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Causal Inference in Econometrics

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This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume.

To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

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Series Title

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Call Number

006.3

Publisher

Cham : Springer Cham., 2016

Collation

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Language

English

ISBN/ISSN

978-3-319-27284-9

Classification

006.3

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Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Computational Intelligence

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Statement of Responsibility

Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta

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Cataloger

ratna

Source

https://link.springer.com/10.1007/978-3-319-27284-9

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