Why do United Nations agencies fabricate data?

by Sasha Alyson

In several stories, I’ve highlighted a little-known tendency of United Nations agencies: Fabricating data that doesn’t exist and passing it off as real. (UNESCO calls this process imputation, which sounds nicer — but only because most of us don’t know precisely what it means.) Two examples:

  • In 2011, the U.N.’s Food and Agriculture Organization said there had been 833.2 million undernourished people in the developing world in 1990. This was a problem not only for those who were hungry, but also for the United Nations, which had set a goal of cutting the hunger rate in half by 2015. But the most recent FAO data found 838 million undernourished people – the number had actually increased since 1990. What to do? The FAO decided – 20 years after publishing them – that the 1990 figures had been wrong. The next year, it announced that undernourishment in 1990 had actually been not 833.2 million, but 980 million. That 18% jump, plus a few more data changes, arrived just in time to make it look like hunger was falling, and thus that the U.N. was close to meeting its goal. (Full story)
  • UNESCO, official keeper of U.N. education data, publishes detailed statistics for each region of the world – for example, it gives gender parity data for secondary-school students in sub-Saharan Africa. But it has actual data for only 4 of these 47 countries (and arguably not even good data). For the other 43 countries it made a guess, added them up, and produced a regional average which is of no use for anything, except to prevent a chart from looking empty. (Full story)

Why are these U.N. agencies so eager to fabricate statistics?

In the case of the hunger data, it’s obvious: The U.N. was desperate to show that its Millennium Development Goals (MDGs) were a success. The FAO, perhaps reluctantly, produced the needed numbers.

Couldn’t they simply have said that it’s not possible to accurately count the undernourished people around the world?(1) Couldn’t UNESCO say, “We don’t have enough data to calculate regional averages for Sub-Saharan Africa”?

They could, so let’s look at why they don’t. Data from the past is valuable if it helps us make better decisions for the future. But that’s not what this data is about. Revised 20-year-old hunger statistics won’t help us plan tomorrow’s food policies. Nor will UNESCO’s flimsy regional averages help make school policy.

This data is about control. The U.N. wants to be the global database for numbers related to development. To fill that role, it must  produce numbers. And why does it want role? Several factors are at work.

Control of the data. By collecting and publishing so much data, the U.N. discourages others from doing so. That’s important. The U.N. does not merely compile and publish statistics produced by national governments, it processes these numbers along the way. Thousands of decisions are made regarding which numbers are seen, which are not, how they are combined and weighted… and when to toss out old data and recalculate it. Had a disinterested agency been the data-keeper, it seems highly unlikely it would have decided (again and again!) to recalculate the old hunger data just in time for the U.N.’s MDG report.

Keeping attention on the SDGs. After dishonestly claiming great success for the MDGs from 2000-2015, U.N. officials got the General Assembly to pass the Sustainable Development Goals, which push Western priorities to the forefront for another fifteen years.(2) The U.N. wants the world focused on these goals, pouring money and attention into them. But who watches the ballgame if there’s nobody announcing the score? Showing progress along the way (typically with statements like, “We have accomplished great things, but there is still much to do”) requires statistics.

An illusion of expertise. The U.N. has become the go-to source for a wide range of global statistics. That increases its standing as the go-to source for wisdom on how to interpret all this information, and what to do next.

Deciding what gets measured. Twenty years ago, the U.N. chose to define “education” as school enrollment, regardless of whether students learn anything. Within five years, it was clear to many observers that this was a big mistake. But the U.N. didn’t need to listen or change. It chose to remain focused only on enrollment, not on learning.(3)

It’s a job. The people who compile, massage, and report these statistics want to keep their jobs, and will go to great lengths to justify their work. The UNESCO Institute for Statistics has announced an “an urgent need for … more resources for data collection and analysis.” But we today have more education data than ever before in history, and schools in developing countries are getting worse. Data is not what’s missing.

They can get away with it. Recalculating 20-year-old data – again and again – was only one of the deceits used by the U.N. in 2015, as it claimed great success for the MDGs. The mainstream media was happy for the good-news story: We’ve reduced extreme poverty by half, and we’ve gotten more children than ever into school. Had a politician given such a glowing self-evaluation, the media would have asked a few hard questions. For the U.N.’s story, it did not.(4)

* * *

It would be useful to have an accurate picture of where we are now, and the direction things are moving. The U.N.’s imputed and re-re-re-recalculated statistics give merely the illusion of having that picture. The world would be better off if we knew that we don’t know. But for the U.N., imputed statistics help it maintain control over social policies in the global South.

Twitter comments

The tweet that announced this story has drawn a spirited discussion. Here are some of those comments.

Scottish Highlander, @Scot_Highlander: Nothing I didn’t already know. I spent 35 yrs in int’l development and the UN agencies are by far the most ineffective – yet in every country they succeeded in imposing they agenda. Mind you, they are not alone in masking their utter ineffectiveness behind nice publications.

