Unobserved components with stochastic volatility in U.S. inflation: Estimation and signal extraction
- Publisher:
- WILEY
- Publication Type:
- Journal Article
- Citation:
- Journal of Applied Econometrics, 2018, 36, (5), pp. 614-627
- Issue Date:
- 2018-02-02
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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.
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