2SLS estimation (Warning: estimated covariance matrix of moment conditions not of full rank.)

[hussein bataineh]

Hi

please im using Ivreg2 to estimate for 2SLS , i control form year using I.year also i use fixed effect by controing i.id , Also i use robust

ivreg2 EQUITY FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR Gov_score Sustain_Perf Sust_Commit i.id i.year (CSO = Instrumental), first endog(CSO) robust

at the end of the estimation it appear for me (Warning: estimated covariance matrix of moment conditions not of full rank.)


When i remove robust at the end of the Ivreg2 , the warning sign disappear


ivreg2 EQUITY FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR Gov_score Sustain_Perf Sust_Commit i.id i.year (CSO = Instrumental), first endog(CSO)

Im not sure where is the problem

[hussein bataineh]

 ivreg2 EQUITY  FSIZE OP_CF SD_OCF TAX   BM LEV MA DPP RPP PSIZE   DR  Gov_score Sustain_Perf Sust_Commit i.id  i.year (CSO = Instrumental),  first endog(CSO) robust

First-stage regressions
-----------------------


First-stage regression of CSO:

Statistics robust to heteroskedasticity
Number of obs =                   4051
------------------------------------------------------------------------------
             |               Robust
         CSO | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
Instrumental |   .0156519   .0025078     6.24   0.000     .0107352    .0205686
       FSIZE |    .008078   .0195917     0.41   0.680    -.0303335    .0464895
       OP_CF |  -.0828493   .1582074    -0.52   0.601    -.3930308    .2273321
      SD_OCF |   1.446089   .3087004     4.68   0.000     .8408507    2.051327
         TAX |   .0273629   .0207264     1.32   0.187    -.0132732    .0679991
          BM |  -.0247828   .0320911    -0.77   0.440    -.0877006     .038135
         LEV |   .1534906   .0765899     2.00   0.045     .0033284    .3036528
          MA |  -.0171832    .039293    -0.44   0.662    -.0942211    .0598546
         DPP |  -.0248049   .0594671    -0.42   0.677    -.1413962    .0917863
         RPP |  -.1013338   .0870105    -1.16   0.244    -.2719265     .069259
       PSIZE |   .0500369   .0181779     2.75   0.006     .0143974    .0856764
          DR |  -.0142629   .0173808    -0.82   0.412    -.0483397    .0198139
   Gov_score |   .0003102   .0003373     0.92   0.358    -.0003512    .0009715
Sustain_Perf |   .0011279   .0005127     2.20   0.028     .0001227    .0021331
 Sust_Commit |   .0079999   .0161639     0.49   0.621    -.0236909    .0396908
             |
          id |
          3  |   .0768793   .0915472     0.84   0.401    -.1026081    .2563667
          6  |   .2510733   .2196025     1.14   0.253    -.1794794    .6816259
          8  |   .2230446   .0895023     2.49   0.013     .0475664    .3985229
         10  |   .2780777   .0483471     5.75   0.000     .1832884     .372867
         12  |   .1085079   .0698411     1.55   0.120    -.0284226    .2454385
         13  |   .3877063    .093848     4.13   0.000     .2037079    .5717047
         14  |   .4627727   .1094081     4.23   0.000     .2482672    .6772782
         15  |    .835076    .088949     9.39   0.000     .6606826    1.009469
         16  |   .2096608   .0886564     2.36   0.018      .035841    .3834806
         17  |   .8564496   .0760335    11.26   0.000     .7073784    1.005521
         18  |  -.0750803   .0701352    -1.07   0.284    -.2125875    .0624269
         19  |   .2760072   .1006024     2.74   0.006     .0787662    .4732482
         20  |   .5141315   .1317224     3.90   0.000     .2558765    .7723865
         21  |   .5060567     .10118     5.00   0.000     .3076831    .7044303
         22  |   1.182202   .0703706    16.80   0.000     1.044233    1.320171
         24  |   .4078878   .1374321     2.97   0.003     .1384383    .6773373
         26  |  -.0875506   .0660016    -1.33   0.185    -.2169534    .0418523
         28  |   .0475152   .0647136     0.73   0.463    -.0793624    .1743927
         29  |   .1551686   .0917831     1.69   0.091    -.0247814    .3351186
         30  |   .3185186   .0959249     3.32   0.001     .1304483     .506589
         32  |   .1039583   .0671306     1.55   0.122     -.027658    .2355746
         35  |   .1501911    .087355     1.72   0.086     -.021077    .3214593
         40  |   .2972917   .1006934     2.95   0.003     .0998722    .4947113
         41  |   .3714094   .1728426     2.15   0.032     .0325342    .7102846
         42  |   .1620113   .0989343     1.64   0.102    -.0319594     .355982
         43  |  -.0279063   .0760293    -0.37   0.714    -.1769694    .1211569
         44  |   .5646908   .0945926     5.97   0.000     .3792325    .7501492
         45  |   .4045257   .1457874     2.77   0.006     .1186949    .6903565
         47  |   .0631079    .073268     0.86   0.389    -.0805414    .2067572
         50  |  -.0801545   .0909942    -0.88   0.378    -.2585579    .0982488
         51  |   .2019402   .0511246     3.95   0.000     .1017054     .302175
         52  |  -.0615122   .0662779    -0.93   0.353    -.1914565    .0684322
         53  |   .9020011   .1437957     6.27   0.000     .6200752    1.183927
         55  |  -.0200097     .09144    -0.22   0.827    -.1992869    .1592675
         56  |   .0360549   .0923699     0.39   0.696    -.1450455    .2171553
         57  |   .2298868   .0798969     2.88   0.004     .0732409    .3865326
         58  |  -.1481876   .0711771    -2.08   0.037    -.2877375   -.0086377
         61  |   .6765226   .0946321     7.15   0.000      .490987    .8620583
         62  |   .2721111    .087072     3.13   0.002     .1013977    .4428244
         63  |   .4976292   .0903594     5.51   0.000     .3204706    .6747878
         64  |   .4859941   .1073784     4.53   0.000      .275468    .6965202
         66  |  -.0395931   .0840909    -0.47   0.638    -.2044617    .1252756
         70  |  -.1959618   .0737214    -2.66   0.008       -.3405   -.0514236
 
