FULL INFORMATION MAXIMUM LIKELIHOOD ESTIMATION WITH AUTOCORRELATED ERRORS: A NUMERICAL APPROACH

Date

1991

Author

Tansel, Aysıt
BOYCE, Richard

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

31
views

14
downloads

Cite This

The purpose of this work is efficient estimation. That is, we seek to incorporate all a priori knowledge into our model building and estimation technique. The model considered is a nonlinear simultaneous equation model. The disturbances are assumed to follow a first order autoregressive process. The method of estimation is full information maximum likelihood. We focus on specifying a covariance structure and the associated likelihood function, whereby initial observations are incorporated. An algorithm for computation is developed within the gradient methods. The unique feature of the algorithm is that the likelihood function is numerically concentrated with respect to the elements of the variance-covariance matrix and the autoregressive coefficients.

URI

https://hdl.handle.net/11511/110818

Collections

Department of Economics, Article