Comparative methods of computing maximum likelihood estimates for non-linear econometric systems

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" Comparative methods of computing maximum likelihood estimates for non-linear econometric systems "
Chong, Yock Yoon

Document Type	:	Latin Dissertation
Record Number	:	1103295
Doc. No	:	TLets788192
Main Entry	:	Chong, Yock Yoon
Title & Author	:	Comparative methods of computing maximum likelihood estimates for non-linear econometric systems\ Chong, Yock Yoon
College	:	London School of Economics and Political Science (LSE)
Date	:	1981
student score	:	1981
Degree	:	Ph.D.
Abstract	:	This research is mainly concerned with numerical optimisation techniques applied to general non-linear econometric simultaneous equations systems. The method of estimation used is maximum likelihood. An estimation program which applies gradient-type procedures, specifically the Berndt-Hall-Hall-Hausman and Gill-Murray' Pitfield methods, is developed. This program allows the estimation of a general small-to-medium size model which is non-linear in parameters, variables or both. In the course of program development, a general differentiation program is written which will differentiate a set of econometric equations and thus provide the analytical gradients for the optimisation procedures. A comparative study has been made of the relative efficiency of the two methods by running a set of simulated non-linear models and also using a small macro- economic model of the British Economy specified by David F. Hendry. To improve the efficiency of the estimation program in terms of computing time, the Berndt-Hall-Hall-Hausman method was implemented on the ICL Distributed Array Processor (DAP)’ which employs parallel computations. The DAP runs show that for a model with a large sample size, the DAP is approximately 30 times faster than the conventional computer CDC 7600, but that for the present algorithm, the latter is a more efficient alternative for small sample sizes.
Subject	:	HB Economic Theory
	:	QA Mathematics
Added Entry	:	London School of Economics and Political Science (LSE)