Overview
- Recent research in Modeling Dependence in Econometrics
- Selected papers of the Seventh International Conference of the Thailand Econometric Society, Faculty of Economics, Chiang Mai University, Thailand, January 8-10, 2014
- Written by experts in the field
Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 251)
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Table of contents (37 papers)
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Front Matter
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Keynote Paper
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Front Matter
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Fundamental Theory
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Front Matter
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Applications
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Front Matter
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Keywords
About this book
In economics, many quantities are related to each other. Such economic relations are often much more complex than relations in science and engineering, where some quantities are independence and the relation between others can be well approximated by linear
functions. As a result of this complexity, when we apply traditional statistical techniques - developed for science and engineering - to process economic data, the inadequate treatment of dependence leads to misleading models and erroneous predictions. Some economists even blamed such inadequate treatment of dependence for the 2008 financial crisis.
To make economic models more adequate, we need more accurate techniques for describing dependence. Such techniques are currently being developed. This book contains description of state-of-the-art techniques for modeling dependence and economic applications of
these techniques. Most of these research developments are centered around the notion of a copula - a general way of describing dependence in probability theory and statistics. To be even more adequate, many papers go beyond traditional copula techniques and
take into account, e.g., the dynamical (changing) character of the dependence in economics.
Editors and Affiliations
Bibliographic Information
Book Title: Modeling Dependence in Econometrics
Editors: Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta
Series Title: Advances in Intelligent Systems and Computing
DOI: https://doi.org/10.1007/978-3-319-03395-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Softcover ISBN: 978-3-319-03394-5Published: 05 December 2013
eBook ISBN: 978-3-319-03395-2Published: 18 November 2013
Series ISSN: 2194-5357
Series E-ISSN: 2194-5365
Edition Number: 1
Number of Pages: XX, 575
Number of Illustrations: 30 b/w illustrations, 45 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Econometrics