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Bayesian Unit Root Test in Double Threshold Heteroskedastic Models

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  • Cathy Chen
  • Shu-Yu Chen
  • Sangyeol Lee

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

Suggested Citation

  • Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.
    • Handle: RePEc:kap:compec:v:42:y:2013:i:4:p:471-490
    DOI: 10.1007/s10614-012-9354-7
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