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Threshold MIDAS Forecasting of Inflation Rate

Author

Listed:
  • Chaoyi Chen
  • Yiguo Sun
  • Yao Rao
Abstract
We propose several threshold mixed data sampling (TMIDAS) autoregressive models to forecast the Canadian inflation rate using predictors observed at different frequencies. These models take two low-frequency variables and a high-frequency index as a threshold variable. We compare our TMIDAS models to commonly used benchmark models, evaluating their in-sample and out-of-sample forecasts. Our results demonstrate the good forecasting performance of the TMIDAS models. Particularly, the in-sample results highlight that the TMIDAS model using the high-frequency index as the threshold variable outperforms other models. Through unconditional superior predictive ability (USPA) and conditional superior predictive ability (CSPA) tests for out-of-sample evaluation, we find that no single model consistently outperforms the others, although at least one of our TMIDAS models remains competitive in most cases

Suggested Citation

  • Chaoyi Chen & Yiguo Sun & Yao Rao, 2023. "Threshold MIDAS Forecasting of Inflation Rate," Working Papers 202314, University of Liverpool, Department of Economics.
    • Handle: RePEc:liv:livedp:202314
    as

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    File URL: https://www.liverpool.ac.uk/media/livacuk/schoolofmanagement/docs/ECON,WP,202314,full.pdf
    File Function: First version, 2023
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    References listed on IDEAS

    as
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    3. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    4. Cologni, Alessandro & Manera, Matteo, 2008. "Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries," Energy Economics, Elsevier, vol. 30(3), pages 856-888, May.
    5. Banerjee, Anindya & Marcellino, Massimiliano, 2006. "Are there any reliable leading indicators for US inflation and GDP growth?," International Journal of Forecasting, Elsevier, vol. 22(1), pages 137-151.
    6. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    7. Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Forecasting; High-frequency index; Mixed data sampling; Superiority predictive ability test; Threshold regression;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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