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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, LINUX, Solaris, and Mac.
Requirements : GAUSS/GAUSS Light version 8.0 or higher.