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An Empirical Confirmation of the Superior Performance of MIDAS over ARIMAX

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9978))

Abstract

A new model (MIDAS) for forecasting economic data has been proposed recently to take into account of more relevant information than the ARIMAX model. However, in order to convince econometricians to use MIDAS instead of ARIMAX, at least some evidence from empirical studies is needed, to indicate that the forecast performance of MIDAS is superior than that of ARIMAX. Our present work precisely aims at filling this need. In doing so, we also investigate a practical problem: Forecasting export growth in Thailand. Our empirical findings confirm that the MIDAS regression model significantly improves the forecast accuracy when compared with the ARIMAX model.

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Acknowledgement

We are grateful for financial support from “Puay Ungpakoyn Centre of Excellence in Econometrics”, Faculty of Economics, Chiangmai University.

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Authors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Tanaporn Tungtrakul, Natthaphat Kingnetr & Songsak Sriboonchitta

Authors
  1. Tanaporn Tungtrakul
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  2. Natthaphat Kingnetr
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  3. Songsak Sriboonchitta
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Corresponding author

Correspondence to Tanaporn Tungtrakul .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

  2. Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  3. University of Science, Ho Chi Minh City, Vietnam

    Bac Le

  4. Duy Tan University, Da Nang, Vietnam

    Bao Nguyen Le

  5. Université de Technologie de Compiègne , Compiègne, France

    Thierry Denoeux

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Tungtrakul, T., Kingnetr, N., Sriboonchitta, S. (2016). An Empirical Confirmation of the Superior Performance of MIDAS over ARIMAX. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_51

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  • DOI: https://doi.org/10.1007/978-3-319-49046-5_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49045-8

  • Online ISBN: 978-3-319-49046-5

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