The Refinement of Econometric Estimation and Test Procedures
Finite Sample and Asymptotic Analysis

The main theme of this book is the importance of refined asymptotic methods to econometric analysis.

Garry D. A. Phillips (Edited by), Elias Tzavalis (Edited by)

9781107406247, Cambridge University Press

Paperback / softback, published 9 August 2012

418 pages
22.9 x 15.2 x 2.2 cm, 0.56 kg

Review of the hardback: 'This book is a tribute to one of the great contributors to the subject of econometrics. The excellent papers contributed here reflect on the research of the late Michael Magdalinos and acknowledge his solid and beneficial impact on the foundational issue of finite and asymptotic sample econometrics. They will make the book widely read and referenced.' Aman Ullah, Professor of Economics, University of California, Riverside

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.

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.

Subject Areas: Economic statistics [KCHS], Econometrics [KCH], Economic theory & philosophy [KCA]