Lamborghinis in London

“Power tends to corrupt and absolute power corrupts absolutely.”

“Liberty consists in the division of power. Absolutism, in concentration of power.”

-Lord Acton, 1887 (1)

Corruption from concentrated oil wealth costs the world $US200B per year, an amount sufficient to install 100 gigawatts of wind turbine capacity per year - enough power for 70 million US homes - or to other great causes, instead of to oil prince playboy supercars and the like. How can vast wealth not corrupt when it is in the concentrated, inherited ownership of powerful families or clans? Here’s the analysis to show the costs.

Supercars (2), capable of 200mph, in a city center where traffic rarely moves much faster than walking pace.  But if money is no object, “why not?” is the question that, it seems, dozens of oil-rich playboys ask themselves. So, off to London they go, with their crazy cars air-shipped in.

These cars exemplify mind-boggling levels of inequality. Of young men with more time and money on their hands than is beneficial (3). And the indolence of their plutocrat owners - whose great riches come without commensurate work.

Our analysis here asks: are countries that gain much of their wealth from fossil fuel extraction more corrupt than other nations? The answer is, for the most part, yes. In fact, we provide a rough estimate - that corruption may cost $200 billion per year. Our analysis:

  1. Examines the statistical correlation between a country’s fossil-fuel wealth (measured as oil reserves per capita - what we call the reserve ratio here) and its corruption (as ranked by Transparency International). We’ll show how the data were used (and where they came from and we’ll note the strengths and limitations of the data and analysis
  2. Estimate the cost of corruption by gauging it against estimates of the total cost of corruption to the global economy.

Notes and caveats

  • Caveat #1: we’re not investment advisors. Nothing here, or in any of the other related notes, should be considered investment advice. 
  • Caveat #2: while we’re going to use best-available data - and make our sources and calculations freely visible - we’ll get some things wrong. Stick with us, help make our data more accurate. Let’s get this right. 
  • Caveat #3: we made some simplifying assumptions. One is that we applied a uniform value of oil to all countries’ reserves: $20/barrel. The absolute number has little significance on the analysis, but the uniformity does. But Saudi oil, with a much lower cost of production than any other nation’s, generates more asset value per barrel than does oil where extraction costs are much higher (e.g. the tar sands of Canada).

The data we use, and comments on their quality:

  • Fossil fuel reserves: data from OPEC. (4)
    • Limitations on data: most comprehensive data including non-OPEC members is from 2013; data is reported by countries themselves and may not be reliable - for example, UAE estimated reserves are shown as unchanging from 1996 to 2013. All data in millions of barrels (quality and yield not considered).
    • OPEC data seem to largely exclude oil from fracking. Fracked oil is a large part now of the oil reserves of the US.
  • Valuation of fuel reserves: the fossil fuel reserves converted to $USD at $20 per barrel, without consideration of varying prices, etc.
  • Population and GDP data: from World Bank (5)
    • Except: data on Venezuela is from multiple other sources.
  • Corruption index data: from Transparency International. (6)
    • The Transparency CPI index is used without modification EXCEPT that Transparency ranks the least corrupt countries highest (viz. Denmark CPI = 88) so for graphical depiction purposes we depict (100-CPI), so that the most corrupt countries earn the highest ranking.
    • Overall data: Transparency International does not normally use the formal naming conventions as formalized by large, multinational organizations, so we altered the names in the fields to enable the VLOOKUP functions in the Google worksheets to work uniformly.
  • These data are aggregated and analyzed at the spreadsheet linked here. (7)

Correlation between corruption and fossil fuel wealth

Our goal is to see how the degree of corruption of a state aligns with its fossil fuel wealth. Transparency International has been tracking, and trying to quantify, the corruption of nearly all the world’s countries since 1993. It does so via in-country surveys of how ordinary life and the processes of government and business are corrupted, and it aggregates corruption data from other sources using different approaches (8). Transparency’s corruption perceptions index (CPI) is used as the basis of our analysis.

Our first chart projects the raw data for dozens of countries. It’s hard to look at this graph and imagine a simple correlation between corruption (horizontal axis) and wealth from fossil fuels per capita (vertical axis). 

There are too many countries in the data field to depict clearly: the blue bubble at the top is Kuwait, the second-highest, to the far right (more corrupt), is Venezuela.

One can also see, looking at the many countries clustered along the bottom, that countries with low or moderate levels of fuel reserves per capita may or may not be corrupt: the large pink and red bubbles to the left (least corrupt) are Denmark and Norway; the small dark green bubble to the far right (most corrupt) is Sudan; the relative sizes of these bubbles reflect that they’re proportionate to GDP/capita.

