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:
- The “$1 trillion in annual bribes” number, often attributed to the World Bank as an institution, actually comes from the appendix to a chapter by Daniel Kaufmann (a World Bank researcher) in the WEF’s 2005-2006 Global Competitiveness Report. That appendix relies on data from surveys of firms or households that ask how much the respondents typically pay each year in bribes (expressed as a percentage of household income in the case of household surveys, and as a percentage of sales in the firm surveys). Kaufmann then tries to convert these responses to dollar amounts, relying on highly dubious assumptions. He then extrapolates the data to other countries not included in the surveys by using even more dubious assumptions (principally the notion that the amount paid in bribes per capita each year is about the same in countries with similar scores on country-level corruption perception indexes). Even if we put aside a lot of the obvious problems with the methodology, the uncertainty in the estimated bribe quantity is huge, ranging from $600 billion to over $1.5 trillion, depending on which (strong and dubious) assumptions one chooses to make. The $1 trillion point estimate comes from the fact that it’s roughly the midpoint of the range, and has no further justification. Really the punchline of Kaufmann’s appendix, properly interpreted, is that though we know that there’s a lot of bribery, but we have no real idea how much. And it might also be worth noting that the data on which this estimate is based are more than 14 years old.
- The “$2.6 trillion annual economic cost of bribes” estimate (often also expressed as 5% of global GDP) is even worse. That number, attributed to the WEF, actually comes from basically nowhere. The WEF did not come up with this estimate itself. Rather, it cited to the same Kaufmann appendix that was used to come up with the $1 trillion in bribes figure. But the Kaufmann analysis didn’t purport to estimate the economic cost of all that bribery, so citing that study for any such estimate is clearly a simple and obvious error. So how did the WEF extract its figure for annual cost of bribery from the Kaufmann appendix? So far as I can tell, the Kaufmann study tried to “validate” its $1 trillion in annual bribes figure by seeing whether it was comparable t estimates of the magnitude of other sorts of illicit activity. In undertaking this “validation” exercise, Kaufmann cited two papers (from 1998 and 1999) that tried to estimate the amount (not the cost) of money laundering worldwide. One of those studies estimated the amount of money laundering at between $600 billion and $2.8 trillion, equivalent to 2%-5% of global GDP at the time (that is, in 1999). A 2007 World Bank document appeared to take up the high end of that range (5% of global GDP), misrepresent that estimate as the annual cost of bribery (rather than the annual amount of money laundering), and applied the percentage to 2007 global GDP, producing the $2.6 trillion figure, which was later cited by the WEF (without proper attribution).
This is clearly nonsense, as I explained in my posts on these figures from almost three years ago. I guess it’s mostly-harmless nonsense, given that no consequential policy or advocacy decisions depend on whether the annual cost of bribery is $500 billion or $1 trillion or $2.6 trillion or unknown. These numbers aren’t about rigorous cost-benefit analysis or even soft priority-setting; they’re just decoration, and their purpose would be served equally well by making up a random number ending in “-illion”. Still, I wish people would stop using made-up numbers as a rhetorical flourish, not only on general principle but because I think we should be collectively sending a message, and setting a tone, that facts and evidence and careful scrutiny of data are crucial for addressing corruption and other serious social problems.