Economics at your fingertips  

Commodity prices and global economic activity: A derived-demand approach

Angelo Mont'Alverne Duarte, Wagner Gaglianone, Osmani Guillén and João Issler ()

Energy Economics, 2021, vol. 96, issue C

Abstract: We propose a derived-demand approach to explain the positive correlation and the synchronicity between the growth rates of commodity prices and of economic activity at the global level. Our focus is on important traded commodities, which supply function is very price inelastic in the short run, such as oil and major metal commodities. Our contributions are as follows. We first show the synchronicity of oil-price and global activity cycles using the tools of the common-feature literature. Second, we show how to improve forecasts of global activity using commodity prices, noting that we observe the latter at an almost continuous-time basis, but observe the former at a much lower frequency and with considerable delay. Third, we show the usefulness of optimal forecast combinations for oil prices employing a wide array of macroeconomic and financial variables. The out-of-sample R2 statistic for model combinations can reach up to about 14%, a major improvement over the previous literature.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Commodity Prices and Global Economic Activity: a derived-demand approach (2020) 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:

DOI: 10.1016/j.eneco.2021.105120

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

Page updated 2023-09-08
Handle: RePEc:eee:eneeco:v:96:y:2021:i:c:s0140988321000256