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