How to effectively stabilize China's commodity price fluctuations?

Boqiang Lin () and Bin Xu

Energy Economics, 2019, vol. 84, issue C

Abstract: The bulk commodities are basic goods, and their price fluctuations are directly related to the stability of a country's macro economy. Investigating the main driving forces of the commodity price fluctuations is the key to stabilizing the macro economy. Ignoring the objective facts that there are a large number of nonlinear relationships between economic variables, most of the existing scholars use the linear models to commodity price fluctuations. To compensate for the shortcomings of existing research, this paper uses the nonparametric additive regression model with data-driven features to investigate the main driving forces of China’s commodity price fluctuations. The results show that exchange rate has an “early promotion, late inhibition” inverse “U-shaped” nonlinear effect on commodity price fluctuations because the renminbi appreciates in the early stages, but depreciates in the later stages. The nonlinear impact of the real economy also appears an inverted “U-shaped” pattern, due to the changes in growth mode of the real economy. Similarly, international oil price produces an inverted “U-shaped” nonlinear effect, owing to the rise in international oil prices in the early stages and the decline in the later stages. However, the money supply has an “early inhibition, late promotion” positive “U-shaped” nonlinear effect on commodity prices. Therefore, government departments should formulate targeted policies over time to effectively stabilize China’s commodity prices.

Keywords: Commodity price fluctuations; Driving forces; Nonparametric additive regression models (search for similar items in EconPapers)
JEL-codes: G1 O13 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319303391

DOI: 10.1016/j.eneco.2019.104544

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