EconPapers    
Economics at your fingertips  
 

Bootstrap Procedures for Detecting Multiple Persistence Shifts in Heteroskedastic Time Series

Mohitosh Kejriwal, Xuewen Yu () and Pierre Perron
Additional contact information
Xuewen Yu: Purdue University

No WP2020-009, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: This paper proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by nonstationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-speciÖc bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. A comparison with existing tests that assume homoskedasticity illustrates the finite sample improvements o§ered by our methods. An application to OECD ináation rates highlights the empirical relevance of the proposed approach and weakens the case for persistence change relative to existing procedures.

Keywords: heteroskedasticity; multiple structural changes; sequential procedure; unit root; Wald tests; wild bootstrap (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2020-03
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
http://www.bu.edu/econ/files/2020/05/KPZ-bootstrap.pdf

Related works:
Journal Article: Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series (2020) Downloads
Working Paper: Bootstrap Procedures for Detecting Multiple Persistance4 Shifts in a heteroskedastic Time Series (2018) Downloads
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:bos:wpaper:wp2020-009

Access Statistics for this paper

More papers in Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Program Coordinator ().

 
Page updated 2024-02-23
Handle: RePEc:bos:wpaper:wp2020-009