-------------------------------------------------------------------------------------------------------------------------- log: D:\research\pripiski\dataset\probits.log log type: text opened on: 3 Dec 2010, 14:37:06 . . /*PART ONE. Dependent variable is MAXPENALTY.*/ . /*The maximum penalty in each case is ranked on a scale from 0 to 5.*/ . . /*Network size; control for time, sector, and space (political or social value).*/ . . oprobit maxpenalty accused slope ag lndistance russia, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -79.966417 Iteration 2: log pseudolikelihood = -79.966402 Ordered probit regression Number of obs = 57 Wald chi2(5) = 0.53 Prob > chi2 = 0.9910 Log pseudolikelihood = -79.966402 Pseudo R2 = 0.0031 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0040328 .0139154 -0.29 0.772 -.0313065 .0232409 slope | -.0938371 .3885093 -0.24 0.809 -.8553014 .6676272 ag | -.1537631 .3279332 -0.47 0.639 -.7965004 .4889743 lndistance | .0230706 .0691214 0.33 0.739 -.1124049 .1585461 russia | .0595271 .3730617 0.16 0.873 -.6716604 .7907146 -------------+---------------------------------------------------------------- /cut1 | -1.614096 .6990027 -2.984116 -.2440755 /cut2 | -.3627761 .6560241 -1.64856 .9230075 /cut3 | .8271567 .65324 -.4531703 2.107484 /cut4 | 1.024745 .6392239 -.2281111 2.277601 /cut5 | 1.181919 .6251285 -.0433108 2.407148 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance russia, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -80.070566 Iteration 2: log pseudolikelihood = -80.070559 Ordered probit regression Number of obs = 57 Wald chi2(4) = 0.36 Prob > chi2 = 0.9858 Log pseudolikelihood = -80.070559 Pseudo R2 = 0.0018 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0067795 .0129553 -0.52 0.601 -.0321714 .0186125 slope | -.1193611 .3897768 -0.31 0.759 -.8833097 .6445874 lndistance | .0150885 .0705929 0.21 0.831 -.123271 .153448 russia | .0909784 .3639729 0.25 0.803 -.6223953 .8043522 -------------+---------------------------------------------------------------- /cut1 | -1.59675 .6966158 -2.962092 -.2314077 /cut2 | -.357289 .6576464 -1.646252 .9316742 /cut3 | .8315392 .6554066 -.453034 2.116112 /cut4 | 1.031523 .6410943 -.2249987 2.288045 /cut5 | 1.190694 .6275929 -.0393654 2.420753 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -80.098307 Iteration 2: log pseudolikelihood = -80.098301 Ordered probit regression Number of obs = 57 Wald chi2(3) = 0.32 Prob > chi2 = 0.9556 Log pseudolikelihood = -80.098301 Pseudo R2 = 0.0015 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0067994 .0126991 -0.54 0.592 -.0316892 .0180904 slope | -.1238102 .3931 -0.31 0.753 -.894272 .6466515 lndistance | .0089868 .0640366 0.14 0.888 -.1165226 .1344963 -------------+---------------------------------------------------------------- /cut1 | -1.704575 .5097954 -2.703756 -.7053942 /cut2 | -.4661997 .5092347 -1.464281 .5318821 /cut3 | .7239418 .5222864 -.2997208 1.747604 /cut4 | .924138 .5027431 -.0612203 1.909496 /cut5 | 1.082869 .5290524 .0459454 2.119793 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope russia, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -85.024066 Iteration 2: log pseudolikelihood = -85.024061 Ordered probit regression Number of obs = 61 Wald chi2(3) = 0.35 Prob > chi2 = 0.9509 Log pseudolikelihood = -85.024061 Pseudo R2 = 0.0013 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0063611 .012623 -0.50 0.614 -.0311018 .0183796 slope | -.1106664 .3429326 -0.32 0.747 -.7828019 .5614691 russia | -.0289418 .3089478 -0.09 0.925 -.6344684 .5765848 -------------+---------------------------------------------------------------- /cut1 | -1.791397 .3935867 -2.562812 -1.019981 /cut2 | -.5369353 .3565549 -1.23577 .1618995 /cut3 | .6626529 .3634461 -.0496884 1.374994 /cut4 | .846188 .3602002 .1402087 1.552167 /cut5 | .9888799 .3509462 .3010381 1.676722 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -85.028277 Iteration 2: log pseudolikelihood = -85.028272 Ordered probit regression Number of obs = 61 Wald chi2(2) = 0.30 Prob > chi2 = 0.8588 Log pseudolikelihood = -85.028272 Pseudo R2 = 0.0013 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0063994 .0126547 -0.51 0.613 -.0312021 .0184033 slope | -.1115154 .3401387 -0.33 0.743 -.778175 .5551443 -------------+---------------------------------------------------------------- /cut1 | -1.770071 .3485444 -2.453205 -1.086936 /cut2 | -.5158314 .3380827 -1.178461 .1467985 /cut3 | .6832609 .3510204 -.0047265 1.371248 /cut4 | .8667297 .3403515 .199653 1.533806 /cut5 | 1.009477 .3552575 .3131851 1.705769 ------------------------------------------------------------------------------ . oprobit maxpenalty accused ag, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -86.16463 Iteration 2: log pseudolikelihood = -86.164623 Ordered probit regression Number of obs = 62 Wald chi2(2) = 0.32 Prob > chi2 = 0.8513 Log pseudolikelihood = -86.164623 Pseudo R2 = 0.0020 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0022832 .0134877 -0.17 0.866 -.0287185 .0241521 ag | -.1518608 .3208389 -0.47 0.636 -.7806935 .4769719 -------------+---------------------------------------------------------------- /cut1 | -1.733743 .2877179 -2.29766 -1.169826 /cut2 | -.4330197 .1866268 -.7988014 -.067238 /cut3 | .7489546 .193562 .36958 1.128329 /cut4 | .9286411 .1992554 .5381076 1.319175 /cut5 | 1.068995 .2188525 .6400514 1.497938 ------------------------------------------------------------------------------ . oprobit maxpenalty accused, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -86.2915 Iteration 2: log pseudolikelihood = -86.291498 Ordered probit regression Number of obs = 62 Wald chi2(1) = 0.17 Prob > chi2 = 0.6845 Log pseudolikelihood = -86.291498 Pseudo R2 = 0.0005 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0049836 .0122655 -0.41 0.685 -.0290234 .0190563 -------------+---------------------------------------------------------------- /cut1 | -1.686232 .2914131 -2.257391 -1.115073 /cut2 | -.3958877 .1749806 -.7388434 -.0529319 /cut3 | .7855858 .1850043 .422984 1.148188 /cut4 | .9669717 .1951882 .5844099 1.349534 /cut5 | 1.10848 .2057089 .7052985 1.511662 ------------------------------------------------------------------------------ . . /*Control for scale of deception (value of the offense).