Overview
- Presents recent research on robustness in econometrics
- Introduces theoretical foundations and applications
- Written by respected experts in the field
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 692)
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About this book
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems.
Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
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Table of contents (43 chapters)
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Front Matter
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Keynote Addresses
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Front Matter
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Fundamental Theory
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Front Matter
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Editors and Affiliations
Bibliographic Information
Book Title: Robustness in Econometrics
Editors: Vladik Kreinovich, Songsak Sriboonchitta, Van-Nam Huynh
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-50742-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-50741-5Published: 20 February 2017
Softcover ISBN: 978-3-319-84480-0Published: 13 July 2018
eBook ISBN: 978-3-319-50742-2Published: 11 February 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 705
Number of Illustrations: 9 b/w illustrations, 120 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Econometrics