Format:
1 Online-Ressource (viii, 324 pages)
,
digital, PDF file(s)
ISBN:
9780511660092
Content:
Although geometry has always aided intuition in econometrics, more recently 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. Originally published in 2000, this volume was an early example of the application of 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
Content:
An introduction to differential geometry in econometrics / Paul Marriott and Mark Salmon -- Nested models, orthogonal projection and encompassing / Maozu Lu and Grayham E. Mizon -- Exact properties of the maximum likelihood estimator in exponential regression models: a differential geometric approach / Grant Hillier and Ray O'Brien -- Empirical likelihood estimation and inference / Richard J. Smith -- Efficiency and robustness in the geometrical perspective / Russsell Davidson -- Measuring earnings differentials with frontier functions and Rao distances / Uwe Jensen -- First-order optimal predictive densities / J.M. Corcuera and F. Giummolé -- An alternative comparison of classical texts: assessing the effects of curvature / Kees Jan van Garderen -- Testing for unit roots in AR and MA models / Thomas J. Rothenberg -- An elementary account of Amari's expected geometry / Frank Critchley, Paul Marriott and Mark Salmon
Note:
Title from publisher's bibliographic system (viewed on 05 Oct 2015)
Additional Edition:
ISBN 9780521651165
Additional Edition:
ISBN 9780521178297
Additional Edition:
Print version ISBN 9780521651165
Language:
English
DOI:
10.1017/CBO9780511660092
URL:
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