Abstract

AbstractSince the turn of the century, China has experienced economic growth that has called for rapid industrialisation, infrastructure growth and urbanisation, making China highly dependent on primary commodities. The resource intensive growth path followed by a slowdown in recent years has raised the question to what extent her demand for commodities can affect international commodity prices. To this end, recent studies have analysed the link between economic growth or slowdown on commodity prices using linear multivariate models. However, a problem is that commodity prices are known to be highly variable and characterised by multiple structural changes. With such characteristics of the data, it is likely to be the case one may obtain mis‐specified inferences from a linear multivariate framework. Accordingly, we make use of novel Flexible Fourier Form (FFF) econometric procedures to account for multiple breaks in the economic variables, which have better power and size properties over the standard linear models. We find that the persistence of economic variables employed in this study and their causal link are better approximated by such nonlinear FFF procedures. Our results show that there is evidence of short run predictability between selected commodity prices and economic growth in China. Further, the responses of different commodity prices to shocks in economic growth are quite profound especially for those cases where we find causal links with economic growth in China. While we find a significant impact of economic growth of China on commodity prices, the response varies for different commodities.

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