Comment by hybrid_study 3 days ago
The post leans too hard on “we have no idea.” Population numbers are estimates with error bars, especially in places with weak census infrastructure, but that’s not the same as ignorance. Most countries run censuses (sometimes badly) and use births/deaths/migration accounting to update totals. Calling them “fake” is misleading — it’s uneven data quality, not numerology. “Large uncertainty” ≠ “no idea.”
Two countries, ranking 32nd and 41st in Africa have not had a census. Those others have had old census conducted: so we have "some idea" of their population.
Countries have incentives to manipulate population data. Most error that I’m aware of is not attributable to poor data quality. For example, if you have a real estate bubble you have a strong incentive to show population growth.
>For example, if you have a real estate bubble you have a strong incentive to show population growth.
That's one source of bias that is present at a specific time. Mostly you would have competing incentives. There is usually more than one agency that runs does the counting. Vital records registration, voter rolls and tax payers lists, for example are separate agencies in some countries. Not every tax payer is a voter and not everyone who was born still lives in the country. The sources are sometimes cross-referenced too. Then there is usually a place that needs to do macroeconomic forecasting and needs to have some numbers to do it's job.
The first rule in Saul Alinsky's Rules for Radicals:
1. Power is not only what you have but what the enemy thinks you have.
Do you have specific examples?
This study published in Nature [0] says that rural populations in particular are typically UNDERCOUNTED (exactly like the Papa New Guinea in the OP's article), and that this happens at similar rates across poorer and wealthier countries: "no clear effect of country income on the accuracies of the five datasets can be observed."
That study has...issues.
https://human-settlement.emergency.copernicus.eu/ruralPopDis...
You are conflating known and unknown unknowns, otherwise known as Knightian uncertainty. As the article says, many countries have not run censuses in many years and/or manipulate the numbers.
I think "no idea" is an entirely reasonable summary of the magnitude of the uncertainty.
To me, "no idea" suggests the number is likely off by an order of magnitude or more, and even the worst case country in this article was less than 2x with bigger countries having better numbers.
That might be true in measuring abstract absolutes. But I'd agree that if you don't even know if your population is larger or smaller than it was 40 years ago, then it's perfectly fair to say that you have "no idea" what's going on.
Widening your claimed range makes your evidence for the claim stronger. In this situation we can make useful conclusions with strong evidence, with population ranges that are annoyingly wide but not that wide.
And yet... The examples mentioned and the justifications for big errors/fakes in many countries (that historically have been highlighted for scares around overpopulation) are very plausible. "Most countries run census" is not the same as "most countries run mostly reliable census" or "most of the world population is covered by a reliable census".
Aren't there plenty of incentives for over expressing population numbers in many countries, specially in underdeveloped ones?
There are growing sentimental, denialist, conspiracy, narratives on social media that anything that paint US being out of proportion has to be fake. It's up there with flat earths and "birds don't exist" theories. From the article...
> The true population of the world, Bonesaw said, was significantly less than 1 billion people.
Worldwide, there are over 5 billion smartphones.[1] Yes, some people have more than one. They have to connect to the network, so there's a constant census of cellphones.
I think you are missing one of the key point of the article. Some census are indeed fake, as in falsified not as in uncertain, because population is used to allocate resources and as a proxy for power and there is therefore a strong interest in falsifying them.
That's why somme statistics look weird. That's also why things heavily relying on demographic data need to be question. It's particularly significant when it comes to green house gas emissions for example and climate modeling.
> The Democratic Republic of the Congo, which by most estimates has the fourth-largest population in Africa, has not conducted a census since 1984. Neither South Sudan nor Eritrea, two of the newest states in Africa (one created in 2011 and the other in 1991), has conducted a census in their entire history as independent states. Afghanistan has not had one since 1979; Chad since 1991; Somalia since 1975.