*/ . /*Add xplan xplanmiss xloss xlossmiss xgain xgainmiss.*/ . . oprobit maxpenalty accused slope ag lndistance russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -72.35628 Iteration 2: log pseudolikelihood = -72.270778 Iteration 3: log pseudolikelihood = -72.270594 Ordered probit regression Number of obs = 57 Wald chi2(11) = 34.07 Prob > chi2 = 0.0004 Log pseudolikelihood = -72.270594 Pseudo R2 = 0.0991 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0016503 .0137712 -0.12 0.905 -.0286413 .0253408 slope | -.0097871 .4148313 -0.02 0.981 -.8228415 .8032674 ag | -.1460715 .3421071 -0.43 0.669 -.8165892 .5244462 lndistance | -.0110103 .0770554 -0.14 0.886 -.1620361 .1400155 russia | -.1225065 .390924 -0.31 0.754 -.8887036 .6436906 xplan | .0239769 .0371751 0.64 0.519 -.0488851 .0968388 xplanmiss | .5110976 .4567584 1.12 0.263 -.3841324 1.406328 xloss | -.0010566 .000299 -3.53 0.000 -.0016426 -.0004705 xlossmiss | -.9584904 .3360429 -2.85 0.004 -1.617122 -.2998584 xgain | -.0589202 .0207032 -2.85 0.004 -.0994977 -.0183427 xgainmiss | -.9667354 .4487424 -2.15 0.031 -1.846254 -.0872165 -------------+---------------------------------------------------------------- /cut1 | -3.342367 .8503038 -5.008932 -1.675802 /cut2 | -1.880012 .7407703 -3.331895 -.4281288 /cut3 | -.4856966 .724059 -1.904826 .9334329 /cut4 | -.2496226 .7292802 -1.678985 1.17974 /cut5 | -.0709541 .7251184 -1.49216 1.350252 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -72.434496 Iteration 2: log pseudolikelihood = -72.352941 Iteration 3: log pseudolikelihood = -72.352768 Ordered probit regression Number of obs = 57 Wald chi2(10) = 33.38 Prob > chi2 = 0.0002 Log pseudolikelihood = -72.352768 Pseudo R2 = 0.0980 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0042028 .0132984 -0.32 0.752 -.0302673 .0218616 slope | -.0373133 .4232467 -0.09 0.930 -.8668615 .7922349 lndistance | -.0161759 .0787506 -0.21 0.837 -.1705242 .1381725 russia | -.0898427 .3702229 -0.24 0.808 -.8154661 .6357808 xplan | .0238954 .0374022 0.64 0.523 -.0494115 .0972023 xplanmiss | .512826 .4586706 1.12 0.264 -.3861517 1.411804 xloss | -.0010665 .0002907 -3.67 0.000 -.0016362 -.0004967 xlossmiss | -.9534525 .3407216 -2.80 0.005 -1.621255 -.2856504 xgain | -.0578937 .0205863 -2.81 0.005 -.0982421 -.0175454 xgainmiss | -1.001466 .4396287 -2.28 0.023 -1.863123 -.1398097 -------------+---------------------------------------------------------------- /cut1 | -3.338098 .8485282 -5.001183 -1.675014 /cut2 | -1.8879 .741824 -3.341849 -.4339519 /cut3 | -.4966192 .7244455 -1.916506 .9232679 /cut4 | -.2575667 .7315446 -1.691368 1.176234 /cut5 | -.0767722 .7293107 -1.506195 1.35265 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -72.460033 Iteration 2: log pseudolikelihood = -72.375456 Iteration 3: log pseudolikelihood = -72.375262 Iteration 4: log pseudolikelihood = -72.375262 Ordered probit regression Number of obs = 57 Wald chi2(9) = 33.47 Prob > chi2 = 0.0001 Log pseudolikelihood = -72.375262 Pseudo R2 = 0.0978 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0041415 .0136057 -0.30 0.761 -.0308081 .0225252 slope | -.0373894 .4208034 -0.09 0.929 -.8621488 .78737 lndistance | -.0105399 .0701057 -0.15 0.880 -.1479445 .1268646 xplan | .0226782 .0354304 0.64 0.522 -.0467641 .0921206 xplanmiss | .5189373 .4611204 1.13 0.260 -.3848421 1.422717 xloss | -.0010658 .0002893 -3.68 0.000 -.0016329 -.0004987 xlossmiss | -.960751 .3314414 -2.90 0.004 -1.610364 -.3111378 xgain | -.0558168 .0194064 -2.88 0.004 -.0938526 -.0177809 xgainmiss | -.9757587 .4310225 -2.26 0.024 -1.820547 -.1309702 -------------+---------------------------------------------------------------- /cut1 | -3.207217 .7416609 -4.660846 -1.753589 /cut2 | -1.759206 .6296166 -2.993232 -.5251804 /cut3 | -.3715548 .6244865 -1.595526 .8524162 /cut4 | -.1324641 .6233906 -1.354287 1.089359 /cut5 | .0491493 .6460713 -1.217127 1.315426 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -76.29586 Iteration 2: log pseudolikelihood = -76.195043 Iteration 3: log pseudolikelihood = -76.194784 Iteration 4: log pseudolikelihood = -76.194784 Ordered probit regression Number of obs = 61 Wald chi2(9) = 33.84 Prob > chi2 = 0.0001 Log pseudolikelihood = -76.194784 Pseudo R2 = 0.1050 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0036796 .0133594 -0.28 0.783 -.0298635 .0225042 slope | -.0132814 .3717613 -0.04 0.972 -.7419202 .7153573 russia | -.0625329 .3121943 -0.20 0.841 -.6744225 .5493567 xplan | .0236679 .0366892 0.65 0.519 -.0482417 .0955774 xplanmiss | .5382228 .4583572 1.17 0.240 -.3601407 1.436586 xloss | -.0011155 .0002886 -3.87 0.000 -.0016811 -.0005499 xlossmiss | -1.006569 .3426954 -2.94 0.003 -1.67824 -.3348986 xgain | -.0581593 .0211761 -2.75 0.006 -.0996638 -.0166549 xgainmiss | -1.032053 .4424245 -2.33 0.020 -1.89919 -.1649172 -------------+---------------------------------------------------------------- /cut1 | -3.290133 .758845 -4.777442 -1.802824 /cut2 | -1.808513 .6744253 -3.130362 -.4866639 /cut3 | -.3927627 .6619458 -1.690153 .9046272 /cut4 | -.1705182 .6558789 -1.456017 1.114981 /cut5 | -.00422 .6526525 -1.283395 1.274955 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -76.314449 Iteration 2: log pseudolikelihood = -76.21105 Iteration 3: log pseudolikelihood = -76.210769 Iteration 4: log pseudolikelihood = -76.210769 Ordered probit regression Number of obs = 61 Wald chi2(8) = 34.21 Prob > chi2 = 0.0000 Log pseudolikelihood = -76.210769 Pseudo R2 = 0.1048 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0037212 .0135224 -0.28 0.783 -.0302247 .0227823 slope | -.0180236 .3669605 -0.05 0.961 -.7372528 .7012057 xplan | .0229413 .0357307 0.64 0.521 -.0470896 .0929721 xplanmiss | .5479713 .4572656 1.20 0.231 -.3482528 1.444195 xloss | -.0011165 .0002864 -3.90 0.000 -.0016779 -.000555 xlossmiss | -1.017539 .3297176 -3.09 0.002 -1.663774 -.3713046 xgain | -.0566073 .0194799 -2.91 0.004 -.0947873 -.0184274 xgainmiss | -1.004986 .4095254 -2.45 0.014 -1.807641 -.2023314 -------------+---------------------------------------------------------------- /cut1 | -3.216581 .7319976 -4.65127 -1.781892 /cut2 | -1.73757 .6341185 -2.980419 -.4947204 /cut3 | -.3236833 .6258673 -1.550361 .9029941 /cut4 | -.10114 .6154299 -1.30736 1.10508 /cut5 | .0657036 .6264146 -1.162047 1.293454 ------------------------------------------------------------------------------ . oprobit maxpenalty accused ag xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -78.065998 Iteration 2: log pseudolikelihood = -77.966865 Iteration 3: log pseudolikelihood = -77.966555 Iteration 4: log pseudolikelihood = -77.966555 Ordered probit regression Number of obs = 62 Wald chi2(8) = 36.58 Prob > chi2 = 0.0000 Log pseudolikelihood = -77.966555 Pseudo R2 = 0.0969 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0018406 .0138039 -0.13 0.894 -.0288958 .0252146 ag | -.0924228 .3321709 -0.28 0.781 -.7434658 .5586201 xplan | .0243455 .034814 0.70 0.484 -.0438887 .0925798 xplanmiss | .48468 .4499188 1.08 0.281 -.3971446 1.366505 xloss | -.0010862 .0002836 -3.83 0.000 -.0016421 -.0005304 xlossmiss | -.9397296 .3143961 -2.99 0.003 -1.555935 -.3235246 xgain | -.056636 .0180308 -3.14 0.002 -.0919757 -.0212963 xgainmiss | -.9828465 .4287472 -2.29 0.022 -1.823176 -.1425175 -------------+---------------------------------------------------------------- /cut1 | -3.193419 .7405445 -4.644859 -1.741978 /cut2 | -1.676009 .6080582 -2.867781 -.4842368 /cut3 | -.3067761 .5890855 -1.461363 .8478103 /cut4 | -.0909269 .5877995 -1.242993 1.061139 /cut5 | .0717957 .5950499 -1.094481 1.238072 ------------------------------------------------------------------------------ . oprobit maxpenalty accused xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -78.102954 Iteration 2: log pseudolikelihood = -78.006911 Iteration 3: log pseudolikelihood = -78.006623 Iteration 4: log pseudolikelihood = -78.006623 Ordered probit regression Number of obs = 62 Wald chi2(7) = 32.40 Prob > chi2 = 0.0000 Log pseudolikelihood = -78.006623 Pseudo R2 = 0.0965 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0034518 .0130108 -0.27 0.791 -.0289525 .0220489 xplan | .0242031 .0350159 0.69 0.489 -.0444269 .0928331 xplanmiss | .4852324 .4513812 1.07 0.282 -.3994586 1.369923 xloss | -.0010988 .0002669 -4.12 0.000 -.0016219 -.0005757 xlossmiss | -.9320035 .3217231 -2.90 0.004 -1.562569 -.3014378 xgain | -.0566393 .0180652 -3.14 0.002 -.0920465 -.0212322 xgainmiss | -1.015483 .4071975 -2.49 0.013 -1.813576 -.2173907 -------------+---------------------------------------------------------------- /cut1 | -3.191709 .7461378 -4.654112 -1.729306 /cut2 | -1.679907 .6059165 -2.867481 -.4923322 /cut3 | -.3110996 .5861226 -1.459879 .8376796 /cut4 | -.0940152 .585872 -1.242303 1.054273 /cut5 | .0693377 .5943464 -1.09556 1.234235 ------------------------------------------------------------------------------ . . /*Control for type of deception.*/ . /*Add selfins coins unins joint complex.*/ . . oprobit maxpenalty accused slope ag lndistance russia selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -79.174012 Iteration 2: log pseudolikelihood = -79.173746 Ordered probit regression Number of obs = 57 Wald chi2(10) = 2.94 Prob > chi2 = 0.9829 Log pseudolikelihood = -79.173746 Pseudo R2 = 0.0130 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0102659 .0160977 -0.64 0.524 -.0418168 .0212849 slope | -.0879399 .3851762 -0.23 0.819 -.8428714 .6669916 ag | .204424 .6074183 0.34 0.736 -.986094 1.394942 lndistance | .0247821 .0718657 0.34 0.730 -.1160722 .1656363 russia | .0370849 .3835639 0.10 0.923 -.7146865 .7888562 selfins | -.1602065 .4796797 -0.33 0.738 -1.100361 .7799484 coins | .2769375 .3992446 0.69 0.488 -.5055676 1.059443 unins | -.2230534 .3631664 -0.61 0.539 -.9348465 .4887397 joint | -.404805 .5872236 -0.69 0.491 -1.555742 .7461321 complex | -.0305416 .3317185 -0.09 0.927 -.6806979 .6196147 -------------+---------------------------------------------------------------- /cut1 | -1.658117 .8405857 -3.305635 -.0105994 /cut2 | -.3707147 .7883794 -1.91591 1.17448 /cut3 | .8311055 .7873108 -.7119953 2.374206 /cut4 | 1.027333 .7734397 -.4885806 2.543247 /cut5 | 1.184835 .7711382 -.3265685 2.696238 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance russia selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -79.235281 Iteration 2: log pseudolikelihood = -79.235058 Ordered probit regression Number of obs = 57 Wald chi2(9) = 2.52 Prob > chi2 = 0.9802 Log pseudolikelihood = -79.235058 Pseudo R2 = 0.0123 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0072062 .0141689 -0.51 0.611 -.0349767 .0205643 slope | -.0605634 .3830029 -0.16 0.874 -.8112352 .6901085 lndistance | .0268598 .0726685 0.37 0.712 -.1155678 .1692873 russia | .0373483 .3851506 0.10 0.923 -.7175329 .7922295 selfins | -.1974423 .4673234 -0.42 0.673 -1.113379 .7184947 coins | .231833 .3648474 0.64 0.525 -.4832548 .9469208 unins | -.2318206 .3589565 -0.65 0.518 -.9353625 .4717212 joint | -.2610474 .3952499 -0.66 0.509 -1.035723 .5136282 complex | -.0486081 .3125147 -0.16 0.876 -.6611257 .5639095 -------------+---------------------------------------------------------------- /cut1 | -1.670392 .8297837 -3.296738 -.0440455 /cut2 | -.3841484 .7761903 -1.905454 1.137157 /cut3 | .8175395 .7728437 -.6972064 2.332285 /cut4 | 1.01307 .7585158 -.4735932 2.499734 /cut5 | 1.169694 .7550016 -.3100821 2.64947 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope lndistance selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -80.218061 Iteration 1: log pseudolikelihood = -79.239661 Iteration 2: log pseudolikelihood = -79.239435 Ordered probit regression Number of obs = 57 Wald chi2(8) = 2.53 Prob > chi2 = 0.9603 Log pseudolikelihood = -79.239435 Pseudo R2 = 0.0122 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0072183 .0140876 -0.51 0.608 -.0348295 .0203928 slope | -.0622766 .3857164 -0.16 0.872 -.8182669 .6937137 lndistance | .0248196 .0671397 0.37 0.712 -.1067717 .156411 selfins | -.1964913 .4677211 -0.42 0.674 -1.113208 .7202252 coins | .2298404 .3617416 0.64 0.525 -.47916 .9388409 unins | -.2330973 .3578994 -0.65 0.515 -.9345672 .4683727 joint | -.2692455 .3797941 -0.71 0.478 -1.013628 .4751373 complex | -.0479771 .3108279 -0.15 0.877 -.6571886 .5612344 -------------+---------------------------------------------------------------- /cut1 | -1.715309 .6546446 -2.998389 -.4322293 /cut2 | -.428813 .6214561 -1.646845 .7892186 /cut3 | .7734336 .6301853 -.461707 2.008574 /cut4 | .9689318 .6138056 -.234105 2.171969 /cut5 | 1.125305 .6438026 -.1365248 2.387135 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope russia selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -84.376619 Iteration 2: log pseudolikelihood = -84.376478 Ordered probit regression Number of obs = 61 Wald chi2(8) = 2.01 Prob > chi2 = 0.9806 Log pseudolikelihood = -84.376478 Pseudo R2 = 0.0089 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0044472 .0142695 -0.31 0.755 -.0324149 .0235205 slope | -.0595958 .3461896 -0.17 0.863 -.738115 .6189234 russia | -.1025608 .3265299 -0.31 0.753 -.7425476 .537426 selfins | -.2226711 .4251584 -0.52 0.600 -1.055966 .6106241 coins | .2291739 .3362262 0.68 0.495 -.4298174 .8881652 unins | -.0441154 .345126 -0.13 0.898 -.7205499 .632319 joint | -.2182925 .3859735 -0.57 0.572 -.9747868 .5382017 complex | .0436478 .2996202 0.15 0.884 -.5435971 .6308926 -------------+---------------------------------------------------------------- /cut1 | -1.831576 .4973253 -2.806316 -.8568364 /cut2 | -.5441707 .4591314 -1.444052 .3557103 /cut3 | .6651921 .4590673 -.2345632 1.564947 /cut4 | .8460816 .4600655 -.0556301 1.747793 /cut5 | .9872356 .4640718 .0776716 1.8968 ------------------------------------------------------------------------------ . oprobit maxpenalty accused slope selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -85.135518 Iteration 1: log pseudolikelihood = -84.425003 Iteration 2: log pseudolikelihood = -84.424889 Ordered probit regression Number of obs = 61 Wald chi2(7) = 1.86 Prob > chi2 = 0.9672 Log pseudolikelihood = -84.424889 Pseudo R2 = 0.0083 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0047433 .0143867 -0.33 0.742 -.0329408 .0234541 slope | -.0639428 .3412065 -0.19 0.851 -.7326954 .6048097 selfins | -.2410151 .4224407 -0.57 0.568 -1.068984 .5869535 coins | .2172966 .3333719 0.65 0.515 -.4361003 .8706935 unins | -.0331316 .3412074 -0.10 0.923 -.7018858 .6356227 joint | -.2000104 .3807444 -0.53 0.599 -.9462556 .5462348 complex | .0368571 .2992559 0.12 0.902 -.5496736 .6233879 -------------+---------------------------------------------------------------- /cut1 | -1.755498 .466549 -2.669918 -.841079 /cut2 | -.4716624 .4410255 -1.336057 .3927317 /cut3 | .7358916 .4447992 -.1358988 1.607682 /cut4 | .9168573 .4409008 .0527075 1.781007 /cut5 | 1.058383 .4636467 .1496522 1.967114 ------------------------------------------------------------------------------ . oprobit maxpenalty accused ag selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -85.579232 Iteration 2: log pseudolikelihood = -85.579101 Ordered probit regression Number of obs = 62 Wald chi2(7) = 2.12 Prob > chi2 = 0.9529 Log pseudolikelihood = -85.579101 Pseudo R2 = 0.0088 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0069558 .0155465 -0.45 0.655 -.0374264 .0235149 ag | .2159192 .5637489 0.38 0.702 -.8890083 1.320847 selfins | -.1657899 .4211417 -0.39 0.694 -.9912125 .6596327 coins | .2933764 .3713942 0.79 0.430 -.4345429 1.021296 unins | .0111201 .3458741 0.03 0.974 -.6667805 .6890208 joint | -.342683 .5534716 -0.62 0.536 -1.427467 .7421013 complex | .0238857 .3153294 0.08 0.940 -.5941486 .6419199 -------------+---------------------------------------------------------------- /cut1 | -1.665281 .4172519 -2.48308 -.8474826 /cut2 | -.3419126 .3332811 -.9951316 .3113064 /cut3 | .8492177 .3353404 .1919627 1.506473 /cut4 | 1.028273 .3412336 .3594679 1.697079 /cut5 | 1.168881 .3643044 .4548573 1.882904 ------------------------------------------------------------------------------ . oprobit maxpenalty accused selfins coins unins joint complex, vce(robust) Iteration 0: log pseudolikelihood = -86.336895 Iteration 1: log pseudolikelihood = -85.653934 Iteration 2: log pseudolikelihood = -85.653825 Ordered probit regression