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.
Paul Marriott, Mark Salmon, Maozu Lu, Grayham Mizon, Grant Hillier, Ray O'Brien, R. Smith, Uwe Jensen, J. M. Corcuera, F. Giummole, Kees Jan van Garderen, Tom Rothenberg, Russell Davidson, Frank Critchley.
|Publisher:||Cambridge University Press|
|Product dimensions:||5.98(w) x 9.02(h) x 0.75(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.