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Quantitative Finance and Economics

2019, Volume 3, Issue 1: 75-87. doi: 10.3934/QFE.2019.1.75
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Research article

Re-considering the Fisher equation for South Korea in the application of nonlinear and linear ARDL models

  • 1.
    Department of Economics, St. Mary’s College of Maryland, MD, USA
  • 2.
    Department of Econometrics, Adnan Menderes University, Aydin, Turkey
  • Received: 19 December 2018 Accepted: 05 March 2019 Published: 08 March 2019

  • JEL Codes: E0, E40, E43, G12, E6

  • This study aims to approach the Fisher effect issue from a different methodological perspective. To this aim, the nonlinear autoregressive distributed lag (ARDL) model, recently developed by Shin et al. (2014), is applied for South Korea between 2000Q4Ƀ2017Q4. This model allows us to decompose one variable (changes in inflation) into two new variables (increases and decreases in inflation) under the manners of nonlinearity and asymmetry. Hence, it enables us to monitor the Fisher effect in terms of increases and decreases separately. We also apply the linear version of the same model since the nonlinear ARDL model is the extended version of linear ARDL model. While the empirical findings of the nonlinear model support asymmetrically partial Fisher effects in the long-run for 1, 3, 5 and 10-years Korean bond rates, the linear model does not. Additionally, the nonlinear model detects lower size partial Fisher effects when the maturity of interest rates gets longer. Another finding of this study is that the nonlinear model may mathematically identify and introduce a different version of the partial Fisher effect based on singular (separate) effects of each decomposed variable in a parametric manner.

    Citation: Ongan Serdar, Gocer Ismet. Re-considering the Fisher equation for South Korea in the application of nonlinear and linear ARDL models[J]. Quantitative Finance and Economics, 2019, 3(1): 75-87. doi: 10.3934/QFE.2019.1.75

    Related Papers:

  • This study aims to approach the Fisher effect issue from a different methodological perspective. To this aim, the nonlinear autoregressive distributed lag (ARDL) model, recently developed by Shin et al. (2014), is applied for South Korea between 2000Q4Ƀ2017Q4. This model allows us to decompose one variable (changes in inflation) into two new variables (increases and decreases in inflation) under the manners of nonlinearity and asymmetry. Hence, it enables us to monitor the Fisher effect in terms of increases and decreases separately. We also apply the linear version of the same model since the nonlinear ARDL model is the extended version of linear ARDL model. While the empirical findings of the nonlinear model support asymmetrically partial Fisher effects in the long-run for 1, 3, 5 and 10-years Korean bond rates, the linear model does not. Additionally, the nonlinear model detects lower size partial Fisher effects when the maturity of interest rates gets longer. Another finding of this study is that the nonlinear model may mathematically identify and introduce a different version of the partial Fisher effect based on singular (separate) effects of each decomposed variable in a parametric manner.


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