A New Approach to the Threshold Autoregressive Models

Nuri Celik

Journal of Statistical and Econometric Methods, 2022, vol. 11, issue 3, 1

Abstract: Time series analyzing is very important tool for economic and financial system. However, recent developments show that financial systems are known in a structural change. Therefore, nonlinear time series have been analyzed for past decades because of these changes. In this paper, we consider Threshold Autoregressive (TAR) model. The most popular method for estimating the parameters and threshold value is least square (LS) method. However, LS method is not robust to the outliers and departures from normality. Therefore, we propose a robust version of estimation in order to provide robust results. Â JEL classification numbers: C01, C22, C13.

Keywords: Threshold Autoregressive Model; Iterated Weighted Least Square; Skew Normal; Long Tailed Symmetric Distribution; Robustness. (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.scienpress.com/Upload/JSEM%2fVol%2011_3_1.pdf (application/pdf)

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:spt:stecon:v:11:y:2022:i:3:f:11_3_1

Access Statistics for this article

More articles in Journal of Statistical and Econometric Methods from SCIENPRESS Ltd
Bibliographic data for series maintained by Eleftherios Spyromitros-Xioufis ().