             |
        year |
       2005  |   .0082807   .0325949     0.25   0.799    -.0556249    .0721863
       2006  |   .0192298   .0320162     0.60   0.548    -.0435413    .0820008
       2007  |   .0387829   .0325025     1.19   0.233    -.0249414    .1025072
       2008  |   .0400047   .0449738     0.89   0.374    -.0481709    .1281803
       2009  |   .0540236    .034973     1.54   0.122    -.0145444    .1225917
       2010  |   .0595171   .0372905     1.60   0.111    -.0135946    .1326287
       2011  |   .0674747   .0426429     1.58   0.114     -.016131    .1510804
       2012  |    .083411   .0504951     1.65   0.099    -.0155897    .1824117
       2013  |   .1160374   .0429438     2.70   0.007     .0318418     .200233
       2014  |   .0968027   .0515162     1.88   0.060    -.0042001    .1978054
       2015  |   .1064947    .049516     2.15   0.032     .0094137    .2035758
       2016  |   .1348759   .0539288     2.50   0.012     .0291431    .2406087
       2017  |    .153104   .0594751     2.57   0.010      .036497     .269711
       2018  |   .1841829   .0566266     3.25   0.001     .0731607    .2952051
       2019  |   .2249801   .0674822     3.33   0.001     .0926745    .3572857
       2020  |    .234567   .0796006     2.95   0.003      .078502     .390632
       2021  |   .2408054   .0773085     3.11   0.002     .0892344    .3923764
       2022  |   .2706711   .0777777     3.48   0.001     .1181802    .4231621
             |
       _cons |  -.7063311   .1920645    -3.68   0.000    -1.082893   -.3297693
------------------------------------------------------------------------------
F test of excluded instruments:
  F(  1,  3730) =    38.95
  Prob > F      =   0.0000
Sanderson-Windmeijer multivariate F test of excluded instruments:
  F(  1,  3730) =    38.95
  Prob > F      =   0.0000



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,  3730)  P-val | SW Chi-sq(  1) P-val | SW F(  1,  3730)
CSO          |      38.95    0.0000 |       42.31   0.0000 |       38.95

NB: first-stage test statistics heteroskedasticity-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=41.78    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                      52.18
Kleibergen-Paap Wald rk F statistic                                38.95

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,3730)=      9.34     P-val=0.0023
Anderson-Rubin Wald test           Chi-sq(1)=     10.14     P-val=0.0014
Stock-Wright LM S statistic        Chi-sq(1)=         .     P-val=     .

NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity-robust

Number of observations               N  =       4051
Number of regressors                 K  =        321
Number of endogenous regressors      K1 =          1
Number of instruments                L  =        321
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =     4051
                                                      F(320,  3730) =   410.26
                                                      Prob > F      =   0.0000
Total (centered) SS     =  153.8218013                Centered R2   =   0.6665
Total (uncentered) SS   =  1071.865387                Uncentered R2 =   0.9521
Residual SS             =  51.30371339                Root MSE      =    .1125

------------------------------------------------------------------------------
             |               Robust
      EQUITY | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         CSO |  -.1729897   .0584959    -2.96   0.003    -.2876396   -.0583398
       FSIZE |   .0123795   .0080366     1.54   0.123    -.0033721     .028131
       OP_CF |     -.0683    .065158    -1.05   0.295    -.1960073    .0594074
      SD_OCF |  -.1461356   .1487631    -0.98   0.326    -.4377059    .1454348
         TAX |  -.0058738   .0077634    -0.76   0.449    -.0210899    .0093422
          BM |  -.0258302   .0120476    -2.14   0.032    -.0494431   -.0022173
         LEV |   -.020226   .0316568    -0.64   0.523    -.0822721    .0418201
          MA |   .0038532   .0145438     0.26   0.791    -.0246522    .0323585
         DPP |   .1396388   .0246513     5.66   0.000     .0913231    .1879546
         RPP |   .0998273   .0351349     2.84   0.004     .0309642    .1686904
       PSIZE |   .0209352   .0090069     2.32   0.020     .0032821    .0385884
          DR |   .0404173   .0071513     5.65   0.000      .026401    .0544337
   Gov_score |  -.0000358   .0001254    -0.29   0.775    -.0002816    .0002099
Sustain_Perf |   -.000039   .0002055    -0.19   0.850    -.0004418    .0003639
 Sust_Commit |  -.0079053   .0065138    -1.21   0.225    -.0206721    .0048615
             |
          id |
          3  |   -.196843   .0440745    -4.47   0.000    -.2832275   -.1104585
          6  |  -.2818958   .0703924    -4.00   0.000    -.4198623   -.1439292
          8  |  -.1530946   .0370148    -4.14   0.000    -.2256422   -.0805469
         10  |  -.0958093   .0346259    -2.77   0.006    -.1636748   -.0279439
         12  |  -.0715845    .050358    -1.42   0.155    -.1702843    .0271153
         13  |  -.1566972   .0515031    -3.04   0.002    -.2576414   -.0557529
         14  |  -.0983788   .0501605    -1.96   0.050    -.1966917    -.000066
         15  |   .0873498   .0690924     1.26   0.206    -.0480688    .2227685
         16  |  -.1577911    .042644    -3.70   0.000    -.2413718   -.0742103
         17  |  -.1926949   .0632552    -3.05   0.002    -.3166729    -.068717
         18  |  -.2842097   .0337847    -8.41   0.000    -.3504264    -.217993
         19  |  -.2289776   .0464038    -4.93   0.000    -.3199275   -.1380278
         20  |    -.27578   .0534121    -5.16   0.000    -.3804659   -.1710942
         21  |  -.3130877   .0490545    -6.38   0.000    -.4092326   -.2169427
         22  |    .158974   .0758572     2.10   0.036     .0102966    .3076515
         24  |  -.1280691   .0489432    -2.62   0.009     -.223996   -.0321423
         26  |  -.2706416   .0384196    -7.04   0.000    -.3459426   -.1953406
         28  |  -.5033943   .0452778   -11.12   0.000    -.5921372   -.4146513
         29  |  -.2097703   .0375714    -5.58   0.000     -.283409   -.1361317
         30  |  -.3230224   .0348629    -9.27   0.000    -.3913524   -.2546924
         32  |  -.1517933   .0331707    -4.58   0.000    -.2168067   -.0867798
         35  |  -.2780842   .0480705    -5.78   0.000    -.3723006   -.1838678
         40  |  -.3798279   .0493405    -7.70   0.000    -.4765335   -.2831223
         41  |  -.1239616   .0599064    -2.07   0.039    -.2413759   -.0065473
         42  |  -.2560138   .0408748    -6.26   0.000    -.3361269   -.1759008
         43  |  -.1209293   .0290472    -4.16   0.000    -.1778607   -.0639979
         44  |  -.0436356   .0541652    -0.81   0.420    -.1497974    .0625262
         45  |   -.249741    .043053    -5.80   0.000    -.3341234   -.1653586
         47  |   .0237943   .0339059     0.70   0.483      -.04266    .0902485
         50  |   -.541778    .060014    -9.03   0.000    -.6594032   -.4241528
         51  |   -.150783   .0442984    -3.40   0.001    -.2376062   -.0639598
         52  |  -.1356262   .0330178    -4.11   0.000      -.20034   -.0709124
         53  |  -.1439585   .0639517    -2.25   0.024    -.2693015   -.0186155
         55  |  -.4241971   .0417459   -10.16   0.000    -.5060176   -.3423766
         56  |  -.2505044    .043135    -5.81   0.000    -.3350474   -.1659613
         57  |  -.3619691   .0323835   -11.18   0.000    -.4254397   -.2984985
         58  |  -.1241552   .0265477    -4.68   0.000    -.1761878   -.0721226
         61  |  -.1885559   .0525321    -3.59   0.000     -.291517   -.0855948
         62  |   .1806477   .0518632     3.48   0.000     .0789976    .2822977
         63  |  -.0641431   .0580543    -1.10   0.269    -.1779275    .0496413
         64  |   -.738005    .060382   -12.22   0.000    -.8563515   -.6196585
         66  |   -.229681   .0357134    -6.43   0.000    -.2996779    -.159684
         70  |  -.2268429   .0377784    -6.00   0.000    -.3008872   -.1527985
 
