December 22, 2022


Facts on the Ground

Assessing the crisis

The energy system that underpins contemporary life is marked with blindspots. Take the fossil fuel sector. Facing simultaneous existential and geopolitical vulnerability—due to Russia invading Ukraine, advances in renewable energy, and the climate imperative—there is profound uncertainty about how demand for fossil fuels will transform over the next five to seven years, the time it takes to bring a new gas or offshore oil field online. On the supply side, that uncertainty is matched by the lack of knowledge and monitoring of physical flows of commodities—let alone the kind of detailed information needed to model the ways that geopolitical, climate, and technological disruptions may play out.

Climate campaigners aim for an end to fossil fuel extraction—the minimum requirement to reduce catastrophic and irreversible climatic harm. But with much built infrastructure still relying on fossil fuels, unexpected supply shocks roil households, firms, and governments. New analysis from Isabella Weber, Jesus Lara Jauegui, Lucas Teixeira, and Luiza Nassif Pires shows that energy—in particular petroleum, coal, and oil and gas extraction—are intrinsically more important to inflation than other prices.

What if policymakers could assess inflation with the knowledge that it is driven partly by geopolitical shocks with an unknown timeframe to resolution, and can be approached by policy tools, poured concrete, and steel? These micro considerations do not tend to filter up to the macro modelers whose work informs monetary and fiscal policy. The consequences are significant. Unnecessary pain caused by misdiagnosing the drivers of inflation, and failing to employ targeted tools in response to it, narrows the political space needed to overcome systemic issues and in particular to act on climate.

Energy prices going to the moon are a problem, and we need to decarbonize while some fossil fuel extraction continues. The dilemma is how to navigate these tensions while transitioning a system that was already lacking in information in its previous state. Relying on opaque and volatile commodity markets is one thing; relying on those markets while they enter a messy twilight accompanied by geopolitical instability and climate impacts is entirely another.

To understand how fossil fuel commodities may become expensive, abundant, or inaccessible due to geopolitics, energy policies, climate impacts, and technology requires a granular view. Which assets are likeliest to be stranded? If we need new investment, where exactly is it required? Without this kind of detail, the simplistic global demand models used by policymakers, capital allocators, and influential experts will not be able to grapple with an emerging multipolarity, breakdowns in trading relationships, and climate shocks.

Facts on the ground

After working on several coal and coal-related bankruptcies in the 2010s, I realized that the state of underwriting was far from adequate, and that this was largely attributable to the sorry shape of commodity analysis. Coal is plentiful, and no one is concerned we might run out of it. Despite this lack of any plausible shortage, the volatility persisted.

On-the-ground research and contact with policymakers made the regular implosions and explosions of the coal price more comprehensible. Self-sufficiency and energy security were growing priorities for China, for instance, which was rapidly expanding its logistical networks to better exploit its own resources and expand its renewables output. On a global basis, coal supply did not change much year-to-year on a global basis. But on a local basis—the only level that matters at the end of the day for someone who needs coal—circumstances could change quickly, because “the market” was something of a fiction. Sure, there might be a lot of cheap fuel thousands of miles away, but unless it can be delivered it’s of no use. One port or rail addition and the whole situation is changed. This is a fact of life for bulky energy commodities that, unlike gold, you cannot just put in your pocket and move.

Intelligence about the physical world of resources and commodities mostly comes from private consultancies with opaque methodologies, whose business model is to manufacture consent to drill more holes and agencies that, while ostensibly public, don’t reveal their model workings and assumptions.

The temperamental nature of the coal industry led me back to some old university textbooks in operations research to see whether anybody had developed ways to measure the impacts of changes in physical transport networks. If there were a way to get this knowledge, you could answer straight forward questions like: “What is the impact of this piece of infrastructure?” Getting down to literally concrete things and their measurable impacts could guide your predictions, rather than the editorializing of China-watchers.

At best, the actually existing plumbing structures of various commodity markets were vastly underappreciated. At worst, they did not seem to exist for researchers. There was some literature on oil market infrastructure, but it had fallen out of fashion since the 1980s. Gas networks were well covered within national boundaries, but cross-border coverage was scant even as a global trade in liquid natural gas had emerged. Europe’s gas regulator, for example, had not modeled a Russia gas cutoff. Despite still being a major fuel source, coal was well analyzed as a seaborne market, but only on the national level—the typical analysis treated each country as a blob with no internal transport requirements or other constraints.

It seemed that years of relative price stability and fossil fuel oversupply following the boom in natural gas production from shale in the 2010s had allowed our understanding of sourcing and moving commodities to weaken, just as the computational power to do so systematically became cheaper and more available. A decade after a financial crisis ravaged the world, we now have regular and rigorous stress tests for banks, but nothing for any of our other markets, neither energy, food, nor other critical commodities.

Together with researcher Jorrit Gosens, I started to look at developing a network analysis methodology that could begin to fill these gaps. Despite the accessibility challenges of data on China—which range from not cheap to not available at all—we managed to map all of China’s coal mines, steel plants, and infrastructure to understand where China’s infrastructure boom was taking their coal imports. Modeling this granular data showed that China’s imports of coal are likely to fall substantially under various plausible scenarios, even if the country’s total amount of coal burnt doesn’t decrease much. That has implications for coal exporting countries, Indonesia and Australia in particular.

