observations because you have a data issue; based on what you told us, I cannot offer further advice other than to gather more and better data

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