Linear Regression MT#

Set of procedures for estimating single equations or a simultaneous system of equations in GAUSS.


The Linear Regression MT application module is a set of procedures for estimating single equations or a simultaneous system of equations. It allows constraints on coefficients, calculates het-con standard errors, and includes two-stage least squares, three-stage least squares, and seemingly unrelated regression. It is thread-safe and takes advantage of structures found in later versions of GAUSS.


If you’re interested in purchasing LRMT Please contact us to request pricing and installation information.

If you already own LRMT , you can use the GAUSS Package Manager for quick download and installation.

Requires GAUSS/GAUSS Engine/GAUSS Light v8.0 or higher.

Key Features#

Provides convenient and comprehensive tools for linear regression including:

  • Heteroskedastic-consistent standard errors.

  • Performs both influence and collinearity diagnostics inside the ordinary least squares routine (OLS).

  • All regression procedures can be run at a specified data range.

  • Performs multiple linear hypothesis testing with any form.

  • Estimates regressions with linear restrictions.

  • Accommodates large data sets with multiple variables.

  • Stores all important test statistics and estimated coefficients in an efficient manner.

Thorough Documentation#

The comprehensive user’s guide includes both a well-written tutorial and an informative reference section. Additional topics are included to enrich the usage of the procedures. These include:

  • Joint confidence region for beta estimates.

  • Tests for heteroskedasticity.

  • Tests of structural change.

  • Using ordinary least squares to estimate a translog cost function.

  • Using seemingly unrelated regression to estimate a system of cost share equations.

  • Using three-stage least squares to estimate Klein’s Model I.