             |
        year |
       2005  |    .001583   .0130419     0.12   0.903    -.0239788    .0271447
       2006  |  -.0101608   .0133865    -0.76   0.448    -.0363978    .0160762
       2007  |   -.038981   .0135934    -2.87   0.004    -.0656236   -.0123384
       2008  |  -.0813137   .0190981    -4.26   0.000    -.1187454   -.0438821
       2009  |  -.0907544   .0153258    -5.92   0.000    -.1207924   -.0607163
       2010  |  -.0699317   .0160638    -4.35   0.000    -.1014162   -.0384471
       2011  |  -.0766685   .0182318    -4.21   0.000    -.1124023   -.0409348
       2012  |  -.0652068    .021339    -3.06   0.002    -.1070304   -.0233832
       2013  |  -.0893286   .0197775    -4.52   0.000    -.1280917   -.0505655
       2014  |    -.08869   .0221876    -4.00   0.000    -.1321769   -.0452031
       2015  |  -.0976987    .022044    -4.43   0.000    -.1409042   -.0544932
       2016  |  -.0936859   .0249886    -3.75   0.000    -.1426626   -.0447092
       2017  |  -.1017087   .0274862    -3.70   0.000    -.1555806   -.0478368
       2018  |  -.1531187   .0276838    -5.53   0.000     -.207378   -.0988595
       2019  |  -.1285871   .0330575    -3.89   0.000    -.1933786   -.0637956
       2020  |  -.0980854   .0372913    -2.63   0.009     -.171175   -.0249959
       2021  |  -.1394551   .0371555    -3.75   0.000    -.2122785   -.0666318
       2022  |  -.2075709   .0370445    -5.60   0.000    -.2801768   -.1349649
             |
       _cons |   .3504631   .0915978     3.83   0.000     .1709347    .5299916
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             41.775
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               52.182
                         (Kleibergen-Paap rk Wald F statistic):         38.954
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         CSO
Included instruments: FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR
                      Gov_score Sustain_Perf Sust_Commit 3.id 6.id 8.id 10.id
                      12.id 13.id 14.id 15.id 16.id 17.id 18.id 19.id 20.id
                      21.id 22.id 24.id 26.id 28.id 29.id 30.id 32.id 35.id
                      40.id 41.id 42.id 43.id 44.id 45.id 47.id 50.id 51.id
                      52.id 53.id 55.id 56.id 57.id 58.id 61.id 62.id 63.id
                      64.id 66.id 70.id 76.id 78.id 79.id 81.id 82.id 85.id
                      88.id 91.id 93.id 94.id 95.id 97.id 98.id 99.id 100.id
                      101.id 102.id 104.id 106.id 107.id 109.id 110.id 111.id
                      114.id 117.id 121.id 122.id 123.id 124.id 126.id 127.id
                      128.id 130.id 131.id 133.id 134.id 135.id 139.id 140.id
                      144.id 145.id 147.id 148.id 149.id 151.id 152.id 156.id
                      157.id 158.id 159.id 160.id 161.id 162.id 163.id 169.id
                      170.id 172.id 173.id 175.id 176.id 177.id 181.id 184.id
                      186.id 187.id 193.id 200.id 201.id 202.id 206.id 207.id
                      208.id 209.id 210.id 212.id 215.id 217.id 218.id 219.id
                      222.id 223.id 224.id 227.id 228.id 229.id 230.id 233.id
                      235.id 236.id 237.id 239.id 240.id 243.id 246.id 247.id
                      248.id 249.id 253.id 254.id 255.id 257.id 259.id 261.id
                      262.id 263.id 264.id 265.id 266.id 268.id 269.id 270.id
                      271.id 272.id 273.id 274.id 277.id 278.id 279.id 280.id
                      281.id 282.id 283.id 284.id 287.id 290.id 291.id 293.id
                      296.id 300.id 301.id 302.id 303.id 307.id 309.id 310.id
                      311.id 313.id 315.id 316.id 319.id 321.id 322.id 325.id
                      326.id 333.id 334.id 335.id 337.id 339.id 341.id 342.id
                      344.id 348.id 350.id 351.id 354.id 355.id 356.id 357.id
                      360.id 361.id 362.id 365.id 366.id 368.id 369.id 370.id
                      371.id 372.id 374.id 376.id 379.id 380.id 381.id 382.id
                      384.id 385.id 386.id 388.id 399.id 404.id 405.id 409.id
                      414.id 416.id 417.id 419.id 420.id 421.id 423.id 425.id
                      426.id 427.id 429.id 431.id 432.id 435.id 436.id 437.id
                      438.id 439.id 440.id 442.id 443.id 444.id 445.id 446.id
                      447.id 448.id 454.id 457.id 458.id 460.id 461.id 463.id
                      465.id 468.id 469.id 471.id 472.id 473.id 475.id 476.id
                      481.id 482.id 483.id 484.id 485.id 486.id 489.id 491.id
                      492.id 494.id 497.id 499.id 500.id 502.id 503.id 504.id
                      505.id 506.id 507.id 509.id 510.id 2005.year 2006.year
                      2007.year 2008.year 2009.year 2010.year 2011.year
                      2012.year 2013.year 2014.year 2015.year 2016.year
                      2017.year 2018.year 2019.year 2020.year 2021.year
                      2022.year
Excluded instruments: Instrumental
------------------------------------------------------------------------------

