GMM Toolbox for Matlab

Kostas N. Kyriakoulis

GMMTBX is a set of MATLAB® functions that perform GMM estimation and testing of linear/nonlinear time series and cross section models. One of its major features is that it includes a Graphical User Interface that controls all the functions of the toolbox. This provides a friendly, yet powerful interface for the end-user. In addition, all the functions are stand alone and can be simply executed from Matlab's command prompt.

The GMMTBX requires the use of the Matlab® Optimization and Statistics Toolboxes. All the functions, apart from the GUI, are compatible with Matlab version 5.0 or higher; the GUI is compatible with Matlab version 6.0 or higher.

DOWNLOAD

The GMM toolbox
UPDATE #1 (Feb/01/2005): All GUI windows are now resizable. Just click/drag on any of the window corners to resize it.
UPDATE #2 (Feb/08/2005): Corrected a problem that was resulting to error messages during the execution of the GUI.

 

Download a zip file that contains:
(i) A Matlab function for calculating the CBAPM moments and their gradient (cbapm.m)
(ii) A Matlab function that calculates a set of linear restrictions on the CBAPM parameters (cbapmtest.m)

Download the dataset used for the CBAPM estimation

HELP & EXAMPLES

Study all the features of the program using the Consumption Based Asset Pricing Model (Page will load in new window)

How this thing works? Documentation/help files (Page will load in new window)

FEATURES

  1. Graphical User Interface (GUI), for a user friendly environment that can control both estimation and testing

  2. GMM estimation for both unrestricted and restricted models (linear, nonlinear, or "bounded parameters" restrictions)

  3. Continuous Updated GMM

  4. Variance, std. deviation, and 95% confidence intervals of the parameters

  5. J-test for testing the validity of the moment conditions

  6. Wald, LM, and D tests for both linear and nonlinear constraints

  7. Structural stability tests in the case of known break-point

  8. Sup-, AV-, and Exp- structural stability tests in the case of an unknown break-point

  9. Moments' long-run covariance matrix includes : Serially Uncorrelated, HAC with Bartlett weights, and HAC with Parzen weights

  10. Bandwidth's value: Provided by the user or automatically calculated using Newey and West's method of bandwidth selection


Last Update: November 21, 2007