Applications of Differential Geometry to Econometrics

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Differential geometry has become a standard tool in the analysis of statistical models, offering a deeper appreciation of existing methodologies and highlighting the issues that 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 following chapters offer applications of geometric methods to practical solutions and offer insight into problems of econometric inference.
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Editorial Reviews

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

  • ISBN-13: 9780521651165
  • Publisher: Cambridge University Press
  • Publication date: 8/31/2000
  • Pages: 336
  • Product dimensions: 5.98 (w) x 8.98 (h) x 0.87 (d)

Table of Contents

Introduction P. Marriott and M. Salmon; 1. An introduction to differential geometry P. Marriott and M. Salmon; 2. Orthogonal projection, nested models and encompassing Maozu Lu and G. Mizon; 3. Exact properties of the maximum likelihood estimator in exponential regression models G. Hillier and R. O'Brien; 4. Empirical likelihood estimation and inference R. Smith; 5. Measuring earnings differentials with frontier functions and Rao distances U. Jensen; 6. First order predictive densities J. M. Corcuera and F. Giummole; 7. An alternative comparison of classical tests: assessing the effects of curvature K. J. van Garderen; 8. Testing for unit roots in AR and MA Models T. Rothenberg; 9. Efficiency and robustness in a geometrical perspective R. Davidson; 10. Paramaterisations and transformations; An elementary introduction to Amari's differential geometry F. Critchley, P. Marriott and M. Salmon.
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