Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility

Stefanos Dimitrakopoulos

Economics Letters, 2017, vol. 150, issue C, 10-14

Abstract: We develop a Bayesian semiparametric method to estimate a time-varying parameter regression model with stochastic volatility, where both the error distributions of the observations and parameter-driven dynamics are unspecified. We illustrate our methodology with an application to inflation.

Keywords: Dirichlet process; Markov chain Monte Carlo; Stochastic volatility; Time-varying parameters; Inflation (search for similar items in EconPapers)
JEL-codes: C11 C14 C15 C22 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:150:y:2017:i:c:p:10-14

DOI: 10.1016/j.econlet.2016.10.035

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