Linear Regression MT

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.

Features

• Calculates heteroskedastic-consistent standard errors, and 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


• Both three-stage least squares and seemingly unrelated regression can be estimated iteratively


• 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

Platform: Windows, Mac, and Linux.

Requirements: GAUSS/GAUSS Light version 8.0 or higher.