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Modeling Dependence in Econometrics [electronic resource] : Selected Papers of the Seventh International Conference of the Thailand Econometric Society, Faculty of Economics, Chiang Mai University, Thailand, January 8-10, 2014 / edited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta.

Contributor(s): Huynh, Van-Nam [editor.] | Kreinovich, Vladik [editor.] | Sriboonchitta, Songsak [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Advances in Intelligent Systems and Computing: 251Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XX, 575 p. 75 illus., 45 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319033952.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Econometrics | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | EconometricsAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Part I Keynote Paper -- Part II Fundamental Theory -- Part III Applications.
In: Springer eBooksSummary: 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.
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Part I Keynote Paper -- Part II Fundamental Theory -- Part III Applications.

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.

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