Title
Amemiya's Generalized Least Squares and Tests of Overidentification in Simultaneous Equation Models with Qualitative or Limited Dependent Variables
Publisher
Center for Economic Research, Department of Economics, University of Minnesota
Abstract
Amemiya's generalized least squares method for the estimation of simultaneous equation models 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 Amemiya's generalized least squares procedure. Amemiya's procedure is shown to be a minimum chi-square
method. The Amemiya procedure is valuable both for efficient estimation and for model evaluation
of such models.
Previously Published Citation
Lee, L., (1991), "Amemiya's Generalized Least Squares and Tests of Overidentification in Simultaneous Equation Models with Qualitative or Limited Dependent Variables", Discussion Paper No. 262, Center for Economic Research, Department of Economics, University of Minnesota.
Suggested Citation
Lee, Lung-Fei.
(1991).
Amemiya's Generalized Least Squares and Tests of Overidentification in Simultaneous Equation Models with Qualitative or Limited Dependent Variables.
Center for Economic Research, Department of Economics, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/55561.