Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set
Journal of Commodity Markets, 2021, vol. 23, issue C
The long-run behavior of real primary commodity prices, especially whether these series are trend stationary or contain a unit root, has been a topic of major debate in applied economics. In this paper, I perform a meta-analysis and combine the evidence of 12 representative studies on the subject in order to reach a unified conclusion about the presence of unit roots in these prices. The studies use different testing procedures, but share the common null hypothesis of a difference stationary process. Also, they use the individual price indices from the Grilli and Yang data set that is arguably one the most popular sources of long-term data on commodity prices. The combined evidence against unit roots in real primary commodity prices is strong: out of 24 cases, the unit root is not rejected in at most four. This rate means that real primary commodity prices are mean reverting and thus, to some degree, forecastable.
Keywords: Primary commodity prices; Unit roots; Grilli and Yang data; Meta-analysis (search for similar items in EconPapers)
JEL-codes: C12 C22 O13 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jocoma:v:23:y:2021:i:c:s2405851321000027
Access Statistics for this article
Journal of Commodity Markets is currently edited by Marcel Prokopczuk, Betty Simkins and Sjur Westgaard
More articles in Journal of Commodity Markets from Elsevier
Bibliographic data for series maintained by Catherine Liu ().