While we were engaged in this work, the Ukraine conflict went from Russian kayfabe to fact, and the importance of modeling commodity markets as logistical networks became even more urgent. No one was sure how much Russian supply in anything—coal, wheat, oil, or metals—could be rerouted, and how much of it would vanish. 

We had been working on more graphical models to take account of China’s informal ban on Australian coal, and that tooling and framework became ideal to make sense of the disorder following the invasion of Ukraine. How quickly can China and Russia put pipelines across the Amur River at their mutual border to relieve Russia’s oil glut? How much coal capacity can Mongolian rail networks take? Are China’s gas pipelines from Russia to China fully utilized? Will Chinese imports of LNG remain low all winter?

Neither China nor Russia is tipping their hand on these matters, leading to significant uncertainty about what happens next. Uncertainty is risk. Risk hurts liquidity and asset prices, and in turn confidence and growth. Mainstays of forecasting such as global demand curves are all well and good when commerce happens freely, but they are irrelevant when sanctions are flying back and forth and the Black Sea becomes a shooting gallery. When that happens, the established models used during the good old days of free commerce in energy products become a poor guide to the future.

While national governments and energy authorities may not be responsible for all commodity markets globally, they are likely to be held electorally responsible for their effects, particularly inflation and cost of living pressures. Gritty fundamental research is now very high stakes.

The fossil sector and the environmental movement are sticking to their respective positions—namely “drill more holes” and “no new holes.” Neither is able to explain what the path forward might be under our new geopolitical circumstances in terms of prices, emissions, and energy capacity over time, or how to assess the security tradeoffs of those choices. It’s difficult to block new gas development when prices are as high as they are now, but similarly, it’s naive to assume that renewables won’t be able to meet a lot of the demand. If there is one truth in all of this, it is that local, non-fossil sources of energy are the only strictly domestic strategy available unless you want to significantly expand coal burning.

Seeing the grid

Such blindspots do not plague electrical grid modeling. Within the boundaries of a regulated transmission area such as California’s Independent System Operator or the Australian National Energy Market, there is extensive research and data that are systematically updated with each new piece of legislation. The path to “electrify everything,” as Saul Griffith wants us to do, is clear and getting clearer. We know electrical engineers can monitor complex networks because if you live in the global North, you likely expect “three nines” of reliability—99.999 percent uptime of the grid. Grids are broadly well managed and have accountable regulatory bodies with extensive disclosure, a marked contrast to commodities.

There is one problem: limited information on the feedback loop from grid plans to global fossil prices and back again. This leads to a great deal of confusion. Most grid models assume some elasticity between coal and gas fuel-switching in power fleets—if gas prices are high you run more coal and if coal prices are high you run more gas. But what happens when every energy provider gets their gas and coal from the same markets? Heavily indebted players often have inelastic demand when they are close to their limits, and crowding leads to excessive volatility. That is the mess we are now in.

Modeling physical flows of fossil fuels is not inherently challenging, nor does it have all the challenges of maintaining instantaneous supply at all times and within a tight frequency range: there are vastly more challenging things done by power engineers every day of the week. Vast regions can now be analyzed in geographically precise detail, and projects like Openmod provide open source tooling for power grid decarbonization. Extending this to fossil demand would require some effort, but much less than what has already been expended thus far. What is more, using open source frameworks circumvents the general tendency of fossil fuel consultancies to provide projections that suit the assumptions of their customers, which are principally fossil energy businesses. There is a profound weakness in this space—customers often ask questions, hint at the answers they want, and are presented the conclusion with proprietary data, limited capacity to check the work, and no code review. Open modeling frameworks and open data provide a way forward with richer discourse around future pathways and risks.

Questions like, “What happens if the Straits of Hormuz are shut?” and “What will the Power of Siberia 2 pipeline between Russia and China mean for LNG flows?” become answerable rather than merely fodder for retired politicians to pontificate about on CNN. Further questions as to whether, say, centering the US’s entire LNG export capacity in Louisiana’s Hurricaine Alley is wise with respect to climate models, also now have clear answers. The future will remain unpredictable, but we can at least get some sense of where the fossil pinch points are for the near term, not to mention how much—if any—incremental new capacity will be required before we can say goodbye to fossil fuel for good.

In a world that is once again experiencing resource scarcity, certainty not only saves money, it also saves monetary policy. Central banks are concerned about their credibility on inflation. How can anybody have credibility without having first evaluated what the risk profile of future shocks might be? 

The future of energy looks different from today’s picture. Energy will be sourced much closer to where it is used, and much more from renewables, nuclear, and geothermal. This will mean a lot less trade across pipelines and in ships, and less exposure to geopolitical crisis, though perhaps more exposure to weather. 

Policymakers, investors and the public need an analytical framework that can include all the things that can happen to physical assets—not least of all wars and embargoes. With that work completed, we may get a clearer view of the consequences of moving slowly on the energy transition. 

The Polycrisis is a publication focusing on macro-economics, energy security & geopolitics.

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