Number of obs = 62 Wald chi2(6) = 2.00 Prob > chi2 = 0.9200 Log pseudolikelihood = -85.653825 Pseudo R2 = 0.0079 ------------------------------------------------------------------------------ | Robust maxpenalty | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0039545 .0137739 -0.29 0.774 -.0309509 .0230419 selfins | -.195089 .4108946 -0.47 0.635 -1.000428 .6102497 coins | .2483798 .3354746 0.74 0.459 -.4091384 .905898 unins | .0033621 .3435647 0.01 0.992 -.6700123 .6767364 joint | -.1806107 .3829071 -0.47 0.637 -.9310948 .5698734 complex | .0029072 .2968323 0.01 0.992 -.5788734 .5846878 -------------+---------------------------------------------------------------- /cut1 | -1.706064 .3820212 -2.454811 -.9573157 /cut2 | -.3853012 .2870901 -.9479874 .177385 /cut3 | .8053711 .2843684 .2480192 1.362723 /cut4 | .9842458 .2941511 .4077203 1.560771 /cut5 | 1.124444 .3175081 .5021397 1.746749 ------------------------------------------------------------------------------ . . /*PART TWO. Dependent variable is EXPEL.*/ . /*"Expel" is equal to 1 when maxpenalty > 2.*/ . /*This variable is called expel because the accused was expelled*/ . /*from either the ministerial system or the party and/or was sent for trial.*/ . . /*Network size; control for time, sector, and space (political or social value).*/ . . probit expel accused slope ag lndistance russia, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -27.412919 Iteration 2: log pseudolikelihood = -27.40236 Iteration 3: log pseudolikelihood = -27.402359 Probit regression Number of obs = 57 Wald chi2(5) = 4.04 Prob > chi2 = 0.5436 Log pseudolikelihood = -27.402359 Pseudo R2 = 0.0659 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0169578 .016655 -1.02 0.309 -.0496011 .0156855 slope | -.8254337 .4511644 -1.83 0.067 -1.7097 .0588322 ag | .4349525 .4279383 1.02 0.309 -.4037912 1.273696 lndistance | -.042634 .0913532 -0.47 0.641 -.221683 .1364151 russia | .103659 .5402488 0.19 0.848 -.9552093 1.162527 _cons | -.1592414 .8316221 -0.19 0.848 -1.789191 1.470708 ------------------------------------------------------------------------------ . probit expel accused slope lndistance russia, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -27.845697 Iteration 2: log pseudolikelihood = -27.84134 Iteration 3: log pseudolikelihood = -27.84134 Probit regression Number of obs = 57 Wald chi2(4) = 2.92 Prob > chi2 = 0.5721 Log pseudolikelihood = -27.84134 Pseudo R2 = 0.0509 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0085092 .0162524 -0.52 0.601 -.0403633 .0233449 slope | -.7406629 .4378848 -1.69 0.091 -1.598901 .1175755 lndistance | -.0179124 .0881245 -0.20 0.839 -.1906332 .1548083 russia | .0044181 .5513562 0.01 0.994 -1.07622 1.085056 _cons | -.1363146 .8345359 -0.16 0.870 -1.771975 1.499346 ------------------------------------------------------------------------------ . probit expel accused slope lndistance, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -27.845388 Iteration 2: log pseudolikelihood = -27.841374 Iteration 3: log pseudolikelihood = -27.841374 Probit regression Number of obs = 57 Wald chi2(3) = 2.87 Prob > chi2 = 0.4113 Log pseudolikelihood = -27.841374 Pseudo R2 = 0.0509 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0085073 .0162569 -0.52 0.601 -.0403703 .0233557 slope | -.740947 .440427 -1.68 0.093 -1.604168 .1222742 lndistance | -.0182085 .0831648 -0.22 0.827 -.1812084 .1447915 _cons | -.1310354 .5761041 -0.23 0.820 -1.260179 .9981078 ------------------------------------------------------------------------------ . probit expel accused slope russia, vce(robust) Iteration 0: log pseudolikelihood = -31.601316 Iteration 1: log pseudolikelihood = -30.778342 Iteration 2: log pseudolikelihood = -30.776682 Iteration 3: log pseudolikelihood = -30.776682 Probit regression Number of obs = 61 Wald chi2(3) = 1.64 Prob > chi2 = 0.6498 Log pseudolikelihood = -30.776682 Pseudo R2 = 0.0261 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0044894 .0162238 -0.28 0.782 -.0362875 .0273086 slope | -.5239062 .4123164 -1.27 0.204 -1.332031 .284219 russia | .0454508 .4442227 0.10 0.919 -.8252097 .9161113 _cons | -.4318085 .4661453 -0.93 0.354 -1.345437 .4818195 ------------------------------------------------------------------------------ . probit expel accused slope, vce(robust) Iteration 0: log pseudolikelihood = -31.601316 Iteration 1: log pseudolikelihood = -30.784155 Iteration 2: log pseudolikelihood = -30.782511 Iteration 3: log pseudolikelihood = -30.782511 Probit regression Number of obs = 61 Wald chi2(2) = 1.61 Prob > chi2 = 0.4472 Log pseudolikelihood = -30.782511 Pseudo R2 = 0.0259 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0043993 .0161842 -0.27 0.786 -.0361199 .0273212 slope | -.5243997 .4141471 -1.27 0.205 -1.336113 .2873137 _cons | -.3979045 .3699791 -1.08 0.282 -1.12305 .3272412 ------------------------------------------------------------------------------ . probit expel accused ag, vce(robust) Iteration 0: log pseudolikelihood = -31.838796 Iteration 1: log pseudolikelihood = -31.761524 Iteration 2: log pseudolikelihood = -31.761503 Probit regression Number of obs = 62 Wald chi2(2) = 0.15 Prob > chi2 = 0.9270 Log pseudolikelihood = -31.761503 Pseudo R2 = 0.0024 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0010987 .0160702 -0.07 0.945 -.0325957 .0303983 ag | .1523427 .3951129 0.39 0.700 -.6220644 .9267497 _cons | -.8559341 .2281256 -3.75 0.000 -1.303052 -.4088162 ------------------------------------------------------------------------------ . probit expel accused, vce(robust) Iteration 0: log pseudolikelihood = -31.838796 Iteration 1: log pseudolikelihood = -31.835625 Iteration 2: log pseudolikelihood = -31.835622 Probit regression Number of obs = 62 Wald chi2(1) = 0.01 Prob > chi2 = 0.9082 Log pseudolikelihood = -31.835622 Pseudo R2 = 0.0001 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0018236 .0158229 0.12 0.908 -.0291887 .0328358 _cons | -.8162026 .1951216 -4.18 0.000 -1.198634 -.4337712 ------------------------------------------------------------------------------ . . /*Control for scale of deception (value of the offense).