. 
end of do-file

[Jeff Wooldridge]

Hussein: You shouldn't be putting in the dummy variables for id. if you use ivreghdfe (which you have to install: ssc install ivreghdfe). Then you can absorb id and year and focus on the parameters you care about. That should clear up the problem. Also, cluster the standard errors at the id level to allow serial correlation and heteroskedasticity.

[hussein bataineh]

thanks Jeff for your advice

plesae i have two enquires if you can advice me on how to solve them

1. i want to identify this singleton groups detected. 7 observation(s) so i can delete them in order to have same same number of observations in main regression and 2SLS
2. the Endogeneity test does not appear for me , I'm not sure why , is this is because of singleton groups and is there a way to display the Endogeneity test results

. ivreghdfe EQUITY FSIZE OP_CF SD_OCF TAX  BM LEV MA DPP RPP PSIZE DR Gov_score Sustain_Perf Sust_Commit (CSO = Instrumental),  absorb(id year)
(dropped 7 singleton observations)
(MWFE estimator converged in 7 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics consistent for homoskedasticity only

                                                      Number of obs =     4044
                                                      F( 15,  3730) =    10.13
                                                      Prob > F      =   0.0000
Total (centered) SS     =  46.32975885                Centered R2   =  -0.1074
Total (uncentered) SS   =  46.32975885                Uncentered R2 =  -0.1074
Residual SS             =  51.30371339                Root MSE      =    .1173

