Unobserved components with stochastic volatility: Simulation-based estimation and signal extraction

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Abstract

© 2021 The Authors. Journal of Applied Econometrics Published by John Wiley & Sons, Ltd.The unobserved components time series model with stochastic volatility has gained much interest in econometrics, especially for the purpose of modelling and forecasting inflation. We present a feasible simulated maximum likelihood method for parameter estimation from a classical perspective. The method can also be used for evaluating the marginal likelihood function in a Bayesian analysis. We show that our simulation-based method is computationally feasible, for both univariate and multivariate models. We assess the performance of the method in a Monte Carlo study. In an empirical study, we analyse U.S. headline inflation using different univariate and multivariate model specifications.
Original languageEnglish
Pages (from-to)614-627
JournalJournal of Applied Econometrics
Volume36
Issue number5
DOIs
Publication statusPublished - 1 Aug 2021

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