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Combining a regression model with a multivariate Markov chain in a forecasting problem

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  • Damásio, Bruno
  • Nicolau, João

Abstract

This paper proposes a new concept: the usage of Multivariate Markov Chains (MMC) as covariates. Our approach is based on the observation that we can treat possible categorical (or discrete) regressors, whose values are unknown in the forecast period, as an MMC in order to improve the forecast error of a certain dependent variable. Hence, we take advantage of the information about the past state interactions between the MMC categories to forecast the categorical (or discrete) regressors and improve the forecast of the actual dependent variable.

Suggested Citation

  • Damásio, Bruno & Nicolau, João, 2014. "Combining a regression model with a multivariate Markov chain in a forecasting problem," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 108-113.
    • Handle: RePEc:eee:stapro:v:90:y:2014:i:c:p:108-113
    DOI: 10.1016/j.spl.2014.03.026
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    References listed on IDEAS

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    1. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
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    Cited by:

    1. Damásio, Bruno & Louçã, Francisco & Nicolau, João, 2018. "The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 524-533.

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