Causal Inference in Econometrics

Nonfiction, Science & Nature, Mathematics, Applied, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Causal Inference in Econometrics by , Springer International Publishing
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Author: ISBN: 9783319272849
Publisher: Springer International Publishing Publication: December 28, 2015
Imprint: Springer Language: English
Author:
ISBN: 9783319272849
Publisher: Springer International Publishing
Publication: December 28, 2015
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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