The globe’s growing demand for energy and concerns over climate change are driving the need for renewables and related low-emission technologies. At Baillie Gifford, we’re on the lookout for companies that can gain a competitive edge and generate strong returns by leading the way.
Existing holdings across our clients’ portfolios include makers of wind turbines, solar panels, electric vehicle batteries, and hydrogen electrolyzers, such as Vestas, LONGi, Northvolt, and Nel. They also comprise suppliers of aluminum, nickel, lithium, and other raw materials, including Rio Tinto, PT Vale Indonesia, and Albemarle. And while we believe renewables have superior long-term growth prospects to fossil fuels, hydrocarbon companies can still play a critical role. For example, Reliance is reinvesting its oil refining profits into developing cutting-edge hydrogen fuel cells and solar panels.
As long-term growth investors, we’re excited about these companies’ potential and intend to explore further opportunities for years to come.
We believe many of the factors that led ‘cleantech’ innovators to underperform financially in the early 2000s are now behind us. But we’re aware that three concerns need to be addressed:
- Renewable electricity sources need to demonstrate that they can scale to meet different types of energy demands.
- Companies need to spend significant sums on physical infrastructure, requiring investors to support firms that are capital-intensive.
- Governments and companies need to have confidence in the advantages of a fast energy transition to overcome caution and inertia.
We can’t yet know exactly how the energy and climate transition will unfold over the next five, 10, let alone 50 years. But we should expect the unexpected. We should be open to scenario analysis that challenges incremental thinking and explores the complexities of the deep systems changes that likely lie ahead.
A recent study from Oxford University’s Institute for New Economic Thinking (INET Oxford) provides one such opportunity. It challenges consensus forecasts, suggesting they don’t properly account for the implications of long-term exponential growth.
The work is well-founded and calls to mind how progress in computing and the internet caught many by surprise. Moreover, the researchers involved are highly credible, including Prof J Doyne Farmer, a complex systems scientist whose work we sponsor and who recently joined us to discuss the findings.
The academics ask why other studies repeatedly underestimated the deployment of renewable energy technologies and overestimated their costs. They conclude that models relied on by the International Energy Agency (IEA) and the Intergovernmental Panel on Climate Change, among others, are unduly pessimistic about future trends in renewables and carbon emissions. Moreover, the researchers propose that a rapid shift to renewable technologies could save society trillions of dollars.
The feedback flywheel
The authors base their approach on Wright’s Law. You can read more about it below. But the key insight is that a ‘learning curve’ applies to wind turbines, solar panels, and other renewable technologies: for each cumulative doubling in production, the cost of manufacturing each unit falls by a constant percentage.
That gives rise to a virtuous feedback cycle: resulting price drops stimulate demand, leading to efficiency gains, allowing manufacturers to cut prices further, and so on. And because the price cuts are exponential, the loop speeds up as it goes.
The feedback loop of cost cuts and rising demand
One consequence is that deployments of successful technologies tend to follow an S-curve. Early growth seems slow as the exponential effect takes time to build. Then a period of ‘hypergrowth’ takes hold.
The bigger the market size, the longer hypergrowth endures before demand eventually tapers off as the market gets saturated.
The S-curve model of technological deployment
However, fossil fuels don’t benefit from the same effect. While engineers have continually improved extraction processes, the need to work in ever-more extreme environments as resources become harder to find cancels out the savings. In addition, for 50 years the actions of the OPEC cartel have added social and political complexities to the market prices of these energy commodities. As a result, oil, gas, and coal prices are roughly the same as they were 140 years ago, once you adjust for inflation.
The key message here is that renewable energy is a technology, while fossil energy is a commodity. Technologies can access learning curves and persistent cost deflation. Commodities, it seems, cannot.
Theodore Wright was involved in the design of military, civilian, and racing aircraft when he developed his formula.
He was determined to tease out the relationship between the cost of manufacturing a plane and the number of units produced. In 1936, after 14 years of study, he published his findings. They detailed a ‘curve relationship’: for every doubling of the quantity of aircraft made, production costs (ie labour, materials, factory overheads) fell by a constant percentage. In effect, the more planes workers made, the more they learned.
Wright deduced the ‘learning rate’ for the aircraft he studied resulted in a 10–17 percent cost drop each time the number built doubled. The rate varied as the cost of raw and purchased materials took on greater importance as production increased. Follow-up studies by others observed the relationship applied to other technologies, from semiconductors to electric car batteries, albeit with different learning rates.
Wright went on to head the US’s efforts to increase plane production during World War Two. But his ‘law’ may be his most enduring legacy. About four decades after his death, researchers at MIT and the Santa Fe Institute found it to be more accurate than five rival progress-predicting formulas.