Bayesian Unit Root Test in Double Threshold Heteroskedastic Models

Cathy Chen (), Shu-Yu Chen and Sangyeol Lee
Authors registered in the RePEc Author Service: Cathy W. S. Chen ()

Computational Economics, 2013, vol. 42, issue 4, 490 pages

Abstract: This paper aims to detect the presence of local non-stationarity of nonlinear autoregressive processes with heteroskedastic errors. A Bayesian test is developed to test for the unit root in multi-regime threshold autoregression with heteroskedasticity. To implement a test, a posterior odds analysis is proposed. Particularly, a mixture prior for the autoregressive coefficient is used to alleviate the identifiability problem that occurs when time series has unit roots. The proposed method achieves a reliable inference despite of the non-integrability problem in the likelihood function. A simulation study and two real data analysis are conducted for illustration. This paper successfully proves the proposed model can accommodate different threshold values to cope with local non-stationarity and in addition, captures discrete time-varying properties. Copyright Springer Science+Business Media New York 2013

Keywords: Bayesian hypothesis testing; SETAR; GARCH; Unit-root test; Markov chain Monte Carlo method; Posterior odds ratio (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10614-012-9354-7

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