The long-run relationship between stock prices and goods prices: New evidence from panel cointegration

Andros Gregoriou and Alexandros Kontonikas ()

Journal of International Financial Markets, Institutions and Money, 2010, vol. 20, issue 2, pages 166-176

Abstract: We examine the long-run relationship between stock prices and goods prices to gauge whether stock market investment can hedge against inflation. Data from 16 OECD countries over the period 1970-2006 are used. We account for different inflation regimes with the use of sub-sample regressions, while maintaining the power of tests in small sample sizes by combining time-series data across our sample countries in a panel unit root and panel cointegration econometric framework. The evidence supports a positive long-run relationship between goods prices and stock prices with the estimated goods price coefficient being in line with the generalized Fisher hypothesis.

Keywords: Stock; prices; Good; prices; Panel; cointegration (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/B6VGT ... 4996b60714039e9a1b49
Full text for ScienceDirect subscribers only

Related works:
Working Paper: The long run relationship between stock prices and goods prices: new evidence from panel cointegration (2008)
Working Paper: THE LONG RUN RELATIONSHIP BETWEEN STOCK PRICES AND GOODS PRICES: NEW EVIDENCE FROM PANEL COINTEGRATION
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: http://EconPapers.repec.org/RePEc:eee:intfin:v:20:y:2010:i:2:p:166-176

Access Statistics for this article

Journal of International Financial Markets, Institutions and Money is edited by I. Mathur and C. J. Neely

More articles in Journal of International Financial Markets, Institutions and Money from Elsevier
Series data maintained by Wendy Shamier ().