NONLINEAR SIMULTANEOUS EQUATIONS: ESTIMATION AND PREDICTION.
Abstract
The small sample properties of certain estimators of the coefficients of systems of simultaneous nonlinear equations are investigated. Sampling experiments are used in connection with two specific nonlinear models. The estimating methods investigated comprise direct least squares, various forms of two-stage least squares and full-information maximum likelihood. The relative performances of the various methods are evaluated on the basis of informal comparisons of their respective mean absolute errors and root mean square errors and also by more formal tests of significance. Direct least squares is found to be, as expected, the worst estimating method. The other two methods are rather more comparable with full-information maximum likelihood holding the edge for both theoretical and experimental reasons. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 21, 1965
- Accession Number
- AD0624254
Entities
People
- Richard E. Quandt
- Stephen M. Goldfeld
Organizations
- Princeton University