The Refinement of Econometric Estimation and Test Procedures
The Refinement of Econometric Estimation and Test Procedures
The small sample properties of estimators and tests are frequently too complex to be useful or are unknown. Much econometric theory is therefore developed for very large or asymptotic samples where it is assumed that the behaviour of estimators and tests will adequately represent their properties in small samples. Refined asymptotic methods adopt an intermediate position by providing improved approximations to small sample behaviour using asymptotic expansions. Dedicated to the memory of Michael Magdalinos, whose work is a major contribution to this area, this book contains chapters directly concerned with refined asymptotic methods. In addition, there are chapters focusing on new asymptotic results; the exploration through simulation of the small sample behaviour of estimators and tests in panel data models; and improvements in methodology. With contributions from leading econometricians, this collection will be essential reading for researchers and graduate students concerned with the use of asymptotic methods in econometric analysis.
- Brings together original papers by leading econometricians
- Use of refined asymptotic methods improves understanding of analytical tools in econometrics
- Methodological improvements provide stronger underpinning for theory
Reviews & endorsements
"Overall, I highly recommend this book to researchers, practitioners, and students who will benefit from its high quality, usefulness, and importance to the field of higher-order asymptotic theory."
Emma M. Iglesias, Michigan State University for the Journal of the American Statistician
Product details
August 2012Paperback
9781107406247
418 pages
229 × 152 × 22 mm
0.56kg
Available
Table of Contents
- List of figures
- List of tables
- Contributors
- Preface
- Michael Magdalinos 1949–2002
- Acknowledgements
- Introduction Garry D. A. Phillips and Elias Tzavalis
- 1. Conditional heteroscedasticity models with Pearson disturbances Michael A. Magdalinos and George P. Mitsopoulos
- 2. The Instrumental Variables method revisited: on the nature and choice of optimal instruments Aris Spanos
- 3. Nagar-type moment approximations in simultaneous equation models: some further results Garry D. A. Phillips
- 4. Local GEL methods for conditional moment restrictions Richard J. Smith
- 5. Limit theory for moderate deviations from a unit root under weak dependence Peter C. B. Phillips and Tassos Magdalinos
- 6. The structure of multiparameter tests Christopher L. Cavanagh and Thomas J. Rothenberg
- 7. Cornish-Fisher size corrected t and F statistics for the linear regression model with heteroscedastic errors Spyridon D. Symeonides, Hellen Kandiloriou and Elias Tzavalis
- 8. Non-parametric specification testing of non-nested econometric models Qi Li and Thanasis Stengos
- 9. Testing for autocorrelation in systems of equations Phoebus J. Dhrymes
- 10. Alternative approaches to estimation and inference in large multifactor panels: small sample results with an application to modelling of Asset Returns G. Kapetanios and M. Hashem Pesaran
- 11. Judging contending estimators by simulation: tournaments in dynamic panel data models Jan F. Kiviet
- 12. A statistical proof of the transformation theorem Karim M. Abadir and Jan R. Magnus
- 13. On the joint density of the sum and sum of squares of nonnegative random variables Grant Hillier
- 14. Conditional Response Analysis Grayham E. Mizon and Anna Staszewska
- Index.
