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GMM and nonlinear regression

Generalized method of moments (GMM) Updated

  • 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 New

  • View and run all postestimation features for your command
  • Automatically updated as estimation commands are run
Watch Postestimation Selector.

Additional resource

See tests, predictions, and effects.

See New in Stata 14 for more about what was added in Stata 14.

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