Linear Regression MT

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