**[TE] eteffects postestimation** -- Postestimation tools for eteffects

__Postestimation commands__

The following postestimation command is of special interest after
**eteffects**:

Command Description
-------------------------------------------------------------------------
**estat endogenous** perform tests of endogeneity
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The following standard postestimation commands are available after
**eteffects**:

Command Description
-------------------------------------------------------------------------
**estat summarize** summary statistics for the estimation sample
**estat vce** variance-covariance matrix of the estimators (VCE)
**estimates** cataloging estimation results
**hausman** Hausman's specification test
**lincom** point estimates, standard errors, testing, and
inference for linear combinations of coefficients
**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
**test** Wald tests of simple and composite linear hypotheses
**testnl** Wald tests of nonlinear hypotheses
-------------------------------------------------------------------------

__Syntax for predict__

**predict** [*type*] {*stub****** | *newvar* | *newvarlist*} [*if*] [*in*] [**,** *statistic*
__tle__**vel**]

**predict** [*type*] {*stub****** | *newvarlist*} [*if*] [*in*] **,** __sc__**ores**

*statistic* Description
-------------------------------------------------------------------------
Main
**te** treatment effect; the default
__cm__**ean** conditional mean at treatment level
**ps** propensity score
**xb** linear prediction
**psxb** linear prediction for propensity score
__xbt__**otal** linear prediction, using residuals from treatment model
-------------------------------------------------------------------------
Specify one new variable with **te**; specify one or two new variables with
**cmean**, **ps**, and **xb**.

__Menu for predict__

**Statistics > Postestimation**

__Description for predict__

**predict** creates a new variable containing predictions such as treatment
effects, conditional means, propensity scores, and linear predictions.

__Options for predict__

+------+
----+ Main +-------------------------------------------------------------

**te**, the default, calculates the treatment effect.

**cmean** calculates the conditional mean for the control group. To also
obtain the conditional mean for the treatment group, specify two
variables. If you want the conditional mean for only the treatment
group, specify the **tlevel** option.

**ps** calculates the probability of being in the control group. To also
obtain the probability of being in the treatment group, specify two
variables. If you want the probability of being in the treatment
group only, specify the **tlevel** option.

**xb** calculates the linear prediction for the control group. To also
obtain the linear prediction for the treatment group, specify two
variables. If you want the linear prediction for only the treatment
group, specify the **tlevel** option.

**psxb** calculates the linear prediction for the propensity score.

**xbtotal** calculates the linear prediction for the control group, including
the residuals from the treatment model as regressors. To also obtain
the linear prediction for the treatment group, specify two variables.
If you want the linear prediction, including the residuals from the
treatment model as regressors, only for the treatment group, specify
the **tlevel** option.

**tlevel** specifies that the statistic be calculated for the treatment
group; the default is to calculate the statistic for the control
group.

**scores** calculates the score variables. For **eteffects**, this is the same as
the residuals in the moment conditions used by the generalized method
of moments (see **[G] gmm**). For the average treatment effect, the
average treatment effect on the treated, and the potential-outcome
means, parameter-level scores are computed. For the auxiliary
equations, equation-level scores are computed.

__Syntax for estat__

**estat** __endog__**enous**

__Menu for estat__

**Statistics > Postestimation**

__Description for estat__

**estat endogenous** performs a Wald test to determine whether the estimated
correlations between the treatment-assignment and potential-outcome
models are different from zero. The null hypothesis is that the
correlations are jointly zero. Rejection of the null hypothesis suggests
endogeneity.

__Examples__

Setup
**. webuse cattaneo2**
**. eteffects (bweight i.prenatal1 i.mmarried mage i.fbaby)** **(mbsmoke**
**i.mmarried mage i.fbaby medu fedu)**

Test for endogeneity
**. estat endogenous**

Compute the estimated treatment probabilities
**. predict prob1 prob2, ps**

Summarize the estimated treatment probabilities
**. summarize prob1 if mbsmoke==1, detail**

Summarize the estimated control probabilities
**. summarize prob2 if mbsmoke==0, detail**