Bayesian Semiparametric Regression for Autoregressive Models with Possible Unit Roots

Ricardo Silva (rgs.rsilva@gmail.com)

Econometrics from University Library of Munich, Germany

Abstract: In this paper we consider bayesian semiparametric regression within the generalized linear model framework. Specifically, we study a class of autoregressive time series where the time trend is incorporated in a nonparametrically way. Estimation and inference where performed through Markov Chain Monte Carlo simulation techniques. Main results show that treating the time trend nonparametrically possible model misspecification and biased results from structural break issues are solved. Empirical applications are conducted using the extended Nelson and Plosser benchmark time series

Keywords: Bayesian Inference; Unit Root; Structural Break; MCMC; Semiparametric Regression; Nonlinear Time Trend; Random Walk Prior; Macroeconomic Time Series (search for similar items in EconPapers)
JEL-codes: C11 C13 C14 C22 C44 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2004-05-20
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: Type of Document - pdf; pages: 16
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0405002

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