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Markov-Switching ARDL Modeling of Parboiled Rice Import Demand from Thailand

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10758))

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Abstract

In this paper, we develop a Markov Switching autoregressive distributed lag (MS-ARDL) model in which short- and long-run nonlinearities are introduced. The model is used to investigate the import demand of Nigeria for parboiled rice from Thailand. We demonstrate that the model is estimable by Maximum likelihood estimator and then a reliable long-run inference can be achieved by bound testing regardless of the integration orders of the variables. Furthermore, we first examine the accuracy of the model using a simulation study, and then the salient features of the model are employed to investigate the Thai parboiled rice demand from Nigeria.

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Acknowledgement

We are grateful for financial support from Puay Ungpakorn Centre of Excellence in Econometrics, Faculty of Economics, Chiang Mai University.

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Authors and Affiliations

  1. Faculty of Economics, Center of Excellent in Econometric, Chiang Mai University, Chiang Mai, Thailand

    Roengchai Tansuchat & Woraphon Yamaka

Authors
  1. Roengchai Tansuchat
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  2. Woraphon Yamaka
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Correspondence to Roengchai Tansuchat .

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Editors and Affiliations

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

    Van-Nam Huynh

  2. Osaka University, Osaka, Japan

    Masahiro Inuiguchi

  3. Hanoi National University of Education, Hanoi, Vietnam

    Dang Hung Tran

  4. Université de Technologie de Compiègne, Compiègne, France

    Thierry Denoeux

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Tansuchat, R., Yamaka, W. (2018). Markov-Switching ARDL Modeling of Parboiled Rice Import Demand from Thailand. In: Huynh, VN., Inuiguchi, M., Tran, D., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2018. Lecture Notes in Computer Science(), vol 10758. Springer, Cham. https://doi.org/10.1007/978-3-319-75429-1_31

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  • DOI: https://doi.org/10.1007/978-3-319-75429-1_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75428-4

  • Online ISBN: 978-3-319-75429-1

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