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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

Adrian Licht, Alvaro Escribano () and Szabolcs Blazsek ()

UC3M Working papers. Economics from Universidad Carlos III de Madrid. Departamento de Economía

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.

Keywords: Markov; Regime-Switching; Models; Score-Driven; Multivariate; Stochastic; Location; And; Stochastic; Seasonality; Models; Score; Models; Dynamic; Conditional; United; States; Industrial; Production; World; Crude; Oil; Production (search for similar items in EconPapers)
JEL-codes: C52 C51 C32 (search for similar items in EconPapers)
Date: 2019-10
New Economics Papers: this item is included in nep-ecm, nep-ene, nep-ets and nep-ore
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