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This is a concise introduction to the literature on the statistical analysis of atypical observations in economic and financial time series. It shows how statistical techniques usually applied to cross-sectional data can be applied to time series in order to avoid the use of inappropriate models. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.
This book investigates the methodological challenges of identifying and managing atypical observations, or outliers, within economic and financial time series data. The authors, André Lucas, Dick van Dijk, and Philip H. Franses, leverage their expertise in econometrics to bridge the gap between cross-sectional statistical techniques and time-dependent data structures. By providing a rigorous framework for outlier detection, the text argues that standard modeling approaches often fail when data contains anomalies, necessitating more robust analytical tools.
What You Will Find
Experts recognize this volume as a specialized resource for researchers and graduate students seeking to refine their econometric modeling techniques. Readers frequently note the technical density of the prose, which serves as a bridge between introductory textbooks and primary research literature.
Page Count:
256
Publication Date:
2011-07-14
Publisher:
Oxford University Press
ISBN-10:
0199247013
ISBN-13:
9780199247011
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