Bayesian estimation for threshold autoregressive model with multiple structural breaks

Varun Agiwal () and Jitendra Kumar ()
Additional contact information
Varun Agiwal: Central University of Rajasthan
Jitendra Kumar: Central University of Rajasthan

METRON, 2020, vol. 78, issue 3, No 7, 382 pages

Abstract: Abstract This paper provides a Bayesian setup for multiple regimes threshold autoregressive model with possible break points. A full conditional posterior distribution is obtained for all model parameters with considering suitable prior information. Threshold and break point variables do not attain standard form distributions. To compute posterior distributions, we apply the Gibbs sampler with the Metropolis-Hastings algorithm. A variety of loss functions are considered for optimizing the risk associated with each parameter. For empirical evidence, simulation study and real data illustration are carried out.

Keywords: Threshold autoregressive model; Bayesian Inference; MCMC method; Structural Break; 62F15; 37M10 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40300-020-00188-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metron:v:78:y:2020:i:3:d:10.1007_s40300-020-00188-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40300

DOI: 10.1007/s40300-020-00188-0

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().