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

Phillips, G. D. A. (Editor)/ Tzavalis, Elias (Editor)

ISBN 10: 0521870534 / ISBN 13: 9780521870535

Published by Cambridge Univ Pr, 2007

About this Item

389 pages. 9.00x6.25x1.00 inches. In Stock. This item is printed on demand.

Seller Inventory # __0521870534

Bibliographic Details

• Title: The Refinement of Econometric Estimation and Test Procedures: Finite Sample and Asymptotic Analysis
• Publisher: Cambridge Univ Pr
• Publication Date: 2007
• Language: English
• ISBN 10: 0521870534
• ISBN 13: 9780521870535
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.82 kilograms

About this title

Synopsis

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.

Book Description

This book concerns the importance of refined asymptotic methods to approximate the finite sample behaviour of econometric estimators and tests. It also features chapters 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.