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This textbook is intended for graduate students and professionals who have an interest in linear and nonlinear simultaneous equation models. These models arise in a great many settings in econometrics. The author's aim is to present a readable account, starting from an introduction to the general linear structural econometric model. From there, the book covers the identification problem, maximum likelihood methods, two and three stage least square methods, the general nonlinear model, and more advanced topics such as the general nonlinear simultaneous equations model. The reader is assumed to have a basic background in probability theory but otherwise this account is self-contained.
The mathematical problems encountered in nonlinear econometrics are not easily treated by the analytical methods most commonly acquired by students, who have learned about probability and inference through the use of density functions. Few students enter graduate programs in economics prepared to approach probability theory in measure theoretic terms. Dhrymes (economics, Columbia U.) addresses the need for stronger analytic skills in this text, appropriate for graduate students and professionals in nonstandard contemporary econometrics. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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