But what if we consider instead the extent to which fossil fuel reserves dominate the economy? We took a shortcut to consider that: we compared the fossil fuel reserves, still valued at $20/barrel to the GDP / capita of each country. Here we get a more interesting and useful picture. The following two charts depict the asset value of fossil fuels / capita divided by the GDP / capita as the factor to compare with corruption. Thus: we’re measuring how much of the country’s wealth derives from oil reserves. We depict this twice: once with the names of countries (but most of them overlap and are unreadable) and once without the names of countries. Top right: overlapping bubbles - the highest ratios of fossil fuel asset value to GDP (both per capita) AND highest levels of corruption: Venezuela and Libya.

And below with names not shown. Bubbles here are proportioned to total national GDP: the large blue bubble is US; the large red circle is China. Here it is evident: the least-corrupt countries also have much lower values of oil assets as a fraction of their GDP. 

This does indicate that a high dependence of a country’s wealth and economy on fossil fuel assets correlates with high degrees of corruption. One can quantify this further by calculating the correlation coefficient for countries based on their fossil fuel wealth (9). In the following chart, we project the correlation coefficient across the set of all 38 countries. The top 3 countries (warning: low n) yield a 0.99 correlation coefficient vs the reserve ratio, with the correlation dropping to just 0.28 for all countries considered (10). (The correlation between fossil fuel wealth and corruption becomes very weak when the ratio of aggregate reserves to GDP drops below 2.5.)

This shows, with high confidence, that corruption is indeed highly correlated with the extent to which a country’s wealth is concentrated in fossil fuel assets - the correlation increasing with a rising ratio of reserves to GDP.

The cost of fossil fuel corruption

So, how much does corruption cost? And how much specifically does it cost in the context of economies largely dependent on fossil fuel industries?

At its simplest, in economic terms only, corruption’s cost arises because monies are taken away from creating enduring asset value, and instead go to less productive uses. A playboy buying a Lamborghini is using funds that aren’t creating new infrastructures back home (including schools), or starting or investing in an asset-creating firm. But still, the supercar was designed, built, and customized; the money did go somewhere: Sant’Agata Bolognese in Italy, or its corporate parent, Audi in Ingolstadt, Germany, for Lamborghini.

The United Nations has estimated that corruption’s harm to the global economy is about $US3.6 Trillion ($3,600 billion) per year (11). Assuming the global economy to be $88T - $140T (ranges from nominal to PPP (12), then losses to corruption range from 2.5% to 4% of the whole world’s economy. Taking only the higher range of this and applying it to the value of fossil fuels - about $6T / year at wholesale - would suggest that corruption costs as much as $US240 billion per year, while the mid-point percentage (3.25%) would imply corruption costs of $US195 billion per year (13). Thus, a good estimate might be that fossil fuel industry corruption is $US200 billion per year.

Remembering our quest: to consider the business case for the end of fossil fuels. We estimated previously that total fossil fuel sales at retail total about $US6T per year, and about $US3T/year at wholesale (14). We estimate these companies to have aggregate profits of about $1T, and so can see that considering the costs of corruption would make a significant dent in the overall profits. Furthermore, while no industry is exempt from corruption, it is infeasible to imagine that large-scale deployment of solar panels and wind turbines (and even nuclear plants) would engender corruption on the scale in fossil fuels. At a wild, wild guess: moving to non-fossil fuel energy sources will free up as much as $150 billion per year now trapped in corruption (15).



Additional Information

1 John Dalberg-Acton, Lord Acton. Two separate quotations, the first from his correspondence, 1887. The other undated.,_1st_Baron_Acton and

2 Image: Lamborghinis and other cars in London. 

3 Idle hands are the devil’s workshop, etc.

4 Despite the origin in OPEC, it has data on other, non-OPEC member nations.

5 downloaded as .xls

6 download “full data set” as zip and saved as .xls


8 and see also which lists some of the organization’s own challenges in keeping its parent company and the operations of some national chapters (including, particularly the US chapter) themselves beyond reproach. There are, however, no better data on this subject anywhere.

9  Calculations performed using the CORREL function in Google sheets. 

10  How this graph was created. The data point furthest right correlates Corruption with reserves / GDP for the three most oil-rich countries in our list. The next point (12500 on horizontal axis) adds a 4th county; the next (about 6800 on horizontal, 0.77 vertical) adds a 5th, and so on, until the points on the far left include all countries. The big drop in correlation from the topmost point to the next is because Iraq is very much more corrupt than its ratio of fuel assets to GDP would alone imply. The next data added is that of Saudi Arabia, and the correlation coefficients normalize.



13 This combines a high-range estimate - 4% - with a low-range estimate: we show that the highest oil reserves are associated with highest corruption, but then assume that fossil fuel industries are no more corrupt than the average of all countries and industries worldwide. Anecdotes from the energy sector suggest that corruption is rife, so the estimates here should be considered conservative.


15 Or, more cynically, $150 billion per year would be equivalently available for corrupt inducements to enable the transition to green energy sources. Sales of Lamborghinis might not diminish, but the buyers would be different.