© 2016

Causal Inference in Econometrics

  • Van-Nam Huynh
  • Vladik Kreinovich
  • Songsak Sriboonchitta

Part of the Studies in Computational Intelligence book series (SCI, volume 622)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Fundamental Theory

    1. Front Matter
      Pages 1-1
    2. Monica Billio, Maddalena Cavicchioli
      Pages 3-15
    3. Rasika P. Yatigammana, S. T. Boris Choy, Jennifer S. K. Chan
      Pages 83-107
    4. Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta
      Pages 109-118
    5. Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta
      Pages 119-131
    6. Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta
      Pages 133-152
    7. Weizhong Tian, Cong Wang, Mixia Wu, Tonghui Wang
      Pages 153-169
    8. Zheng Wei, Tonghui Wang, Baokun Li
      Pages 185-198
  3. Applications

    1. Front Matter
      Pages 225-225
    2. Hooi Hooi Lean, Geok Peng Yeap
      Pages 227-241
    3. Lee Tzong-Ru (Jiun-Shen), Kanchana Chokethaworn, Huang Man-Yu
      Pages 243-254
    4. Warut Pannakkong, Van-Nam Huynh, Songsak Sriboonchitta
      Pages 255-277

About this book


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.


Computational Intelligence Econometrics Risk Intelligent Econometrics Causal Inference

Editors and affiliations

  • Van-Nam Huynh
    • 1
  • Vladik Kreinovich
    • 2
  • Songsak Sriboonchitta
    • 3
  1. 1.School of Knowledge ScienceJapan Advanced Ins. of Sci. & TechIshikawaJapan
  2. 2.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA
  3. 3.Faculty of EconomicsChiang Mai UniversityChiangmaiThailand

Bibliographic information

  • Book Title Causal Inference in Econometrics
  • Editors Van-Nam Huynh
    Vladik Kreinovich
    Songsak Sriboonchitta
  • Series Title Studies in Computational Intelligence
  • Series Abbreviated Title Studies Comp.Intelligence
  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-27283-2
  • Softcover ISBN 978-3-319-80108-7
  • eBook ISBN 978-3-319-27284-9
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XI, 638
  • Number of Illustrations 91 b/w illustrations, 15 illustrations in colour
  • Topics Computational Intelligence
    Quantitative Finance
    Quality Control, Reliability, Safety and Risk
  • Buy this book on publisher's site
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