Amemiya‘s generalized least squares and tests of overidentification in simultaneous equation models with qualitative or limited dependent variables

Abstract

Amemiya's generalized least squares method for the estimation of simultaneous equation modeis with qualitative or limited dependent variables is known to be efficient relative to many popular two stage estimators. This note points out that test statistics for overidentification restrictions can be obtained as by-products of Amerniya's generalized least squares procedure. Amemiya's procedure is shown to be a minimum chisquare method. The Amemiya procedure is valuable both for efficient estimation and for model evaluation of such models.

Keywords:

• Key Words And Phrases: Amemiya's Gls
• Minimum Distance Method
• Minimum Chi-Square
• Simultaneous Equation Models
• Qualrtative Dependent Variables
• Limited Dependent Variables
• Overidentification Tests