Commodity Price Shocks : Order within Chaos?
The prices of 27 internationally traded commodities are decomposed into transitory and permanent shocks by applying an ideal band-pass filter to monthly data from 1970–2020. The two types of shocks contributed roughly equally to price variations, b...
| Main Authors: | , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2021
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/undefined/693261633374058029/Commodity-Price-Shocks-Order-within-Chaos http://hdl.handle.net/10986/36343 |
| Summary: | The prices of 27 internationally
traded commodities are decomposed into transitory and
permanent shocks by applying an ideal band-pass filter to
monthly data from 1970–2020. The two types of shocks
contributed roughly equally to price variations, but with
wide heterogeneity. Permanent shocks ac-counted for
two-thirds of the variability in agricultural prices but
less than 30 percent in energy prices. The transitory shock
component revealed three medium-term cycles. The first (from
the early 1970s to the mid-1980s) and third (from the early
2000s to 2020 onward) exhibit similar duration and involve
almost all commodities, while the second (spanning the
1990s) is mostly applicable to metals, with the notable
absence of energy. The permanent shock components differ
across commodities, with an up-ward trend for most
industrial commodities and downward trend for agriculture.
Moreover, the permanent component of commodity prices where
investment is irreversible, including energy, metals, and
tree crops, exhibits a high degree of nonlinearities, which
also coincide with the two post–World War II supercycles. By
contrast, the permanent component of annual agricultural
prices is linear, reflecting greater flexibility in
investment allocation and input use of these commodities.
Prices of commodities subjected to widespread policy
interventions, such as international commodity agreements,
exhibit persistent deviations from linear trends. |
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