Abstract
The present paper has two main objectives: first, to accurately estimate commodity price uncertainty; and second to analyze the uncertainty connectedness among commodity markets and the macroeconomic uncertainty, using the time-varying vector-autoregressive (TVP-VAR) model. We use eight main commodity markets, namely energy, fats and oils, beverages, grains, other foods, raw materials, industrial meals, and precious metals. The sample covers the period from January 1960 to June 2020. The estimated commodity price uncertainties are proven to be leading indicators of uncertainty rather than volatility in commodity markets. In addition, the time-varying connectedness analysis indicates that the macroeconomic uncertainty has persistent spillover effects on the commodity uncertainty, especially during the recent COVID-19 pandemic period. It has also found that the energy uncertainty shocks are the main drivers of connectedness among commodity markets, and that fats and oils uncertainty is the influence driver of uncertainty spillovers among agriculture commodities. The achieved results are of important significance to policymakers, firms, and investors to build accurate forecasts of commodity price uncertainties.