Oil Shocks and Purchasing Power: Bit o' Spatial Analysis Fun

One of the professors at GMU that works with us, Laurie Schintler, has been working on an oil shock model to see what impact different global events could have on purchasing power. It is all still preliminary but the analysis was very intriguing so we thought it would be fun to put it out for comment and scrutiny. Shock models can be controversial and would be great to hear what folks think about the merits of taking a different, spatial approach. It is less about looking a peak oil and more about what diminishing reserves mean for purchasing power and economic growth when shocks happens.

The goal was to first create a baseline spatial consumption/production model of global oil. The idea being that some countries are more dependent on foreign oil than other countries, and which countries they are dependent on for that oil varies widely. Different geo-political events will impact a different critical oil production center, and as a result each event will impact the purchasing power of dependent countries differently.

The ability to understand which markets will lose purchasing power across the globe depending on which event occurs should be a useful metric by which to optimize supply chains and mitigate financial risk across businesses and government. The model can be adjusted in response to any global event that might impact purchasing power through effects on oil production and consumption.

To keep it interesting we modeled four possible scenarios:

1. A Russian invasion of the Ukraine
2. An Israeli attack on Iran
3. A violent coup in Venezuela
4. Massive rebel attacks in Nigeria

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These four scenarios are simply demonstrations of the capability. To estimate the relative impact of an oil supply shock on a country’s purchasing power, for each scenario, we use a simple demand and supply model. In that model, we first assume that a country’s oil consumption is satisfied by the following relation:

C = (I-E) + S

Where,

C = consumption of oil
I = imports of oil
E = exports of oil
S = indigenous contribution to oil (e.g., from oil stock)

The model estimates for each country the relative reduction in purchasing power, through the immediate increase in fuel prices that would arise from a reduction in imports from the country or countries whose exports are reduced due to a supply shock scenario. Reductions in imports for a country that arise from the supply shock scenario depend on the share of oil that country receives from the affected exporting country. The breakdown of each nation’s imports by country of origin was estimated through a two-tier process, based on publicly-available data.

We first took actual oil import and export flows between major regions in the world and selected countries (Europe, Central and South America, Middle East, Former Soviet Union, Singapore, Japan, China, Rest of Asia, USA, Canada and Mexico), and then used relative exports from each of these locations to estimate the most likely breakdown of imports for each region and country. Intra-region imports were also generated. The latter estimation process was necessary due to the fact that the data on imports for a nation by country of origin is scant.

There are only a few selected countries that have that information published on the Internet. For most countries, only total imports and exports of oil are available. The relative reduction in purchasing power for a country was then estimated based on the differential between initial supply, where demand and supply are in equilibrium, and the loss in supply based on the estimated reduction in imports.

For each scenario, we assume the most extreme supply shock – i.e., 100% reduction in exports from the countries whose exports are impacted by the scenario. It should be noted, though, that the model we have developed is set up to do simulations so that one could do a sensitivity analysis using different percent reductions in exports. Further, the model can also be used to estimate the impact on the purchasing power of a country based on changes in the demand for oil or the indigenous supply of a country (e.g., tapping into more reserves ).

There are a couple of caveats to the analysis that should be noted. First, the impact of a scenario on purchasing power of a country would ultimately be tempered by the country’s own available stock and ability to tap into reserves and the ability to recover lost imports from oil trading partners. This could be modeled using an oil import diversity (accessibility) index. Second, the impact on purchasing power for a country could also be impacted on its dependence on oil versus other energy types (e.g., natural gas, nuclear power, etc.). Last, the precise impact on purchasing power in dollars for a country would ultimately depend on the share of that country’s consumption of oil in relation to total consumption, and how this relates to GDP and its components.

The next step is to build a bit more spatial rigor into the simulation by using a gravity model to bring in the friction of distance. Step two is to begin to look at long term economic impact and what role substitution effects could play in impacts on purchasing power. This is still very early phase – about a weeks worth of work – but would be great to get any feedback on the approach and how it could be more useful.