EconPapers    
Economics at your fingertips  
 

Spurious Regression Under Broken‐Trend Stationarity

Antonio Noriega () and Daniel Ventosa‐Santaulària
Authors registered in the RePEc Author Service: Daniel Ventosa-Santaulària

Journal of Time Series Analysis, 2006, vol. 27, issue 5, 671-684

Abstract: Abstract. We study the phenomenon of spurious regression between two random variables, when the generating mechanism of individual series is assumed to follow a stationary process around a trend with (possibly) multiple breaks in the level and slope of trend. We develop the relevant asymptotic theory and show that the phenomenon of spurious regression occurs independent of the structure assumed for the errors. In contrast to previous findings, the presence of a spurious relationship will be less severe when breaks are present in the generating mechanism of individual series. This is true whether the regression model includes a linear trend or not. Simulations confirm our asymptotic results, and reveal that in finite samples, the phenomenon of spurious regression is sensitive to the presence of a linear trend in the regression model and to the relative location of breaks within the sample.

Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9892.2006.00482.x

Related works:
Working Paper: Spurious regression under broken trend stationarity (2005) Downloads
Working Paper: Spurious regression under broken trend stationarity (2005) Downloads
Working Paper: Spurious regression under broken trend stationarity (2005) 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:bla:jtsera:v:27:y:2006:i:5:p:671-684

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is currently edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2024-09-05
Handle: RePEc:bla:jtsera:v:27:y:2006:i:5:p:671-684