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Causal Inference in Econometrics

Causal Inference in Econometrics - Studies in Computational Intelligence

1st ed. 2016

Hardback (06 Jan 2016)

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Publisher's Synopsis

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.

Book information

ISBN: 9783319272832
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
Edition: 1st ed. 2016
DEWEY: 330.015195
DEWEY edition: 23
Language: English
Number of pages: 638
Weight: 1080g
Height: 235mm
Width: 155mm
Spine width: 35mm