[R] ivprobit postestimation -- Postestimation tools for ivprobit
Description
The following postestimation commands are of special interest after ivprobit:
Command Description
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estat classification report various summary statistics, including the classification table
lroc compute area under ROC curve and graph the curve
lsens graph sensitivity and specificity versus probability cutoff
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These commands are not appropriate after the two-step estimator or the svy prefix.
The following standard postestimation commands are also available:
Command Description
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contrast contrasts and ANOVA-style joint tests of estimates
(1) estat ic Akaike's and Schwarz's Bayesian information criteria (AIC and BIC)
estat summarize summary statistics for the estimation sample
estat vce variance-covariance matrix of the estimators (VCE)
estat (svy) postestimation statistics for survey data
estimates cataloging estimation results
(2) forecast dynamic forecasts and simulations
hausman Hausman's specification test
lincom point estimates, standard errors, testing, and inference for linear combinations of
coefficients
(3) lrtest likelihood-ratio test; not available with two-step estimator margins marginal means, predictive margins, marginal effects, and average marginal effects
marginsplot graph the results from margins (profile plots, interaction plots, etc.)
nlcom point estimates, standard errors, testing, and inference for nonlinear combinations of
coefficients
predict predictions, residuals, influence statistics, and other diagnostic measures
predictnl point estimates, standard errors, testing, and inference for generalized predictions
pwcompare pairwise comparisons of estimates
(1) suest seemingly unrelated estimation
test Wald tests of simple and composite linear hypotheses
testnl Wald tests of nonlinear hypotheses
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(1) estat ic and suest are not appropriate after ivprobit, twostep.
(2) forecast is not appropriate with svy estimation results or after ivprobit, twostep.
(3) lrtest is not appropriate with svy estimation results.
statistic Description
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Main
xb linear prediction; the default
stdp standard error of the linear prediction
pr probability of a positive outcome; not available with two-step estimator
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These statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only for
the estimation sample.
Menu for predict
Statistics > Postestimation > Predictions, residuals, etc.
Options for predict
+------+
----+ Main +-----------------------------------------------------------------------------------------------------
xb, the default, calculates the linear prediction.
stdp calculates the standard error of the linear prediction.
pr calculates the probability of a positive outcome. pr is not available with the two-step estimator.
rules requests that Stata use any rules that were used to identify the model when making the prediction. By
default, Stata calculates missing for excluded observations. rules is not available with the two-step
estimator.
asif requests that Stata ignore the rules and the exclusion criteria and calculate predictions for all
observations possible using the estimated parameters from the model. asif is not available with the two-step
estimator.
scores, not available with twostep, calculates equation-level score variables.
For models with one endogenous regressor, four new variables are created.
The first new variable will contain the first derivative of the log likelihood with respect to the probit
equation.
The second new variable will contain the first derivative of the log likelihood with respect to the
reduced-form equation for the endogenous regressor.
The third new variable will contain the first derivative of the log likelihood with respect to
atanh(rho).
The fourth new variable will contain the first derivative of the log likelihood with respect to
ln(sigma).
For models with j endogenous regressors, j + {(j + 1)(j + 2)}/2 new variables are created.
The first new variable will contain the first derivative of the log likelihood with respect to the probit
equation.
The second through (j + 1)th new variables will contain the first derivatives of the log likelihood with
respect to the reduced-form equations for the endogenous variables in the order they were specified when
ivprobit was called.
The remaining score variables will contain the partial derivatives of the log likelihood with respect to
s[2,1], s[3,1], ..., s[j+1,1], s[2,2], ..., s[j+1,2], ..., s[j+1,j+1], where s[m,n] denotes the (m,n)
element of the Cholesky decomposition of the error covariance matrix.
各位，stata14更新后，升级到stata14.2 (stata14.1也有这个问题) margins 命令好像出现幺蛾子了！！我对比了一下stata提供的ivprobit中的例子
发现两个重大区别：
第一，margins 估计出来的系数不一样（值跟原来的不一样了，有的变大，有的变小）
第二，ivprobit中的工具变量male_educ居然还有边际效应！但是注意截图中的文字，“male edu has no effect because it appears only as an instrument”，并且求边际效应， male_educ作为othe_inc的工具变量，理论上也不需要，也求不出来它的边际效应吧？！还请各位牛人指点！详细内容见截图
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