Autocorrelation, structural breaks and the predictive ability of dividend yield

An-Sing Chen and Tai-Wei Zhang

Applied Economics, 2007, vol. 39, issue 5, 645-652

Abstract: We study whether dividend yield (DY) can predict aggregate stock returns while controlling for the effects of structural breaks in the parameters and bias induced by autocorrelation in the predictor variable. To do so we apply the Bai and Perron (BP) (1998, 2000) methodology to test for structural breaks and the bias-adjusted predictability test of Lewellen (2004). We show that although DY predicts market returns during the period 1946 to 1989, there exist 'natural' subsamples bounded by statistically detectable structural breaks that can last for long periods of time (up to 11 years in duration) when DY does not show significant forecasting power. This has important implications in that even if in the long-run DY actually provides strong predictive ability, investors should be mentally prepared for long dry spells of unpredictability with respect to DY.

Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/00036840500447708 (text/html)
Access to full text is restricted to subscribers.

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:taf:applec:v:39:y:2007:i:5:p:645-652

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036840500447708

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().