[回归分析求助] IVprobit结果解读，是工具变量有问题还是不存在内生性？ [推广有奖]

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发表于 2018-5-11 21:22:37 |AI写论文

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ivprobit y S2 S3 S4 S5 S6 S7 S8 (S1 = S11),nolog

Probit model with endogenous regressors       Number of obs    =    1,776
Wald chi2(8)    =    84.49
Log likelihood = -3493.7969                   Prob > chi2    =    0.0000

Coef. Std. Err.    z P>z    [95% Conf. Interval]

S1 .2058583 .1645136    1.25 0.211 -.1165824 .5282989
S2 .0072907 .0326347    0.22 0.823 -.0566722 .0712536
S3 -.1890619 .0314669 -6.01 0.000 -.2507359 -.1273879
S4 -.0282632 .0379172 -0.75 0.456 -.1025796 .0460532
S5 .2290292 .0460846    4.97 0.000    .1387051 .3193533
S6 .3391631 .1229897    2.76 0.006    .0981077 .5802185
S7 -.0491498 .0343376 -1.43 0.152 -.1164503 .0181507
S8 -.118654 .0791566 -1.50 0.134 -.2737982 .0364902
_cons .6308483 .035727 17.66 0.000    .5608245    .700872

corr(e.S1,e.y) .071777 .1585639                   -.235957    .366427
sd(e.S1) .985167    .01653                   .9532957 1.018104

Instrumented:  S1
Instruments: S2 S3 S4 S5 S6 S7 S8 S11

Wald test of exogeneity (corr = 0): chi2(1) = 0.20       Prob > chi2 = 0.6519

.  ivprobit y S2 S3 S4 S5 S6 S7 S8 (S1 = S11),first twostep
Checking reduced-form model...
first-stage regression

Source       SS          df    MS    Number of obs =    1,776
F(8, 1767)    =    10.13
Model 79.0340344       8 9.8792543 Prob > F       = 0.0000
Residual 1723.70386    1,767  .975497374 R-squared    = 0.0438
Adj R-squared = 0.0395
Total 1802.73789    1,775  1.01562698 Root MSE       = .98767

S1    Coef. Std. Err.    t P>t    [95% Conf. Interval]

S11 1.032884 .1166124    8.86 0.000    .8041711 1.261597
S2 .0200373 .0234564    0.85 0.393    -.025968 .0660426
S3 -.0025291 .0234129 -0.11 0.914    -.048449 .0433908
S4 .0077004 .0234962    0.33 0.743 -.0383828 .0537836
S5 -.0292183 .0241588 -1.21 0.227    -.076601 .0181645
S6 -.0218002 .0234786 -0.93 0.353 -.0678488 .0242485
S7    .018477 .0234502    0.79 0.431    -.027516 .0644701
S8 .0093036 .0233553    0.40 0.690 -.0365034 .0551105
_cons -.0001952 .0234384 -0.01 0.993 -.0461652 .0457747

Two-step probit with endogenous regressors       Number of obs =    1,776
Wald chi2(8) =    86.57
Prob > chi2    =    0.0000

Coef. Std. Err.    z P>z    [95% Conf. Interval]

S1 .2063906 .1627429    1.27 0.205 -.1125796 .5253608
S2 .0073096 .0327276    0.22 0.823 -.0568353 .0714544
S3 -.1895508 .0316613 -5.99 0.000 -.2516058 -.1274959
S4 -.0283363 .0379894 -0.75 0.456 -.1027942 .0461216
S5 .2296215 .0465589    4.93 0.000    .1383677 .3208752
S6 .3400402 .1231605    2.76 0.006    .09865 .5814304
S7 -.0492769 .0343673 -1.43 0.152 -.1166356 .0180818
S8 -.1189608 .0793515 -1.50 0.134    -.274487 .0365653
_cons .6324796 .0353165 17.91 0.000    .5632606 .7016986

Instrumented:  S1
Instruments: S2 S3 S4 S5 S6 S7 S8 S11

Wald test of exogeneity: chi2(1) = 0.20                Prob > chi2 = 0.6520