Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results

29 Pages Posted: 26 Apr 2000 Last revised: 23 May 2022

See all articles by David A. Belsley

David A. Belsley

Boston College; National Bureau of Economic Research (NBER)

Kent D. Wall

Naval Postgraduate School

Date Written: July 1976

Abstract

This working paper provides some preliminary results on the computational feasibility of nonlinear full information maximum likelihood (NECML) estimation. Severa1 of the test cases presented were also subjected to nonlinear three stage least square (NLBSLS) estimation in order to illustrate the relative performance of the two estimation techniques. In addition, certain other aspects central to practical implementation are highlighted. These include the effect of various computers on the efficiency of the code, as well as the relative merits of numerical and analytical generation of gradient information. Broadly speaking, NLFIML appears competitive in cost and superior in statistical properties to NL3SLS.

Suggested Citation

Belsley, David A. and Wall, Kent D., Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results (July 1976). NBER Working Paper No. w0142, Available at SSRN: https://ssrn.com/abstract=225163

David A. Belsley (Contact Author)

Boston College ( email )

Department of Economics
Chestnut Hill, MA 02167
United States
617-552-3676 (Phone)
617-552-2308 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Kent D. Wall

Naval Postgraduate School

1522 Cunningham Road
Monterey, CA 93943-5201
United States

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