MacroPolo’s New Energy Geopolitics Index (NEGI) is composed of two equally weighted variables related to renewable energy: 1) independence and 2) capability. These two variables combined result in a proxy score for geopolitical influence in the context of the energy transition for each country in our sample.
While the independence variable is composed of just a single indicator, the capability variable involves numerous indicators. Here we elaborate on the variables, assumptions, sample selection, and data sources used to build the NEGI.
The global energy transition is expected to bring about two major trends. One is the increasing energy independence of countries as they shift away from fossil fuels and towards adopting climate technologies. Two is that each country’s capability in those technologies—defined in terms of value chains and exports—will shape their respective influence when it comes to the geopolitics of energy.
To understand how this works in practice, take the first two countries in the 2019 ranking. China leads the NEGI ranking thanks to a very high capability score combined with an average independence score. Should China continue to raise its independence score, in line with its current climate commitments, it would attain an even higher NEGI ranking and likely move into Quadrant IV.
Brazil was the runner-up because of its exceptionally high independence score, which is due to the large share of hydropower in its current energy mix. However, the country has a relatively low capability score because of its limited role in the value chains for wind, solar, and batteries.
As a consequence, a country like Brazil will have to significantly raise its capability score or risk being surpassed in the future by countries that already have high capability and have committed to ambitious decarbonization plans like Germany, the United States, or Denmark.
In this first iteration, we calculated the NEGI score (the sum of the capability + independence scores) for 25 countries over nine years. We will continue to update and expand the product over time. Data was predominantly collected from publicly available sources with some exceptions where proprietary data was used (see note on sources below).
Composition of the NEGI Visualized
The independence variable is calculated by tabulating each country’s renewable energy consumption (including hydropower) and dividing it by its overall primary energy consumption to derive a score. Nuclear power is not conventionally classified as a renewable energy source and was not included.
The capability variable is composed of indicators that help quantify a country’s production and export capability in three key climate technologies: lithium-ion batteries, solar photovoltaics, and wind turbines. These were selected because their deployment is expected to grow significantly over the next decade, revolutionizing the energy system of many countries.
Wind and solar are expected to become the most common energy sources globally. The International Energy Agency estimates that of the 90% of global renewables electricity that will be needed to reach net zero emissions by 2050, 70% will come from wind and solar.
Lithium-ion batteries are key to electrifying the transport sector and reducing reliance on oil. They are also one of the most established solutions for energy storage, which is key to enabling high renewable energy penetration rates.
To estimate national capability, we constructed indicators that quantify each country’s relative strength in various segments of the value chain, including exports. In the aggregate, the capability score can be interpreted as a country’s leadership in climate technologies.
Value Chain Indicator
The value chain indicator is further disaggregated into three segments: natural resources, manufacturing, and innovation (weighted 20%, 40%, and 40%, respectively).
The natural resources indicator is assigned the least weight because technological innovation and raw material recycling make these inputs less important to a country’s overall climate technology capability.
In other words, we assume a country’s natural resource endowments, while likely to add value to its domestic economy, will not bring the same level of geopolitical influence that oil and gas did. The capacity to produce finished products and generate innovate technologies will become more important.
Manufacturing and innovation indicators are assigned equal weight because while the former represents a country’s actual production capabilities, the latter proxies a country’s importance in generating intellectual property in these technologies. Both are crucial to developing new climate technologies and bringing them to market.
1. Natural Resources
Using available US Geological Services data, we calculated this indicator by adding national reserves or annual refinery production for 18 critical resources used to manufacture the climate technology products. Combining reserves with current production accounts for total potential production of a particular country.
The resources included are rare earths, lithium, cobalt, graphite, tellurium, niobium, silicon, manganese, gallium, indium, selenium, silver, tin, borates, fluorspar, cadmium, nickel, zinc, and copper.
This list could be updated in future iterations of NEGI as technologies evolve and the demand for resources increases or decreases.
This indicator is composed of a score based on the top 10 global manufacturers’ annual solar and electric vehicle (EV) battery shipments and wind installations, as well as the UNIDO Competitive Industrial Performance Index (CIP) score.
We relied on shipments and installations because those are the most common metrics used in those industries and because relying on total company revenue could be misleading since many have diversified business lines beyond the three products in question.
Moreover, we limited it to the top 10 companies because data beyond that sample were poor and because these companies today command between 70% to 90% market share in their respective industries.
This score was assigned to the country in which the parent company or majority owner is based, which can sometimes be different from company headquarters. We also accounted for change in company ownership over the years.
That score was then combined with the CIP score, which serves as a proxy for a country’s overall industrial strength and its potential to expand manufacturing capacity in key climate technologies. This combination helps paint a more holistic picture of a country’s manufacturing capability, especially since company data alone does not reflect subcomponent production or country-level production capacity.
We used the “family of 1 or greater” category of patents in the OECD dataset for environmental technologies, a large share of which are climate technologies, to derive an innovation indicator. Patents are an imperfect proxy for innovation, but they do capture some aspects of a country’s innovation potential. We will consider refining and expanding the innovation indicator in the future, including, for example, measures such as R&D spending and human capital.
4. Export Indicator
The export indicator is calculated using the harmonized schedule codes for the three products (850231 – wind. Electric generating sets wind-powered, 854140 – PV module, wafers, cells,850760 – Batteries. Electric accumulators; lithium-ion).
For each product category we multiplied the total number of trade partners a country has in a certain year with the total dollar value traded of the three climate technology products in that same year. We then logged the result and normalized the range between 0 and 1. This was done to reduce the impact of outliers that were skewing the index excessively. Treating the data in this way does not affect the final rankings of the countries and is helpful in generating a more intelligible visualization.
The export indicator reflects a country’s ability to supply the three products. Having significant export value and multiple trading partners can translate into a key capability in the geopolitical arena as it offers more potential channels of influence.
NEGI covers 25 countries, 19 of which are from the G20 group of countries (European Union was excluded because we wanted a sample of individual countries). This sample covers the bulk of the global economy and the majority of global trade, as well as most global emissions. In short, these countries are central to the global energy transition and its implications.
The additional six countries in the sample (Spain, the Netherlands, Denmark, Malaysia, Chile, and Vietnam) were selected because they hold important positions in the climate technology trade and value chain and represent important regional powers.
African countries are notably underrepresented in our sample. This was largely due to poor data availability, especially when it came to a country’s energy profile. We hope to include African economies like Nigeria and the Democratic Republic of Congo (DRC) in the future as data availability improves. These economies currently occupy niche areas in the renewable energy value chain (despite the DRC’s important role in cobalt production) so their omission should not affect the index’s results.
The index starts in 2011 because of significant data gaps prior to that year. Also, because the size of the renewable industry was very small then, it would have had a negligible geopolitical impact.
Notes on Data Sources and Data Limitation
We treated missing data in two ways. If the missing value is at the end of the time series in 2019, we imputed the missing value with the latest available data in 2018. If there is a data gap in the time series, we imputed the average of the before-and-after annual data for that country.
EV battery manufacturer data for 2011-2013 were omitted because we were unable to find reliable data. Because the EV industry was still in its infancy prior to 2013, we don’t believe this omission should excessively skew the results.
We used a plethora of publicly available sources, particularly in terms of the value chain. In addition to company annual reports, press releases, and financial statements, we relied on data published by consulting firms and news organizations: BNEF; Lux Research; IHS; Reuters; pv-magazine; pv-tech; Wind; SNE Research, GGII, Global Data; GWEC, and Energy1, among others.
We did our best to triangulate data from multiple sources to ensure they are as accurate as possible, though full verification of accuracy is impossible.