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Prediction and Causality in Econometrics and Related Topics

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  • © 2022

Overview

Editors:
  1. Nguyen Ngoc Thach

    1. Banking University Ho Chi Minh City, Ho Chi Minh, Vietnam

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  2. Doan Thanh Ha

    1. Banking University of Ho Chi Minh City, Ho Chi Minh, Vietnam

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    You can also search for this editor in PubMed   Google Scholar

  3. Nguyen Duc Trung

    1. Banking University of Ho Chi Minh City, Ho Chi Minh, Vietnam

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  4. Vladik Kreinovich

    1. Computer Science Department, University of Texas at El Paso, El Paso, USA

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  • Provides recent research on Econometrics for Financial Applications
  • Introduces theoretical foundations and applications
  • Fourth International Econometric Conference of Vietnam—ECONVN2021, Ho Chi Minh City, Vietnam, January 11-13, 2021

Part of the book series: Studies in Computational Intelligence (SCI, volume 983)

Included in the following conference series:

Conference proceedings info: ECONVN 2021.

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Table of contents (49 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Theoretical Results

    1. Front Matter

      Pages 1-1
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    2. On Random Sets for Inference in Statistics and Econometrics

      • Hung T. Nguyen
      Pages 3-21

    3. How the Proportion of People Who Agree to Perform a Task Depends on the Stimulus: A Theoretical Explanation of the Empirical Formula

      • Laxman Bokati, Vladik Kreinovich, Doan Thanh Ha
      Pages 22-27

    4. How to Explain the Anchoring Formula in Behavioral Economics

      • Laxman Bokati, Vladik Kreinovich, Chon Van Le
      Pages 28-34

    5. Models Only Say What They’re Told to Say

      • William M. Briggs
      Pages 35-42

    6. Lüders Rule and Conditional Probability for Commuting Events

      • John Harding, Hung Nguyen
      Pages 43-56

    7. On Solving Image Deblurring Problem via Nash Equilibrium

      • Wachirapong Jirakitpuwapat, Poom Kumam, Nuttapol Pakkaranang
      Pages 57-66

    8. Commonsense Explanations of Sparsity, Zipf Law, and Nash’s Bargaining Solution

      • Olga Kosheleva, Vladik Kreinovich, Kittawit Autchariyapanikul
      Pages 67-74

    9. Practical Steps to Improve Specification Testing

      • Austin Nichols, Mark E. Schaffer
      Pages 75-88

    10. Why Most Empirical Distributions Are Few-Modal

      • Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich
      Pages 89-96

    11. A Different Kind of Effect Size Based on Samples from Two Populations with Delta Log-Skew-Normal Distributions

      • Ziyuan Wang, Tonghui Wang, David Trafimow, Zhaohui Xu
      Pages 97-112

    12. Efficiency Effects in a Copula Based Stochastic Frontier Model

      • Woraphon Yamaka
      Pages 113-122

    13. Why LASSO, Ridge Regression, and EN: Explanation Based on Soft Computing

      • Woraphon Yamaka, Hamza Alkhatib, Ingo Neumann, Vladik Kreinovich
      Pages 123-130

    14. Turning Points of Environmental Kuznets Curves for G20 Economies

      • Kejia Yan, Rakesh Gupta
      Pages 131-141

  3. Practical Applications

    1. Front Matter

      Pages 143-143
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    2. ARIMA Model – Vietnam’s GDP Forecasting

      • Lê Thị Thúy Hằng, Nguyá»…n Xuân DÅ©ng
      Pages 145-151

    3. Neural Network Models for Inflation Forecasting: A Revisit

      • Thi Thanh Xuan Pham, Tu D. Q. Le, Tien Nhat Nguyen
      Pages 152-168

    4. Impact of Financial Development on International Trade in ASEAN-6 Countries: A Bayesian Approach

      • Nguyen Ngoc Thach, Vo Thi Thuy Kieu, Duong Thi Thuy An
      Pages 169-184

    5. Determinants of Bank Liquidity: Evidence from Vietnam

      • Hai Nam Pham, Thi Hong Nhung Pham
      Pages 185-196
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Keywords

About this book

This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy.


This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.



Editors and Affiliations

  • Banking University Ho Chi Minh City, Ho Chi Minh, Vietnam

    Nguyen Ngoc Thach

  • Banking University of Ho Chi Minh City, Ho Chi Minh, Vietnam

    Doan Thanh Ha, Nguyen Duc Trung

  • Computer Science Department, University of Texas at El Paso, El Paso, USA

    Vladik Kreinovich

Bibliographic Information

  • Book Title: Prediction and Causality in Econometrics and Related Topics

  • Editors: Nguyen Ngoc Thach, Doan Thanh Ha, Nguyen Duc Trung, Vladik Kreinovich

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-77094-5

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Hardcover ISBN: 978-3-030-77093-8Published: 27 July 2021

  • Softcover ISBN: 978-3-030-77096-9Published: 28 July 2022

  • eBook ISBN: 978-3-030-77094-5Published: 26 July 2021

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XI, 682

  • Number of Illustrations: 47 b/w illustrations, 129 illustrations in colour

  • Topics: Computational Intelligence

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