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Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production

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  • Blazsek, Szabolcs
  • Escribano, Álvaro
  • Licht, Adrian

Abstract

In this paper, new Seasonal-QVAR (quasi-vector autoregressive) and Markov switching (MS) Seasonal-QVAR (MS-Seasonal-QVAR) models are introduced. Seasonal-QVAR is an outlierrobust score-driven state space model, which is an alternative to classical multivariate Gaussian models (e.g. basic structural model; Seasonal-VARMA). Conditions of the maximum likelihood estimator and impulse response functions are shown. Dynamic relationships between world crude oil production and US industrial production are studied for the period of 1973 to 2019. Statistical performances of alternative models are analyzed. MS-Seasonal-QVAR identies structural changes and extreme observations in the dataset. MS-Seasonal-QVAR is superior to Seasonal-QVAR and, and both are superior to Gaussian alternatives.

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  • Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    • Handle: RePEc:cte:werepe:29030
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    More about this item

    Keywords

    World Crude Oil Production;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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