Those who work in the anticorruption field are likely familiar with the frequent citation of quantitative estimates of the amount and impact of global corruption. Indeed, it has become commonplace for speeches and reports about the corruption problem to open with such statistics—including, for example, the claim that approximately US$1 trillion in bribes are paid each year, the claim that corruption costs the global economy US$2.6 trillion (or 5% of global GDP) annually, and the claim that each year 10-25% of government procurement spending is lost to corruption. How reliable are these quantitative estimates? This is a topic we’ve discussed on the blog before: A few years back I did a couple of posts suggesting some skepticism about the US$1 trillion and US$2.6 trillion numbers (see here, here, here, and here), which were followed by some even sharper criticisms from senior GAB contributor Rick Messick and guest poster Maya Forstater.
This past year, thanks to the U4 Anti-Corruption Resource Centre, I had the opportunity to take a deeper dive into this issue in collaboration with Cecilie Wathne (formerly a U4 Senior Advisor, now a Project Leader at Norway’s Institute for Marine Research). The result of our work is a U4 Issue published last month, entitled “The Credibility of Corruption Statistics: A Critical Review of Ten Global Estimates.” (A direct link to the PDF version of the paper is here.)
In the paper, Cecilie and I identified and reviewed ten widely-cited quantitative estimates concerning corruption (including the three noted above), tried to trace these figures back to their original source, and assess their credibility and reliability. While the report provides a detailed discussion of what we found regarding the origins of each estimate, we also classified each of the ten into one of three categories: credible, problematic, and unfounded.
Alas, we could not rate any of these ten widely-cited statistics as credible (and only two came close). Six of the ten are problematic (sometimes seriously so), and the other four are, so far as we can tell, entirely unfounded. Interested readers can refer to the full report, but just to provide a bit more information about the statistics we investigated and what we found, let me reproduce here the summary table from the paper, and also try to summarize our principal suggestions for improving the use of quantitative evidence in discussions of global corruption: Continue reading
Early last month, UN Secretary General António Guterres delivered some brief opening remarks to the Security Council at a meeting on the relationship between corruption and conflict. In these remarks, Secretary General Guterres cited a couple of statistics about the economic costs of corruption: an estimate, attributed to the World Economic Forum (WEF), that the global cost of corruption is $2.6 trillion (or 5% of global GDP), as well as another estimate, attributed to the World Bank, that individuals and businesses cumulatively pay over $1 trillion in bribes each year. And last week, in her opening remarks at the International Anti-Corruption Conference, former Transparency International chair Huguette Labelle repeated these same figures.
Those statistics, as I’ve explained in prior posts (see here and here) are bogus. I realize that Secretary General Guterres’ invocation of those numbers shouldn’t bother me so much, since these figures had no substantive importance in his speech, and the speech itself was just the usual collection of platitudes and bromides about how corruption is bad, how the international community needs to do more to fight it, that the UN is a key player in the global effort against corruption, blah blah blah. Ditto for Ms. Labelle–her speech used these numbers kind of like a rhetorical garnish, to underscore the point that corruption is widespread and harmful, a point with which I very much agree. But just on principle, I feel like it’s important to set the right tone for evidence-based policymaking by eschewing impressive-sounding numbers that do not stand up to even mild scrutiny. Just to recap: Continue reading
GAB is pleased to publish this Guest Post by Maya Forstater, well-known analyst on business and sustainable development, on a topic of continuing concern to scholars and activists working on corruption and development matters.
Are unreliable guesstimates and made-up statistics mildly irritating, indispensably powerful or potentially dangerous in the public debates on corruption? The topic comes up so often on the Global Anti-Corruption Blog that it has been given its own own three-letter acronym: WAGs (or Wild Ass Guesses).
Those at the sharp end of advocacy maintain, with some justification, that in the battle for attention, an arrestingly big number makes all the difference. But as Rick has argued, overinflated figures can also cause harm.
Something similar happens on the related topic of tax and illicit flows. One example of this is the widespread belief that ‘developing countries lose three times more to the tax avoidance by multinational companies than they receive in aid’. This much quoted WAG gives the impression of huge potential gains for the poorest countries, but is based on a chain of misunderstandings . In practice the magnitudes of revenues at stake are likely to be several times smaller than aid for the countries where that comparison matters.
Similarly, broad estimates of illicit flows or the scale of the black economy (“trillions”) are often presented in ways that suggest that the sums to be gained from tackling corporate tax avoidance are larger than any serious analysis supports.
