The behavior of trust-region methods in FIML estimation
This paper presents a Monte-Carlo study on the practical reliability of numerical algorithms for FIML-estimation in nonlinear econometric models. The performance of different techniques of Hessian approximation in trust-region algorithms is compared regarding their "robustness" against "bad" starting points and their "global" and "local" convergence speed, i.e. the gain in the objective function, caused by individual iteration steps far off from and near to the optimum. Concerning robustness and global convergence speed the crude GLS-type Hessian approximations performed best, efficiently exploiting the special structure of the likelihood function. But, concerning local speed, general purpose techniques were strongly superior. So, some appropriate mixtures of these two types of approximations turned out to be the only techniques to be recommended.
|Date of creation:||1986|
|Date of revision:||1987|
|Publication status:||Published in Computing 38.38(1987): pp. 89-100|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
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- Calzolari, Giorgio & Panattoni, Lorenzo & Weihs, Claus, 1987. "Computational efficiency of FIML estimation," Journal of Econometrics, Elsevier, vol. 36(3), pages 299-310, November.
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- Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "A Simulation Study on FIML Covariance Matrix," MPRA Paper 28804, University Library of Munich, Germany.
- Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665 National Bureau of Economic Research, Inc.
- Belsley, David A., 1980. "On the efficient computation of the nonlinear full-information maximum-likelihood estimator," Journal of Econometrics, Elsevier, vol. 14(2), pages 203-225, October.
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