Senator Elizabeth Warren has made reduction of corruption a central plank of her 2020 presidential campaign. Whether or not we believe that she’s a girly reincarnation of Mark Twain, Albert Einstein, or Nelson Mandela, all of whom were avowed socialists, it’s hard to argue the point. The problem is that all but the corrupt agree that corruption is bad, but, apparently, it’s impossible to measure how bad.
We on The Other Side are inexorably drawn to unquantifiable problems; we cannot turn away. In this particular case, we decided to put one set of expert data side by side with another to see if we could find a way of estimating the cost of corruption.
The first of our datasets is published by Transparency International (TI), a not-for-profit organization devoted to the reduction of corruption worldwide. TI maintains an Anti-Corruption Hub that aggregates their research, authoritative studies, and statistically sound surveys on the topic of corruption. On an annual basis, they produce a Corruption Perception Index that ranks 170 nations around the world on a scale from 0 (purely corrupt) to 100 (breathtakingly honest).
In 2017, New Zealand was the world’s least-corrupt country with a score of 89 out of 100. The US tied Austria and Belgium for 16th with a score of 75. Other notables: Canada and the United Kingdom were tied for 8th with a score of 82, China was 77th with a score of 41, and our new pal Russia was 135th with a score of 29. (We can trust Vladimir Putin more than the sum of our intelligence agencies, right?)
If you peruse the Transparency International list from top to bottom, you’ll find that your wallet is less likely to be stolen in Chile than Mexico, your subsidiary’s managing director is less likely to be extorted by local police in Botswana than South Africa, and US envoys are less likely to be deceived by Iranian mullahs than Russian oligarchs. But the problem remains: Using TI data alone, there’s no way to estimate the cost of corruption. However, when TI’s corruption scores are aligned with the World Bank’s per capita income (PPP) data, a clear correlation jumps off the page. (See Note 1.)
The 20 nations with the lowest corruption (highest Transparency International scores) generated an average per capita income of $57,155 in 2016. The second 20 generated an average of $36,000, or 37% less than the top 20 nations, et cetera, as follows:
- Top 20: Average TI score: 81; average per capita income: $57,155
- 21-40: Average TI score: 64; average per capita income: $36,000
- 41-60: Average TI score: 53; average per capita income: $23,329
- 61-80: Average TI score: 42; average per capita income: $15,236
- 81-100: Average TI score: 38; average per capita income: $13,327
- 101-120: Average TI score: 33; average per capita income: $9,946
- 121-140: Average TI score: 29; average per capita income: $8,909
- 141-160: Average TI score: 23; average per capita income: $3,711
According to the best data extant, there is a palpable cost of corruption, it is plainly visible, and it is huge. Maybe we should care about how corrupt our nation has become in the last generation or so—and what’s going on in Washington right now.
1) Gross National Product (GNP) is an estimate of the value of all final products and services turned out by a nation’s residents over a given period of time.
2) We urge you to visit the Transparency International website, especially if you’re planning to travel outside the US.
One thought on “The Cost of Corruption”
What metrics are used to determine correlation? Simply lowering the score cannot have a statistically significant impact on corruption score. It’s what goes into the mix, but i fail to see where a low GDP per capita, e.g.a change of only 4 points Avg CR corruption rating is the results of a GNP of
$1,000.. I would posit a lower GDP/capita would have a signicant impact on corruption score rating. Need to determine source of input metrics aand what is being measured, specifically.