I have written about these big numbers previously in a paper published by the Centre for Global Development here (or here for the short version).
But what harm do such numbers do, compared to their power at getting people talking about the issues? Is it really worth pointing out misunderstandings and myths in pursuit of a more rigorous and careful approach to evidence? (Or as I have been asked‘ Do you ever wonder how much you help the tax abusers?’)
I see four key dangers from inflated perceptions of the numbers: Continue reading
Matthew sparked a lively discussion last week on the use “of widely-repeated . . . statistics” that are in fact “unreliable guesstimates misrepresented as precise calculations—and at worst, completely bogus” in discussions about corruption. He cited the claims that “$1 trillion in bribes are paid annually” and that “corruption costs the global economy $2.6 trillion per year” as examples. The former, a wild guesstimate, and the latter not even that are routinely accepted as fact in media accounts and policy notes issued by development agencies and appear even in papers purporting to be serious academic works. I do not link to examples for two reasons. One, there are so many that I would have to choose which ones to cite, and I don’t want to be accused to playing favorites. Second, the links would embarrass the guilty by calling them out. But many readers will know of whom I speak, and those who don’t can easily compile a list of offenders thanks to the magic of internet search engines.
I think Matthew did those concerned about combating corruption a great service by prompting debate about the use of such numbers, and I applaud him and those who replied for moving the discussion forward. At the same time, I fear Matthew may have inadvertently pushed the discussion off-track with his observation in the opening paragraph that “in the grand scheme of things, made-up statistics and false precision are not that big a deal.” I say this because, in responding to Matthew’s post, readers focused on a single issue: how much help it can be in discussions about controlling corruption to throw around phony numbers.
If the only question were whether what can fairly be termed a “wild ass guess” about the extent of corruption or some type of corruption or the losses it causes or what-have-you is if it helps advances policies that will help stamp corruption out, then Matthew is right; “made-up statistics and false precision” aren’t a big deal. But suppose WAGs, by which I include both unsupported guesstimates and bogus numbers, are harmful too? That not only are they sometimes useful by drawing attention to the issue or prompting action, but that sometimes they retard the cause of combating corruption. Then what?
Below are two ways corruption WAGs can be harmful and a modest proposal for lessening that harm without calling a complete halt to their use. Continue reading
In my post a couple weeks back, I expressed some puzzlement about the source of the widely-quoted estimate that corruption costs the global economy approximately $2.6 trillion, or roughly 5% of global GDP. I was hoping that someone out there in GAB Reader-Land would be able to point me to the source for this figure (as several GAB readers helpfully did when I expressed similar puzzlement last year about the source for the related estimate that there are approximately $1 trillion in annual bribe payments). Alas, although several people made some very insightful comments (some of which are in the public comment thread with the original post), this time it seems that nobody out there has been able to point me to a definitive source.
I’ve done a bit more poking around (with the help of GAB readers and contributors), and here’s my best guess as to where the $2.6 trillion/5% of GDP number comes from: Continue reading
Last year, I published a post expressing my puzzlement regarding the source of the widely-cited statistic that over $1 trillion dollars are paid annually. I was pleasantly surprised by the speed with which several GAB readers pointed me to the original source that described the methods and data used to calculate that number—and while I wasn’t entirely satisfied, it was at least nice to know where the number came from.
I’m hoping someone out there can help me with a very similar question: Within the last few months, I’ve been at several conferences and meetings where someone has quoted the figure that worldwide corruption (not just bribery) imposes annual costs to the global economy of approximately $2.6 trillion, roughly 5% of global GDP. I’ve looked and looked, and I cannot for the life of me figure out where this number comes from. Continue reading
I’ve posted before (see here, here, and here) about some of my concerns regarding the accuracy of the estimates people sometimes throw around about the total amount of bribes paid each year (sometimes given in absolute terms, sometimes as a percentage of global GDP, but in all cases based on dubious extrapolations from suspect data). But for the moment I want to put those concerns aside to make another point: Even if we knew the total amount of bribes paid, that would not necessarily tell us much of anything about how much bribery costs society. (And that’s true even if we limited attention to economic costs, narrowly construed.) This is not an original point – lots of people have made it, and indeed it’s fairly obvious when you stop to think about it. Yet I keep seeing references to estimates of the amount of bribery that treat these figures as if they were measures of the cost of bribery. (For examples, see here, here, here, here, and here.) But that’s just not right. Continue reading