Generalized method of moments (GMM)

Linear and nonlinear models

Single- and multiple-equation models

One-step, two-step, and iterative estimators

Cross-sectional, time-series, and panel models

Easily specify panel-style instruments

Interactive and programmable versions

Robust, cluster–robust, bootstrap, jackknife, and HAC standard errors

 

Nonlinear least-squares regression

Fit an arbitrary nonlinear function

Enter the function directly or write a program

Built-in exponential, logistic, and Gompertz functions

Robust, cluster–robust, bootstrap, jackknife, and HAC standard errors

 

Nonlinear seemingly unrelated regression

Fit a system of nonlinear equations

Enter the the system directly or write a program

Two-step or iterative feasible generalized nonlinear least squares

Robust, cluster–robust, bootstrap, and jackknife standard errors

 

Postestimation Selector*

View and run all postestimation features for your command

Automatically updated as estimation commands are run

Watch Postestimation Selector.

 

Additional resource

In the spotlight: The generalized method of moments