*/ . /*Add xplan xplanmiss xloss xlossmiss xgain xgainmiss.*/ . . probit expel accused slope ag lndistance russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -20.794865 Iteration 2: log pseudolikelihood = -19.323225 Iteration 3: log pseudolikelihood = -18.748522 Iteration 4: log pseudolikelihood = -18.500012 Iteration 5: log pseudolikelihood = -18.475064 Iteration 6: log pseudolikelihood = -18.474467 Iteration 7: log pseudolikelihood = -18.474466 Probit regression Number of obs = 57 Wald chi2(11) = 26.77 Prob > chi2 = 0.0050 Log pseudolikelihood = -18.474466 Pseudo R2 = 0.3702 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0272041 .0167147 -1.63 0.104 -.0599643 .0055562 slope | -1.491703 .5849832 -2.55 0.011 -2.638249 -.3451569 ag | 1.010196 .521963 1.94 0.053 -.0128332 2.033224 lndistance | -.178535 .1454953 -1.23 0.220 -.4637005 .1066305 russia | .5048421 .8012453 0.63 0.529 -1.06557 2.075254 xplan | -.5241353 .2967358 -1.77 0.077 -1.105727 .0574562 xplanmiss | .6674702 .7390278 0.90 0.366 -.7809977 2.115938 xloss | -.0020408 .0013336 -1.53 0.126 -.0046547 .0005731 xlossmiss | -1.868286 .610637 -3.06 0.002 -3.065113 -.6714599 xgain | -.1512112 .0698224 -2.17 0.030 -.2880606 -.0143618 xgainmiss | -2.07152 .8978352 -2.31 0.021 -3.831245 -.3117954 _cons | 3.137773 1.837931 1.71 0.088 -.4645058 6.740053 ------------------------------------------------------------------------------ Note: 5 failures and 0 successes completely determined. . probit expel accused slope lndistance russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -21.275914 Iteration 2: log pseudolikelihood = -20.124481 Iteration 3: log pseudolikelihood = -19.714604 Iteration 4: log pseudolikelihood = -19.596663 Iteration 5: log pseudolikelihood = -19.576933 Iteration 6: log pseudolikelihood = -19.576377 Iteration 7: log pseudolikelihood = -19.576376 Probit regression Number of obs = 57 Wald chi2(10) = 31.33 Prob > chi2 = 0.0005 Log pseudolikelihood = -19.576376 Pseudo R2 = 0.3327 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0069842 .0162147 -0.43 0.667 -.0387645 .0247961 slope | -.9983329 .5592961 -1.78 0.074 -2.094533 .0978674 lndistance | -.101494 .1216732 -0.83 0.404 -.3399691 .1369812 russia | .3611154 .7759141 0.47 0.642 -1.159648 1.881879 xplan | -.3529765 .3244924 -1.09 0.277 -.9889699 .2830169 xplanmiss | .7423213 .7362107 1.01 0.313 -.7006253 2.185268 xloss | -.0020496 .0014482 -1.42 0.157 -.004888 .0007889 xlossmiss | -1.851628 .5346032 -3.46 0.001 -2.899431 -.8038254 xgain | -.1457001 .0569549 -2.56 0.011 -.2573296 -.0340705 xgainmiss | -1.578406 .7061898 -2.24 0.025 -2.962513 -.1942995 _cons | 2.225985 1.510973 1.47 0.141 -.735467 5.187438 ------------------------------------------------------------------------------ Note: 4 failures and 0 successes completely determined. . probit expel accused slope lndistance xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -29.33523 Iteration 1: log pseudolikelihood = -21.290172 Iteration 2: log pseudolikelihood = -20.262408 Iteration 3: log pseudolikelihood = -19.874864 Iteration 4: log pseudolikelihood = -19.716775 Iteration 5: log pseudolikelihood = -19.699299 Iteration 6: log pseudolikelihood = -19.698879 Iteration 7: log pseudolikelihood = -19.698879 Probit regression Number of obs = 57 Wald chi2(9) = 27.60 Prob > chi2 = 0.0011 Log pseudolikelihood = -19.698879 Pseudo R2 = 0.3285 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0055766 .0164337 -0.34 0.734 -.0377862 .0266329 slope | -1.002054 .5727503 -1.75 0.080 -2.124624 .1205155 lndistance | -.1202388 .1114362 -1.08 0.281 -.3386498 .0981721 xplan | -.4174673 .2713517 -1.54 0.124 -.9493069 .1143724 xplanmiss | .577768 .7210987 0.80 0.423 -.8355595 1.991096 xloss | -.0018907 .0013935 -1.36 0.175 -.0046219 .0008405 xlossmiss | -1.746583 .5403397 -3.23 0.001 -2.805629 -.6875365 xgain | -.1447779 .0547996 -2.64 0.008 -.2521832 -.0373726 xgainmiss | -1.615607 .7208074 -2.24 0.025 -3.028364 -.2028509 _cons | 2.73415 1.051321 2.60 0.009 .6735994 4.794701 ------------------------------------------------------------------------------ Note: 3 failures and 0 successes completely determined. . probit expel accused slope russia xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -31.601316 Iteration 1: log pseudolikelihood = -23.750405 Iteration 2: log pseudolikelihood = -22.643001 Iteration 3: log pseudolikelihood = -22.261069 Iteration 4: log pseudolikelihood = -22.166088 Iteration 5: log pseudolikelihood = -22.137801 Iteration 6: log pseudolikelihood = -22.132998 Iteration 7: log pseudolikelihood = -22.132852 Iteration 8: log pseudolikelihood = -22.132852 Probit regression Number of obs = 61 Wald chi2(9) = 20.06 Prob > chi2 = 0.0176 Log pseudolikelihood = -22.132852 Pseudo R2 = 0.2996 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0037112 .0156746 -0.24 0.813 -.0344329 .0270106 slope | -.6169751 .5202217 -1.19 0.236 -1.636591 .4026407 russia | .6238131 .5665524 1.10 0.271 -.4866092 1.734235 xplan | -.2910461 .3337348 -0.87 0.383 -.9451542 .363062 xplanmiss | .7795494 .7653834 1.02 0.308 -.7205744 2.279673 xloss | -.0018978 .0013603 -1.40 0.163 -.004564 .0007685 