------------------------------------------------------------------------------
      EQUITY | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         CSO |  -.1729897   .0555421    -3.11   0.002    -.2818856   -.0640939
       FSIZE |   .0123795   .0077931     1.59   0.112    -.0028997    .0276586
       OP_CF |     -.0683    .057869    -1.18   0.238    -.1817579     .045158
      SD_OCF |  -.1461356   .1421566    -1.03   0.304    -.4248477    .1325766
         TAX |  -.0058738   .0083983    -0.70   0.484    -.0223396    .0105919
          BM |  -.0258302   .0128145    -2.02   0.044    -.0509542   -.0007062
         LEV |   -.020226   .0296631    -0.68   0.495    -.0783833    .0379314
          MA |   .0038532   .0164687     0.23   0.815    -.0284353    .0361417
         DPP |   .1396388   .0229292     6.09   0.000     .0946838    .1845938
         RPP |   .0998273   .0324568     3.08   0.002     .0361924    .1634622
       PSIZE |   .0209352   .0070038     2.99   0.003     .0072035     .034667
          DR |   .0404173    .006344     6.37   0.000     .0279792    .0528555
   Gov_score |  -.0000358   .0001322    -0.27   0.786     -.000295    .0002233
Sustain_Perf |   -.000039   .0002106    -0.19   0.853    -.0004519    .0003739
 Sust_Commit |  -.0079053   .0065018    -1.22   0.224    -.0206528    .0048421
------------------------------------------------------------------------------
Underidentification test (Anderson canon. corr. LM statistic):          55.794
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               52.182
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
------------------------------------------------------------------------------
Sargan statistic (overidentification test of all instruments):           0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         CSO
Included instruments: FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR
                      Gov_score Sustain_Perf Sust_Commit
Excluded instruments: Instrumental
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
          id |       281           0         281     |
        year |        19           1          18     |
-----------------------------------------------------+

. ivreghdfe EQUITY FSIZE OP_CF SD_OCF TAX  BM LEV MA DPP RPP PSIZE DR Gov_score Sustain_Perf Sust_Commit (CSO = Instrumental),  absorb(id year) cluster(id)
(dropped 7 singleton observations)
(MWFE estimator converged in 7 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on id

Number of clusters (id) =          281                Number of obs =     4044
                                                      F( 15,   280) =     3.73
                                                      Prob > F      =   0.0000
Total (centered) SS     =  46.32975885                Centered R2   =  -0.1074
Total (uncentered) SS   =  46.32975885                Uncentered R2 =  -0.1074
Residual SS             =  51.30371339                Root MSE      =    .1131

------------------------------------------------------------------------------
             |               Robust
      EQUITY | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         CSO |  -.1729897   .1334499    -1.30   0.196    -.4356823    .0897028
       FSIZE |   .0123795   .0164212     0.75   0.452    -.0199452    .0447041
       OP_CF |     -.0683   .1141748    -0.60   0.550    -.2930498    .1564499
      SD_OCF |  -.1461356   .2730804    -0.54   0.593    -.6836868    .3914157
         TAX |  -.0058738   .0088853    -0.66   0.509    -.0233642    .0116165
          BM |  -.0258302   .0219067    -1.18   0.239     -.068953    .0172925
         LEV |   -.020226    .061356    -0.33   0.742    -.1410035    .1005516
          MA |   .0038532   .0149517     0.26   0.797    -.0255788    .0332852
         DPP |   .1396388   .0526328     2.65   0.008     .0360327     .243245
         RPP |   .0998273   .0340293     2.93   0.004     .0328416     .166813
       PSIZE |   .0209352   .0169088     1.24   0.217    -.0123494    .0542198
          DR |   .0404173   .0107475     3.76   0.000     .0192611    .0615736
   Gov_score |  -.0000358   .0002086    -0.17   0.864    -.0004465    .0003748
Sustain_Perf |   -.000039   .0003703    -0.11   0.916     -.000768      .00069
 Sust_Commit |  -.0079053   .0110412    -0.72   0.475    -.0296396     .013829
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):              9.261
                                                   Chi-sq(1) P-val =    0.0023
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               56.099
                         (Kleibergen-Paap rk Wald F statistic):          9.702
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         CSO
Included instruments: FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR
                      Gov_score Sustain_Perf Sust_Commit
Excluded instruments: Instrumental
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
          id |       281         281           0    *|
        year |        19           0          19     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 

[Jeff Wooldridge]

Maybe this will work:

gen used = e(sample)
egen tobs = sum(used), by(id)
list id if tobs == 1

The test for endogeneity probably has to be done by hand. You can look at my paper with Riju Joshi. Basically, you explicitly use xtreg, fe to do the first stage. Save the FE residuals using the "e" option. Then add those residuals in the model estimated in the second stage, again using xtreg, fe. The test is on the first-stage residuals.

xtreg y2 x1 ... xK z1 ... zL if used, fe
predict v2hat, e
xtreg y1 y2 x1 ... xK v2hat if used, fe vce(cluster id)