Natural resources commodity prices volatility and economic performance: Evidence from China pre and post COVID-19

Volatility in the prices of natural resources particularly in the Covid-19 period is the subject of major concern in recent times. Although many studies have empirically investigated the influence of oil prices on economic growth and Covid-19 on oil prices. However, the current study contributes to the literature by investigating the causal linkage of natural resources commodity prices and economic growth in the pre and post Covid-19 period for China over the period from January 01, 2019, to April 01, 2021. This study employed the wavelet power spectrum, and the wavelet coherence approaches, and the frequency domain causality test, which is known for the causal identification in the long-run, medium-run, and short-run. The empirical findings reveal that the natural resource commodity prices are more vulnerable than the economic performance particularly in the Covid-19 peak period in China. However, the wavelet coherence approach demonstrates that a bidirectional causal association exists between natural resources commodity prices and economic performance at different frequencies and time periods. Additionally, the frequency domain causality test confirms that the natural resource commodity prices volatility significantly causes economic performance only in the medium-run. Based on the empirical findings, this study recommends that innovative technological and precautionary measures must be taken to accommodate or overcome natural disasters in the future, and tackle natural resources commodity prices volatility.

Automated summary

The study found that in the Covid-19 period, the prices of natural resource commodities in China were more vulnerable than economic performance, but there was a bidirectional causal relationship between them at different frequencies and time periods. The volatility in natural resource commodity prices significantly affected economic performance only in the medium-run according to the frequency domain causality test.