Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility
Economics Letters, 2017, vol. 150, issue C, 10-14
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)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:150:y:2017:i:c:p:10-14
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