Robustness in Econometrics

  • Vladik Kreinovich
  • Songsak Sriboonchitta
  • Van-Nam Huynh

Part of the Studies in Computational Intelligence book series (SCI, volume 692)

Table of contents

  1. Front Matter
    Pages i-x
  2. Keynote Addresses

    1. Front Matter
      Pages 1-1
    2. Elvezio Ronchetti
      Pages 3-21
  3. Fundamental Theory

    1. Front Matter
      Pages 23-23
    2. Songsak Sriboonchitta, Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva
      Pages 51-68
    3. Olga Kosheleva, Vladik Kreinovich, Songsak Sriboonchitta
      Pages 79-87
    4. Kongliang Zhu, Nantiworn Thianpaen, Vladik Kreinovich
      Pages 99-110
    5. Cathy W. S. Chen, Khemmanant Khamthong, Sangyeol Lee
      Pages 111-134
    6. W. Y. Jessica Leung, S. T. Boris Choy
      Pages 187-200
    7. Qianfang Hu, Zheng Wei, Baokun Li, Tonghui Wang
      Pages 217-233
    8. Weizhong Tian, Guodong Han, Tonghui Wang, Varith Pipitpojanakarn
      Pages 235-248
    9. Xiaonan Zhu, Tonghui Wang, Varith Pipitpojanakarn
      Pages 249-265
    10. Xiaonan Zhu, Ziwei Ma, Tonghui Wang, Teerawut Teetranont
      Pages 267-286
    11. Jiejie Zhang, Ying Chen, Stefan Klotz, Kian Guan Lim
      Pages 287-304

About this book


This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems.

Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.


Computational Intelligence Econometrics Robustness Robustness in Econometrics Models of Economic Phenomena

Editors and affiliations

  • Vladik Kreinovich
    • 1
  • Songsak Sriboonchitta
    • 2
  • Van-Nam Huynh
    • 3
  1. 1.Department of Computer ScienceUniversity of Texas at El Paso Department of Computer ScienceEl Paso, TXUSA
  2. 2.Faculty of EconomicsChiang Mai University Faculty of EconomicsChiang MaiThailand
  3. 3.Japan Adv. Inst. of Sci. & Tech. (JAIST) IshikawaJapan

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-50741-5
  • Online ISBN 978-3-319-50742-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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