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Applications of Differential Geometry to Econometrics - Paul Marriott

Applications of Differential Geometry to Econometrics

By: Paul Marriott (Editor), Mark Salmon (Editor)

Hardcover Published: 31st August 2000
ISBN: 9780521651165
Number Of Pages: 336

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Although geometry has always aided intuition in econometrics, it is only recently that Differential Geometry has become a standard tool in the analysis of statistical models, offering a deeper appreciation of existing methodologies and highlighting the essential issues which can be hidden in an algebraic development of a problem. This volume is the first to apply these techniques to econometrics. An introductory chapter provides a brief tutorial for those unfamiliar with the tools of Differential Geometry. The topics covered in the following chapters demonstrate the power of the geometric method to provide practical solutions and insight into problems of econometric inference.

Industry Reviews

"I strongly recommend [this book] for computational minded statisticians and economists." J. Statist. Comput. Simul.

Introduction
An introduction to differential geometry
Orthogonal projection, nested models and encompassing
Exact properties of the maximum likelihood estimator in exponential regression models
Empirical likelihood estimation and inference
Measuring earnings differentials with frontier functions and Rao distances
First order predictive densities
An alternative comparisom of classical tests: assessing the effects of curvature
Testing for unit roots in AR and MA Models
Efficiency and robustness in a geometrical perspective
Paramaterisations and transformations; An elementary introduction to Amari's differential geometry
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780521651165
ISBN-10: 0521651166
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 336
Published: 31st August 2000
Publisher: CAMBRIDGE UNIV PR
Country of Publication: GB
Dimensions (cm): 22.86 x 15.24  x 2.24
Weight (kg): 0.66

Earn 444 Qantas Points
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