EconPapers    
Economics at your fingertips  
 

Monte Carlo Comparison for Nonparametric Threshold Estimators

Chaoyi Chen () and Yiguo Sun ()
Additional contact information
Chaoyi Chen: Department of Economics and Finance, University of Guelph, Guelph, ON N1G 2W1, Canada
Yiguo Sun: Department of Economics and Finance, University of Guelph, Guelph, ON N1G 2W1, Canada

Journal of Risk and Financial Management, 2018, vol. 11, issue 3, 1-15

Abstract: This paper compares the finite sample performance of three non-parametric threshold estimators via the Monte Carlo method. Our results indicate that the finite sample performance of the three estimators is not robust to the position of the threshold level along the distribution of the threshold variable, especially when a structural change occurs at the tail part of the distribution.

Keywords: difference kernel estimator; integrated difference kernel estimator; M-estimation; Monte Carlo; nonparametric threshold regression (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/1911-8074/11/3/49/pdf (application/pdf)
https://www.mdpi.com/1911-8074/11/3/49/ (text/html)

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:gam:jjrfmx:v:11:y:2018:i:3:p:49-:d:164335

Access Statistics for this article

Journal of Risk and Financial Management is currently edited by Prof. Dr. Michael McAleer

More articles in Journal of Risk and Financial Management from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2018-10-02
Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:3:p:49-:d:164335