Causal Inference in Econometrics (Studies in Computational Intelligence, #622)

Van-Nam Huynh (Editor), Vladik Kreinovich (Editor), and Songsak Sriboonchitta (Editor)

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Book cover for 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.

  • ISBN13 9783319801087
  • Publish Date 30 March 2018 (first published 6 January 2016)
  • Publish Status Active
  • Publish Country CH
  • Imprint Springer International Publishing AG
  • Edition Softcover reprint of the original 1st ed. 2016
  • Format Paperback
  • Pages 638
  • Language English