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This paper investigates the switching effect of COVID-19 pandemic and economic policy uncertainty on commodity prices. We employ Markov regime-switching dynamic model to explore price regime dynamics of eight widely traded commodities namely oil, natural gas, corn, soybeans, silver, gold, copper, and steel. We fit two Markov switching regimes to allow parameters to respond to both low and high volatilities. The empirical evidence shows oil, natural gas, corn, soybean, silver, gold, copper, and steel returns adjust to shocks in COVID-19 outcomes and economic policy uncertainty at varying degrees––in both low volatility and high volatility regimes. In contrast, oil and natural gas do not respond to changes in COVID-19 deaths in both regimes. The findings show most commodities are responsive to historical price in terms of demand and supply in both volatility regimes. Our findings further show a high probability that commodity prices will remain in low volatility regime than in high volatility regime––owing to COVID-19-attributed market uncertainties. These findings are useful to both investors and policymakers––as precious metals and agricultural commodities show less negative response to exogenous variables. Thus, investors and portfolio managers could use precious metals, viz. Gold for short-term cover against systematic risks in the market during the period of global pandemic.

Climate change has become a global burden, requiring strong institutional quality and willingness to mitigate future impacts. Though emissions are transboundary and have the tendency of spreading from high emitting countries to low emitting countries, regional exposure, sensitivity, and adaptation readiness determine the extent of climate effects. The existing literature focuses on immediate drivers and damages of emission effects, failing to account for underlying mechanisms occurring via the nexus between emission levels, economic, social, and governance adaptation readiness. Here, this study broadens the scope of previous attempts and simultaneously examines climate change vulnerability across sectors including ecosystem services, food, health, human habitat, infrastructure, and water. We use the Romano–Wolf technique to test multiple hypotheses and present the spatial–temporal severity of climate vulnerability and readiness to combat climate change and its impacts. Besides, we assess the long-term impact of climate change readiness and income expansion on sectoral-climate vulnerabilities. We find that high-income economies with high social, governance, and economic readiness have low climate vulnerability whereas developing economies with low income have high climate change exposure and sensitivity. Our empirical evidence could be used to prioritize limited resources in addressing and managing adaptive actions of extreme climate change vulnerabilities.

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