xlossmiss | -1.730799 .5182649 -3.34 0.001 -2.74658 -.7150189 xgain | -.2285504 .3228144 -0.71 0.479 -.8612551 .4041542 xgainmiss | -1.776234 1.210956 -1.47 0.142 -4.149665 .5971966 _cons | 1.296396 1.446287 0.90 0.370 -1.538275 4.131068 ------------------------------------------------------------------------------ Note: 4 failures and 0 successes completely determined. . probit expel accused slope xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -31.601316 Iteration 1: log pseudolikelihood = -23.989377 Iteration 2: log pseudolikelihood = -23.172355 Iteration 3: log pseudolikelihood = -22.864369 Iteration 4: log pseudolikelihood = -22.731206 Iteration 5: log pseudolikelihood = -22.698297 Iteration 6: log pseudolikelihood = -22.694112 Iteration 7: log pseudolikelihood = -22.694 Iteration 8: log pseudolikelihood = -22.694 Probit regression Number of obs = 61 Wald chi2(8) = 15.05 Prob > chi2 = 0.0581 Log pseudolikelihood = -22.694 Pseudo R2 = 0.2819 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0002084 .0157314 -0.01 0.989 -.0310415 .0306246 slope | -.5655839 .529985 -1.07 0.286 -1.604335 .4731677 xplan | -.4040194 .292036 -1.38 0.167 -.9763994 .1683606 xplanmiss | .4387647 .7002162 0.63 0.531 -.9336339 1.811163 xloss | -.0014581 .0011227 -1.30 0.194 -.0036586 .0007424 xlossmiss | -1.468744 .5086533 -2.89 0.004 -2.465686 -.4718015 xgain | -.2256915 .3274313 -0.69 0.491 -.867445 .416062 xgainmiss | -1.83172 1.234431 -1.48 0.138 -4.251161 .5877201 _cons | 1.920462 1.316681 1.46 0.145 -.6601854 4.50111 ------------------------------------------------------------------------------ Note: 3 failures and 0 successes completely determined. . probit expel accused ag xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -31.838796 Iteration 1: log pseudolikelihood = -25.170216 Iteration 2: log pseudolikelihood = -24.336404 Iteration 3: log pseudolikelihood = -24.010552 Iteration 4: log pseudolikelihood = -23.885454 Iteration 5: log pseudolikelihood = -23.822116 Iteration 6: log pseudolikelihood = -23.811753 Iteration 7: log pseudolikelihood = -23.811734 Probit regression Number of obs = 62 Wald chi2(8) = 13.85 Prob > chi2 = 0.0858 Log pseudolikelihood = -23.811734 Pseudo R2 = 0.2521 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0013086 .0140736 0.09 0.926 -.0262751 .0288923 ag | .1822808 .431969 0.42 0.673 -.6643629 1.028925 xplan | -.3638995 .311884 -1.17 0.243 -.975181 .247382 xplanmiss | .3674352 .7625291 0.48 0.630 -1.127094 1.861965 xloss | -.0015139 .0011318 -1.34 0.181 -.0037322 .0007043 xlossmiss | -1.359012 .4776682 -2.85 0.004 -2.295224 -.4227992 xgain | -.3326237 .3615243 -0.92 0.358 -1.041198 .3759509 xgainmiss | -2.239124 1.341251 -1.67 0.095 -4.867927 .3896789 _cons | 1.851503 1.476932 1.25 0.210 -1.043231 4.746238 ------------------------------------------------------------------------------ Note: 3 failures and 0 successes completely determined. . probit expel accused xplan xplanmiss xloss xlossmiss xgain xgainmiss, vce(robust) Iteration 0: log pseudolikelihood = -31.838796 Iteration 1: log pseudolikelihood = -25.239464 Iteration 2: log pseudolikelihood = -24.402512 Iteration 3: log pseudolikelihood = -24.073122 Iteration 4: log pseudolikelihood = -23.951971 Iteration 5: log pseudolikelihood = -23.891387 Iteration 6: log pseudolikelihood = -23.881212 Iteration 7: log pseudolikelihood = -23.881192 Probit regression Number of obs = 62 Wald chi2(7) = 13.38 Prob > chi2 = 0.0634 Log pseudolikelihood = -23.881192 Pseudo R2 = 0.2499 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0048408 .0142691 0.34 0.734 -.0231262 .0328077 xplan | -.3471976 .3249224 -1.07 0.285 -.9840339 .2896387 xplanmiss | .3852985 .7615782 0.51 0.613 -1.107367 1.877964 xloss | -.0015554 .0012606 -1.23 0.217 -.0040263 .0009154 xlossmiss | -1.393605 .500776 -2.78 0.005 -2.375108 -.4121017 xgain | -.3310612 .3623885 -0.91 0.361 -1.04133 .3792073 xgainmiss | -2.179919 1.329201 -1.64 0.101 -4.785105 .4252666 _cons | 1.839079 1.478346 1.24 0.213 -1.058426 4.736583 ------------------------------------------------------------------------------ Note: 3 failures and 0 successes completely determined. . . /*Control for type of deception.*/ . /*Add selfins coins unins joint complex.*/ . . probit expel accused slope ag lndistance russia selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -28.604135 Iteration 1: log pseudolikelihood = -25.644095 Iteration 2: log pseudolikelihood = -25.572481 Iteration 3: log pseudolikelihood = -25.572262 Probit regression Number of obs = 54 Wald chi2(9) = 8.35 Prob > chi2 = 0.4996 Log pseudolikelihood = -25.572262 Pseudo R2 = 0.1060 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0073659 .0209246 -0.35 0.725 -.0483773 .0336455 slope | -.8590631 .4545597 -1.89 0.059 -1.749984 .0318575 ag | .3603047 .8452298 0.43 0.670 -1.296315 2.016925 lndistance | -.0250665 .097432 -0.26 0.797 -.2160297 .1658967 russia | .1777063 .5644709 0.31 0.753 -.9286363 1.284049 coins | .2722497 .5518239 0.49 0.622 -.8093053 1.353805 unins | -.11928 .5064547 -0.24 0.814 -1.111913 .8733529 joint | .4606084 .7585095 0.61 0.544 -1.026043 1.94726 complex | .7661811 .458441 1.67 0.095 -.1323468 1.664709 _cons | -.8395291 1.039949 -0.81 0.420 -2.877791 1.198733 ------------------------------------------------------------------------------ . probit expel accused slope lndistance russia selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -28.604135 Iteration 1: log pseudolikelihood = -25.72936 Iteration 2: log pseudolikelihood = -25.660922 Iteration 3: log pseudolikelihood = -25.660702 Probit regression Number of obs = 54 Wald chi2(8) = 8.29 Prob > chi2 = 0.4058 Log pseudolikelihood = -25.660702 Pseudo R2 = 0.1029 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0021134 .0181894 -0.12 0.908 -.0377639 .0335372 slope | -.8089411 .43932 -1.84 0.066 -1.669993 .0521104 lndistance | -.0177 .0957621 -0.18 0.853 -.2053902 .1699902 russia | .1883558 .5604407 0.34 0.737 -.9100878 1.286799 coins | .2043017 .5057628 0.40 0.686 -.7869752 1.195579 unins | -.1054328 .513346 -0.21 0.837 -1.111573 .9007069 joint | .7225486 .5189642 1.39 0.164 -.2946026 1.7397 complex | .745411 .4461536 1.67 0.095 -.129034 1.619856 _cons | -.8572035 1.037798 -0.83 0.409 -2.89125 1.176843 ------------------------------------------------------------------------------ . probit expel accused slope lndistance selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -28.604135 Iteration 1: log pseudolikelihood = -25.771483 Iteration 2: log pseudolikelihood = -25.711897 Iteration 3: log pseudolikelihood = -25.71176 Probit regression Number of obs = 54 Wald chi2(7) = 8.22 Prob > chi2 = 0.3134 Log pseudolikelihood = -25.71176 Pseudo R2 = 0.1011 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | -.0020105 .0181259 -0.11 0.912 -.0375366 .0335156 slope | -.8164722 .4410982 -1.85 0.064 -1.681009 .0480644 lndistance | -.0269812 .0876509 -0.31 0.758 -.1987739 .1448115 coins | .196364 .5055368 0.39 0.698 -.79447 1.187198 unins | -.1099818 .5138978 -0.21 0.831 -1.117203 .8972394 joint | .668843 .5183425 1.29 0.197 -.3470896 1.684776 complex | .7395433 .4419601 1.67 0.094 -.1266826 1.605769 _cons | -.6285066 .7740513 -0.81 0.417 -2.145619 .8886062 ------------------------------------------------------------------------------ . probit expel accused slope russia selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -30.861541 Iteration 1: log pseudolikelihood = -28.570517 Iteration 2: log pseudolikelihood = -28.517179 Iteration 3: log pseudolikelihood = -28.517052 Probit regression Number of obs = 58 Wald chi2(7) = 7.05 Prob > chi2 = 0.4233 Log pseudolikelihood = -28.517052 Pseudo R2 = 0.0760 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0032883 .0181172 0.18 0.856 -.0322208 .0387973 slope | -.5778192 .4123212 -1.40 0.161 -1.385954 .2303155 russia | .1820745 .4576662 0.40 0.691 -.7149348 1.079084 coins | .2287447 .4890183 0.47 0.640 -.7297136 1.187203 unins | .0764694 .451847 0.17 0.866 -.8091344 .9620732 joint | .6937877 .4965302 1.40 0.162 -.2793936 1.666969 complex | .7412298 .434706 1.71 0.088 -.1107783 1.593238 _cons | -1.154399 .678917 -1.70 0.089 -2.485052 .1762542 ------------------------------------------------------------------------------ . probit expel accused slope selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -30.861541 Iteration 1: log pseudolikelihood = -28.63852 Iteration 2: log pseudolikelihood = -28.595059 Iteration 3: log pseudolikelihood = -28.59499 Probit regression Number of obs = 58 Wald chi2(6) = 6.94 Prob > chi2 = 0.3268 Log pseudolikelihood = -28.59499 Pseudo R2 = 0.0734 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0038751 .0180509 0.21 0.830 -.031504 .0392542 slope | -.5702238 .4118648 -1.38 0.166 -1.377464 .2370163 coins | .2431867 .4883065 0.50 0.618 -.7138765 1.20025 unins | .0506765 .4538464 0.11 0.911 -.838846 .9401991 joint | .6461917 .4982028 1.30 0.195 -.3302678 1.622651 complex | .7393006 .4316856 1.71 0.087 -.1067875 1.585389 _cons | -1.008177 .6220431 -1.62 0.105 -2.227359 .2110055 ------------------------------------------------------------------------------ . probit expel accused ag selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -31.112863 Iteration 1: log pseudolikelihood = -29.794021 Iteration 2: log pseudolikelihood = -29.784796 Iteration 3: log pseudolikelihood = -29.784793 Probit regression Number of obs = 59 Wald chi2(6) = 2.52 Prob > chi2 = 0.8661 Log pseudolikelihood = -29.784793 Pseudo R2 = 0.0427 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0105223 .0200719 0.52 0.600 -.028818 .0498626 ag | -.0740748 .8073543 -0.09 0.927 -1.65646 1.508311 coins | .2510715 .5298132 0.47 0.636 -.7873433 1.289486 unins | .0215861 .4360857 0.05 0.961 -.8331262 .8762985 joint | .6097457 .7602354 0.80 0.423 -.8802882 2.09978 complex | .6516288 .4558596 1.43 0.153 -.2418395 1.545097 _cons | -1.360485 .5433073 -2.50 0.012 -2.425348 -.2956226 ------------------------------------------------------------------------------ . probit expel accused selfins coins unins joint complex, vce(robust) note: selfins != 0 predicts failure perfectly selfins dropped and 3 obs not used Iteration 0: log pseudolikelihood = -31.112863 Iteration 1: log pseudolikelihood = -29.797038 Iteration 2: log pseudolikelihood = -29.789236 Iteration 3: log pseudolikelihood = -29.789235 Probit regression Number of obs = 59 Wald chi2(5) = 2.39 Prob > chi2 = 0.7933 Log pseudolikelihood = -29.789235 Pseudo R2 = 0.0425 ------------------------------------------------------------------------------ | Robust expel | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- accused | .0094649 .0174194 0.54 0.587 -.0246766 .0436064 coins | .2628785 .4958354 0.53 0.596 -.7089411 1.234698 unins | .0198474 .4411668 0.04 0.964 -.8448235 .8845184 joint | .5505268 .5168727 1.07 0.287 -.462525 1.563579 complex | .6554821 .4471576 1.47 0.143 -.2209307 1.531895 _cons | -1.370318 .5077607 -2.70 0.007 -2.365511 -.3751255 ------------------------------------------------------------------------------ . . log close log: D:\research\pripiski\dataset\probits.log log type: text closed on: 3 Dec 2010, 14:37:12 --------------------------------------------------------------------------------------------------------------------------