The semiconductor chip shortage of 2021 perfectly demonstrates the degree to which global supply chains are interconnected, and the problems that can arise when production a chokepoint ruptures. Taiwan accounts for 63% of the global semi-conductor market by value, followed by South Korea with 18% and China on 6%. A surge in demand for semiconductors from electronics manufacturers, coupled with the worst drought in over half a century (chip makers require enormous amounts of water to clean the wafers) snarled chip production from the country. The typical lead time between ordering a chip and it being delivered increased from around 3 months pre-pandemic up to around 5 months by mid-2021.
Commodities derive a significant part of their value from network effects. For example, the value of oil is, at least in part, derived from the transportation and refining network that serves it (the pipelines, tankers, refineries and so on), which in turn enables end consumers to derive value from it. Oil, and for that matter coal or natural gas can be burnt outside of this network, but without access to it the value of the fossil fuels are compromised – the range of applications and the market for which they can serve are severely diminished.
As the US ascent to global supremacy in the 20th century was inseparable from oil, global powers are now vying to control the key energy technologies of the future: renewable energy, batteries, digital networks, electric vehicles, and so on. Countries have a strategic interest in being technology makers, not technology takers in these critical areas. Hydrogen is another battleground for technological and economic supremacy between the established and rising powers of this world.
Hydrogen is the most common element in the universe, accounting for three-quarters of its mass. French scientist Lavoisier named the gas ‘hydrogen’ after the Greek name (hydro = water, genes = to create) after discovering that burning hydrogen produces water, and no carbon dioxide. The energy density of hydrogen is higher than fossil fuels, there is three times as much energy per unit weight embedded in hydrogen as there is for petrol, diesel or jet fuel. It has had a long potted history as the answer to human energy needs – one of periodic hype followed by lengthy hibernation.
Putting a price on carbon places the burden for carbon emissions released into the atmosphere (the environmental externality) firmly on those responsible. What is known as the polluter pays principle.
But instead of dictating who should reduce emissions, where and how they do it, a carbon price provides a price signal. If emission cuts fail to meet targets then the price of carbon will rise, and vice versa if targets are overachieved. Polluters must then decide for themselves whether to stop their carbon emitting activities altogether, act to reduce their emissions, or simply carry on regardless and pay for it via the carbon price.
The seaborne trade in dry bulk commodities provides a strong indication of the changing dynamics in global commodity demand. The import of dry bulk commodities (iron ore, coal, grains and minor bulks such as fertiliser) by ship accounts for approximately one-third of overall dry bulk trade, with the rest being transported across land across fixed routes borders (for example, by truck and rail).
The seaborne trade gives a strong indication of who the marginal buyer in the market is. That kind of information is important to know if you want to understand the motivations of different physical commodity market participants, and how committed they are.
First published on ChAI
“Forecasts usually tell us more of the forecaster than the future.” – Warren Buffet
Commodity market forecasters, like others who offer their views on the outlook for other financial markets are subject to several specific behavioural biases. These include confirmation bias (seeking out information that confirms our own worldview and reject or ignore any disconfirming evidence), recency bias (expecting the future to look very similar to the recent past), and theory-induced blindness (factors important in driving historical past are assumed to have the same weighting in the future). These and many other emotional and cognitive biases can result in poor predictions, influenced only by the individual biases of the forecaster.