Kgosi Nyathi, @kgosinyathi: You focus on UN agencies’ data. Do you trust World Bank and IMF data? Most importantly, what can third world countries do about the ‘fake UN data’?
[Sasha: Very good questions, I wish I could give better replies. I don’t often use World Bank data (and IMF even less). The Bank operates under many of the same dynamics as U.N. agencies, including a desire to look like it’s got good data even when it does not. But I find that WB staff are more inclined to disagree on issues, in contrast to the groupthink ethos at the U.N. That could lead to slightly more reliable numbers in some cases. But often, it’s the same junk on a different website. For example: UNESCO reported adult literacy in Vanuatu, as of 2014, at 84.7%. The World Bank puts the same data on its website. But a survey that actually tested literacy skills, rather than just asking people if they could read and write, put the number at 27%. (More at: Fobos: Fear Of Blank On Spreadsheet) I have no good solution, but I believe we must keep raising the issue, in conversations, online, in letters to newspapers, etc.]

Roost, @_Roost_er: I have worked for the UN. When I joined I was shocked to see the complacent attitude prevalent. Their procedural obstacles in getting anything done are beyond comprehension. Slow and unreal. Nothing gets done in the UN. Literally nothing. Big pays and good offices

SMCB, @SMCB50471318: I also find that definitions change without notice. This is a good way of pushing politics. Are they using the same definition of ‘undernourished’ ? (It is like ‘child poverty’. What was, no longer is, but the numbers keep going up!)
[Sasha: Good question. In this case, yes, they do define it, but very narrowly. You must be VERY malnourished for at least a year. A baby who starves to death in nine months will not be counted as ever having been hungry. The FAO, to its credit, calls attention to this narrowness. The UN does not.]

Prasad Raut, @PrasPro: UN is a scum because it is classic ‘No Skin In The Game’ bureaucracy.

Notes and Sources

Top graphic: These figures for undernourished populations in developing regions are from FAO “State of Food Insecurity” (SOFI) reports for 1992, 2003, 2005, 2011, 2012, and 2013, in that order. These statistics are often presented by the FAO as 3-year averages (e.g. 1988-1990, or 1990-1992), but appear in U.N. documents simply as “1990”. The reports (the titles vary slightly) can be downloaded from the FAO site. At the bottom of the page, as of Nov. 2020, are links by year; grey arrows allow you to see other years.

Further reading: A well-reviewed book on the general topic of development data is Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It, by Morten Jerven, Cornell University Press, 2013. He focuses on the poor quality of statistics produced by governments. However, these are the very numbers which are massaged by U.N. agencies, then repackaged as if they offer insight. Confirming what I had also concluded, Jerven writes: “With the exception of some instances of crop and population statistics, economic and social statistics are mostly produced for the consumption of the development community, especially for donors and the IMF and the World Bank.” That’s who they try to please.

1. In the past, FAO sometimes showed hunger estimates as a range – for example, on page 5 of its 2003 State of Food Insecurity in the World report. This is more honest, but someone decided that the world and the media liked the appearance of precision, even if it was faked. The FAO now gives these numbers with breath-taking pseudo-accuracy: For example, by stating that in 1990 there were 1015.3 million undernourished people in the world – after having filled that same spot on the spreadsheet, two years earlier, with the number 848.4 million. It does not know the number. The pseudo-precise statistic hides that reality.

2. Despite their 17 goals and 169 targets, the SDGs manage to ignore major issues such as weapon sales and tax havens that greatly impact the global South but make big profits for Western corporations. I’ve briefly explored how the SDGs promote Western priorities in: The SDGs: What’s missing?

3. It’s not that the U.N. was unwilling to change goals midstream. On several occasions, it redefined the original MDG goals when they became troublesome. It did not have to keep defining education as school enrollment rather than learning; it chose to do so.

4. As the U.N. and FAO scrambled to make their hunger data show improvement, Argentine writer Martin Caparros was one of the few who called attention to this. In a New York Times opinion piece he wrote: “This is not conscious corruption. It’s a symptom of an institutional culture that has to prove it is achieving important progress. The 1990 change justifies the United Nations’ efforts and jobs, as much as it quiets our consciences.”

4 thoughts on “Why do United Nations agencies fabricate data?

  1. This year we could watch WHO offering all kinds of advices during this pandrmic crise, as if they were experts.
    It was clear they knew nothing about it, because every now and then they changed their position.
    A couple of months ago, WHO declared that they couldn’t do more because lack of money.

    That’s exactelly the same behavior.

  2. How else could any of the pro-market, pro-capitalist propagandists push their agenda on inequality, by claiming poorer parts in the world are also getting better, if there is no agency that can fake that data into existence?

  3. Its unfortunate how IMF imposed herself on developing nations. They recently imposed IPPIS on Nigeria, making so much money of it. However, Nigerians recently discovered that IPPIS is a big scam. The Nigerian government has failed to accept this fact, because IPPIS is a product of IMF. It was designed to enrich few people in Govt and IMF. The Academic Staff Union of Universities in Nigeria has refused to accept this fraudulent product of IMF.

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