Brian Potter challenges a comfortable narrative in the energy sector: the idea that renewable energy is destined to get cheaper simply because it is a "technology," while fossil fuels are doomed to remain expensive "commodities." This piece is notable not for dismissing the cost advantages of wind and solar, but for dismantling the rigid binary that suggests only manufactured goods follow learning curves. For investors and policymakers betting their futures on a smooth, exponential cost decline for renewables, Potter's data-driven skepticism offers a necessary reality check.
The Myth of the Binary
The prevailing theory, often cited by groups like the Rocky Mountain Institute, posits a clean split. "Design and technologies beat commodities because they enjoy learning curves and are limitless," the theory claims, suggesting that while old energy relies on centralized, dirty extraction, new energy comes from modular, scalable manufacturing. Potter argues this framing is too neat. He writes, "Regardless of the mechanisms, I think the 'technologies vs. commodities' theory is, in practice, actually bundling a few different questions together." By conflating price trends, supply elasticity, and production dynamics, the theory obscures more than it reveals.
Potter's analysis reveals that the distinction is far fuzzier than proponents admit. He points out that commodities have historically gotten cheaper too. "Oil got cheaper for the hundred-year period from the 1860s to the 1960s," he notes, a fact that complicates the narrative of inevitable fossil fuel price spikes. The core of his argument is that while manufactured goods do show a stronger tendency for price declines, commodities are not immune to efficiency gains. He highlights that even the graph used by the Rocky Mountain Institute to prove commodities don't get cheaper actually shows coal-generated electricity falling by a factor of ten over 70 years, driven by technological improvements in the plants themselves.
"Commodity prices can decline over time thanks to technology improvements and economies of scale, and technologies can be affected by depletion dynamics and other diseconomies."
Critics might argue that the volatility of commodity markets still makes them a riskier long-term bet than the predictable cost curves of solar panels. Potter acknowledges this volatility but suggests it stems from specific market structures, like cartels, rather than an inherent property of being a commodity.
The Hidden Costs of Scale
The most striking part of Potter's commentary is his reversal of the usual script: technologies face their own version of depletion. While a wind turbine doesn't consume fuel, it does consume the best locations. "We have seen wake effects for years, and knew they happen," Potter quotes an expert regarding offshore wind, noting that as capacity expands, turbines must be placed closer together, reducing efficiency. This is a classic diseconomy of scale.
He further argues that social friction acts as a constraint similar to resource depletion. As renewable projects expand, they face increasing local opposition, a dynamic he calls "NIMBYism" in effect. A 2023 report from Columbia University is cited to show that "local opposition to renewable energy facilities is widespread and growing, and represents a potentially significant impediment to achievement of climate goals." This suggests that the "limitless" nature of renewable technology is an illusion when physical space and social license become the bottlenecks.
Conversely, Potter reminds us that commodities are deeply technological. The extraction of oil and gas has been revolutionized by innovations like hydraulic fracturing and PDC drill bits. "Thanks to fracking, proven reserves of oil and natural gas in the US have actually increased since the year 2000," he writes, demonstrating how technology can counteract the depletion dynamics that supposedly doom commodities. The boundary between the two categories is porous; a commodity is often just a technology applied to a natural resource, and a technology can run into the same physical limits as a mine.
The Learning Curve Fallacy
Finally, Potter tackles the statistical heart of the debate: do commodities follow a learning curve? The answer, he suggests, is complicated by data limitations. When plotting price against cumulative production, most commodities do not show the clean, downward-sloping lines seen in manufacturing. However, Potter identifies a critical flaw in how this data is often interpreted. "If some amount of early production is missing from your learning curve dataset, this will distort the linear relations," he warns. Since mining and agriculture have existed for millennia, modern datasets often miss the early, high-cost phase of production, making it impossible to draw a straight line from the start.
He references historical context to bolster this point. Just as Hotelling's rule describes the optimal depletion path of non-renewable resources, the price history of coal shows that efficiency gains in the 1960s halted the decline in thermal efficiency, causing fuel costs to become the dominant factor. This nuance is often lost in the rush to declare renewables the inevitable winners. Potter's data shows that while manufactured goods have a higher probability of price declines, the gap is narrowing, and the dynamics are far more interactive than the "insurgent vs. incumbent" narrative suggests.
Bottom Line
Potter's strongest contribution is exposing the "technologies vs. commodities" theory as a convenient oversimplification that ignores the complex interplay of physical limits, social friction, and technological innovation in both sectors. The argument's biggest vulnerability is that it may underestimate the sheer speed of manufacturing cost reductions in renewables compared to the stubborn inertia of fossil fuel infrastructure. Readers should watch for how local permitting battles and site-specific resource limits begin to dictate the true cost of the energy transition, regardless of the technology's theoretical learning curve.