ivprobit结果解读 - Stata专版

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cfm2013 发表于 2015-7-9 17:06:58 |AI写论文

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我做了ivprobit分析关于结果中交互项的解释，我想请教大家一下
Iteration 0: log likelihood = -3084.9875
Iteration 1: log likelihood = -2968.2453
Iteration 2: log likelihood = -2968.1722
Iteration 3: log likelihood = -2968.1722

Fitting full model

Iteration 0: log pseudolikelihood = -11395.938
Iteration 1: log pseudolikelihood = -11387.774
Iteration 2: log pseudolikelihood = -11387.6
Iteration 3: log pseudolikelihood = -11387.6

Probit model with endogenous regressors       Number of obs    =    4,738
                                             Wald chi2(9)    =    241.01
Log pseudolikelihood = -11387.6             Prob > chi2    =    0.0000

------------------------------------------------------------------------------
         |             Robust
         |    Coef. Std. Err.    z P>|z|    [95% Conf. Interval]
-------------+----------------------------------------------------------------
Dependent |
children |    -0.126    0.024 -5.327 0.000    -0.172    -0.080
      adl |    -0.085    0.022 -3.924 0.000    -0.128    -0.043
      Sex |    0.033    0.043 0.775 0.439    -0.051    0.118
   Rural |    0.078    0.042 1.834 0.067    -0.005    0.161
   Ethnic |    0.760    0.100 7.608 0.000       0.564    0.956
   Income |    0.008    0.001 10.719 0.000       0.006    0.009
schooling |    -0.004    0.005 -0.727 0.467    -0.014    0.007
      age |    0.014    0.004 3.951 0.000       0.007    0.021
Pchild_1 |    0.054    0.015 3.738 0.000       0.026    0.083
   _cons |    -0.814    0.304 -2.679 0.007    -1.409    -0.218
-------------+----------------------------------------------------------------
children    |
      adl |    -0.006    0.030 -0.198 0.843    -0.065    0.053
      Sex |    -0.050    0.046 -1.097 0.273    -0.140    0.039
   Rural |    0.328    0.046 7.167 0.000       0.239    0.418
   Ethnic |    0.155    0.125 1.242 0.214    -0.090    0.399
   Income |    -0.002    0.001 -2.339 0.019    -0.003    -0.000
schooling |    -0.006    0.006 -1.036 0.300    -0.017    0.005
      age |    0.011    0.005 2.309 0.021       0.002    0.020
Pchild_1 |    0.953    0.007  138.906 0.000       0.940    0.967
   policy |    -4.312    0.090  -47.817 0.000    -4.489    -4.135
   _cons |    3.682    0.440 8.374 0.000       2.820    4.543
-------------+----------------------------------------------------------------
   /athrho |    0.161    0.040 4.026 0.000       0.083    0.239
/lnsigma |    0.360    0.015 23.630 0.000       0.330    0.390
-------------+----------------------------------------------------------------
希望大家帮我解释一下Pchild 这个交互项，还有需要进一步做弱工具变量的检验吗
      rho |    0.159    0.039                      0.082    0.235
   sigma |    1.433    0.022                      1.391    1.476
------------------------------------------------------------------------------
Instrumented:  children
Instruments: adl Sex Rural Ethnic Income schooling age Pchild_1 policy
------------------------------------------------------------------------------
Wald test of exogeneity (/athrho = 0): chi2(1) = 16.21 Prob > chi2 = 0.0001